"Key","Item Type","Publication Year","Author","Title","Publication Title","ISBN","ISSN","DOI","Url","Abstract Note","Date","Date Added","Date Modified","Access Date","Pages","Num Pages","Issue","Volume","Number Of Volumes","Journal Abbreviation","Short Title","Series","Series Number","Series Text","Series Title","Publisher","Place","Language","Rights","Type","Archive","Archive Location","Library Catalog","Call Number","Extra","Notes","File Attachments","Link Attachments","Manual Tags","Automatic Tags","Editor","Series Editor","Translator","Contributor","Attorney Agent","Book Author","Cast Member","Commenter","Composer","Cosponsor","Counsel","Interviewer","Producer","Recipient","Reviewed Author","Scriptwriter","Words By","Guest","Number","Edition","Running Time","Scale","Medium","Artwork Size","Filing Date","Application Number","Assignee","Issuing Authority","Country","Meeting Name","Conference Name","Court","References","Reporter","Legal Status","Priority Numbers","Programming Language","Version","System","Code","Code Number","Section","Session","Committee","History","Legislative Body"
"PATNHTMD","conferencePaper","2019","Ni, Zeyu; Shen, Beijun; Chen, Yuting; Meng, Zhangyuan; Cao, Junming","CrowDevBot: A Task-Oriented Conversational Bot for Software Crowdsourcing Platform (S)","","","","10.18293/SEKE2019-068","http://ksiresearchorg.ipage.com/seke/seke19paper/seke19paper_68.pdf","With the trends of developing software on the Internet, many software crowdsourcing platforms are emerging. They attract a lot of developers to bid for crowdsourced projects and develop software systems collaboratively. In this paper, we present CrowDevBot, a task-oriented conversational bot for software crowdsourcing platform, that aims to assist online users in completing crowdsourcing-related tasks in a more natural manner. The key idea of CrowDevBot is to: (1) combine a rulebased method and an SVM-NaiveBayes-C4.5 integrated learning method to discover users’ intention; (2) employ an integrated CRF (conditional random field) method with novel features to improve the performance of slot filling; and (3) leverage a software service knowledge base to unify entity names and predefine the key slots of user query. We implement CrowDevBot and integrate it into JointForce, an IT software crowdsourcing platform in China. To the best of our knowledge, this is the first time that a task-oriented conversational bot is practically used in software crowdsourcing platform(s). We evaluated our approach on real data set from JointForce. The results show that our intention detecting method achieves F1-score of 87% on the limited training data. For the slot filling, the F1-score of our integrated CRF model reaches 82%, 8% higher than that of the normal CRF model.","2019-07-10","2020-06-17 07:48:37","2021-05-29 18:25:02","2020-06-17 07:48:37","410-414","","","","","","CrowDevBot","","","","","","","en","","","","","DOI.org (Crossref)","","tex.ids: ni2019, niCrowDevBotTaskOrientedConversational2019a, niCrowDevBotTaskOrientedConversational2019b","","C:\Users\sant_si\Zotero\storage\PA47Q7Z4\Ni et al. - 2019 - CrowDevBot A Task-Oriented Conversational Bot for.pdf; C:\Users\sant_si\Zotero\storage\87P3NBCH\Ni et al. - 2019 - CrowDevBot A Task-Oriented Conversational Bot for.pdf; C:\Users\sant_si\Zotero\storage\23VABKS5\Ni et al. - 2019 - CrowDevBot A Task-Oriented Conversational Bot for.pdf; C:\Users\sant_si\Zotero\storage\M72X5C65\Ni et al. - 2019 - CrowDevBot A Task-Oriented Conversational Bot for.pdf","","chatbot; software development; crowd sourcing; included; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","The 31st International Conference on Software Engineering and Knowledge Engineering","","","","","","","","","","","","","","",""
"9N6ZVNUS","journalArticle","2018","Sannikova, Svetlana","Chatbot implementation with Microsoft Bot Framework","","","","","","","2018","2020-06-23 09:46:14","2021-01-07 01:56:36","","33","","","","","","","","","","","","","en","","","","","Zotero","","tex.ids: sannikovaChatbotImplementationMicrosoft","","C:\Users\sant_si\Zotero\storage\W5DGEBGM\Sannikova - Chatbot implementation with Microsoft Bot Framewor.pdf; C:\Users\sant_si\Zotero\storage\IL2B4UMI\Sannikova - Chatbot implementation with Microsoft Bot Framewor.pdf","","chatbot; software engineering; included; slack; thesis; communication; microsoft LUIS; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"G24SVNFS","conferencePaper","2019","Seering, Joseph; Luria, Michal; Kaufman, Geoff; Hammer, Jessica","Beyond Dyadic Interactions: Considering Chatbots as Community Members","Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI '19","978-1-4503-5970-2","","10.1145/3290605.3300680","http://dl.acm.org/citation.cfm?doid=3290605.3300680","Chatbots have grown as a space for research and development in recent years due both to the realization of their commercial potential and to advancements in language processing that have facilitated more natural conversations. However, nearly all chatbots to date have been designed for dyadic, one-on-one communication with users. In this paper we present a comprehensive review of research on chatbots supplemented by a review of commercial and independent chatbots. We argue that chatbots’ social roles and conversational capabilities beyond dyadic interactions have been underexplored, and that expansion into this design space could support richer social interactions in online communities and help address the longstanding challenges of maintaining, moderating, and growing these communities. In order to identify opportunities beyond dyadic interactions, we used research-through-design methods to generate more than 400 concepts for new social chatbots, and we present seven categories that emerged from analysis of these ideas.","2019","2020-06-23 09:46:28","2020-10-05 15:31:46","2020-06-23 09:46:28","1-13","","","","","","Beyond Dyadic Interactions","","","","","ACM Press","Glasgow, Scotland Uk","en","","","","","DOI.org (Crossref)","","tex.ids: seeringDyadicInteractionsConsidering2019","","C:\Users\sant_si\Zotero\storage\2XX5HBXH\Seering et al. - 2019 - Beyond Dyadic Interactions Considering Chatbots a.pdf; C:\Users\sant_si\Zotero\storage\N9CIXIY4\Seering et al. - 2019 - Beyond Dyadic Interactions Considering Chatbots a.pdf","","chatbot; included; HCI; communication; persona; social; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","the 2019 CHI Conference","","","","","","","","","","","","","","",""
"4YWBGKR6","conferencePaper","2019","Blersch, Martin; Weigelt, Sebastian; Tichy, Walter; Angele, Kevin","Automatic Generation of Virtual Assistants from Databases using Active Ontologies","","","","10.18293/SEKE2019-077","http://ksiresearchorg.ipage.com/seke/seke19paper/seke19paper_77.pdf","Virtual assistants such as Siri or Google Assistant are omnipresent. However, their development remains costly. One must either manually model the problem domain or provide thousands of labeled samples.","2019-07-10","2020-06-23 09:46:58","2020-10-05 10:24:40","2020-06-23 09:46:58","32-38","","","","","","","","","","","","","en","","","","","DOI.org (Crossref)","","tex.ids: blerschAutomaticGenerationVirtual2019","","C:\Users\sant_si\Zotero\storage\VJPG3WTM\Blersch et al. - 2019 - Automatic Generation of Virtual Assistants from Da.pdf; C:\Users\sant_si\Zotero\storage\KP78NK4L\Blersch et al. - 2019 - Automatic Generation of Virtual Assistants from Da.pdf","","chatbot; included; virtual assistants; dialogflow; Ontologies; lexical dictionary; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","The 31st International Conference on Software Engineering and Knowledge Engineering","","","","","","","","","","","","","","",""
"2SLL6A68","journalArticle","2020","van Brummelen, Jessica; Weng, Kevin; Lin, Phoebe; Yeo, Catherine","Convo: What does conversational programming need? An exploration of machine learning interface design","arXiv:2003.01318 [cs]","","","","http://arxiv.org/abs/2003.01318","Vast improvements in natural language understanding and speech recognition have paved the way for conversational interaction with computers. While conversational agents have often been used for short goal-oriented dialog, we know little about agents for developing computer programs. To explore the utility of natural language for programming, we conducted a study (n=45) comparing different input methods to a conversational programming system we developed. Participants completed novice and advanced tasks using voice-based, text-based, and voice-or-text-based systems. We found that users appreciated aspects of each system (e.g., voice-input efficiency, text-input precision) and that novice users were more optimistic about programming using voice-input than advanced users. Our results show that future conversational programming tools should be tailored to users programming experience and allow users to choose their preferred input mode. To reduce cognitive load, future interfaces can incorporate visualizations and possess custom natural language understanding and speech recognition models for programming.","2020-03-02","2020-06-23 10:05:40","2021-05-29 18:15:32","2020-06-23 10:05:40","","","","","","","Convo","","","","","","","en","","","","","arXiv.org","","tex.ids: vanbrummelenConvoWhatDoes2020 arXiv: 2003.01318","","C:\Users\sant_si\Zotero\storage\HUWNDAJX\Van Brummelen et al. - 2020 - Convo What does conversational programming need .pdf","","chatbot; software development; included; ASR; Useful; conversational agents; ref; cognitive load; Google STT; Google TTS; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"2Z225F9S","journalArticle","2019","Monperrus, Martin; Urli, Simon; Durieux, Thomas; Martinez, Matias; Baudry, Benoit; Seinturier, Lionel","Repairnator patches programs automatically","Ubiquity","","15302180","10.1145/3349589","http://dl.acm.org/citation.cfm?doid=3345321.3349589","","2019-07-29","2020-06-23 09:57:17","2020-11-05 12:21:13","2020-06-23 09:57:17","1-12","","July","2019","","Ubiquity","","","","","","","","en","","","","","DOI.org (Crossref)","","tex.ids: monperrusRepairnatorPatchesPrograms2019","","C:\Users\sant_si\Zotero\storage\MA2Q76AX\Monperrus et al. - 2019 - Repairnator patches programs automatically.pdf","","duplicate; software engineering; included; bots; devbot; repairbot; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"NBFEAH48","journalArticle","2019","Chukaleski, Martin; Daknache, Samer","The effect of test case design in software testing bots","","","","","","Traditional approaches of testing in software development include running the test cases on a software component, referred to as unit testing, which usually only tests a specific part of a component, as opposed to testing the whole flow of the system (end-to-end testing). Test bots are software automation tools that help improve the system testing via automation, which is beneficial for development teams as the test bots help decrease the amount of time spent on testing. As development projects become larger, it is important to focus on improving the test bot’s effectiveness. The test bots run a set of test cases that check whether the system under test meets the requirements set forth by the customer. This thesis uses a case study approach to investigate how test case designs can affect the test bots, and by using the findings gathered from the study, we aim to create a guide for test design schema for such bots. Furthermore, this study aims to find how the software testing practices in an IT company can differ from what the literature presents. We identify the main challenges when using test bots in the automotive industry and a guideline is composed of seven steps to aid stakeholders in designing tests where test bots are part of the testing cycles.","2019","2020-06-23 09:59:52","2020-12-01 15:21:33","","15","","","","","","","","","","","","","en","","","","","Zotero","","tex.ids: chukaleskiEffectTestCase2019","","C:\Users\sant_si\Zotero\storage\L8YU9M65\Chukaleski and Daknache - 2019 - The effect of test case design in software testing.pdf","","software engineering; included; thesis; bots; testbots; devbot; ref; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"ZBA5FUT2","journalArticle","2020","Brown, Chris; Parnin, Chris","Sorry to Bother You Again: Developer Recommendation Choice Architectures for Designing Effective Bots","","","","","","","2020","2020-06-23 09:59:33","2021-05-28 12:04:30","","5","","","","","","","","","","","","","en","","","","","Zotero","","tex.ids: brownSorryBotherYou2020","","C:\Users\sant_si\Zotero\storage\GJAD8RPA\Brown and Parnin - 2020 - Sorry to Bother You Again Developer Recommendatio.pdf","","software engineering; included; bots; devbot; behavioral science; MSR; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"7L2PU8ZC","journalArticle","2020","Melo, Glaucia; Law, Edith; Alencar, Paulo; Cowan, Don","Exploring Context-Aware Conversational Agents in Software Development","arXiv:2006.02370 [cs]","","","","http://arxiv.org/abs/2006.02370","Software development is a complex endeavor that depends on a wide variety of contextual factors involving a large amount of distributed information. This knowledge could include: technology-related tasks, software operating environments and stakeholder requirements. A major roadblock to using this knowledge in software development is that most of this information is implicit and captured in the developers minds (tacit) or spread through volumes of documentation. Developers, as they work often have to maintain mental models of these tasks as they produce the software. As a result, context can be easily lost or forgotten and developers often use trial-anderror approaches while finishing the project. This study aims at analyzing whether supporting software developers with a chatbot during task execution can improve the overall development experience. The chatbot can assist the developers with executing different tasks based on implicit contextual information. We propose an implementation to explore the viability of using textual chatbots to assist developers automatically and proactively with software development project activities that recur.","2020-06-03","2020-06-23 09:57:12","2020-10-16 10:14:59","2020-06-23 09:57:12","","","","","","","","","","","","","","en","","","","","arXiv.org","","tex.ids: melo2020a, meloExploringContextAwareConversational2020, meloExploringContextAwareConversational2020a arXiv: 2006.02370","","C:\Users\sant_si\Zotero\storage\DYIF6SPV\Melo et al. - 2020 - Exploring Context-Aware Conversational Agents in S.pdf","","software engineering; productivity; included; study; Useful; devbot; ref; wizard of oz; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"CE3S4MVT","journalArticle","2020","Dey, Tapajit; Mousavi, Sara; Ponce, Eduardo; Fry, Tanner; Vasilescu, Bogdan; Filippova, Anna; Mockus, Audris","Detecting and Characterizing Bots that Commit Code","arXiv:2003.03172 [cs, stat]","","","10.1145/3379597.3387478","http://arxiv.org/abs/2003.03172","Background: Some developer activity traditionally performed manually, such as making code commits, opening, managing, or closing issues is increasingly subject to automation in many OSS projects. Specifically, such activity is often performed by tools that react to events or run at specific times. We refer to such automation tools as bots and, in many software mining scenarios related to developer productivity or code quality, it is desirable to identify bots in order to separate their actions from actions of individuals. Aim: Find an automated way of identifying bots and code committed by these bots, and to characterize the types of bots based on their activity patterns. Method and Result: We propose BIMAN, a systematic approach to detect bots using author names, commit messages, files modified by the commit, and projects associated with the commits. For our test data, the value for AUC-ROC was 0.9. We also characterized these bots based on the time patterns of their code commits and the types of files modified, and found that they primarily work with documentation files and web pages, and these files are most prevalent in HTML and JavaScript ecosystems. We have compiled a shareable dataset containing detailed information about 461 bots we found (all of which have more than 1000 commits) and 13,762,430 commits they created.","2020-03-27","2020-06-23 09:59:58","2020-12-17 17:46:19","2020-06-23 09:59:58","","","","","","","","","","","","","","en","","","","","arXiv.org","","tex.ids: deyDetectingCharacterizingBots2020 arXiv: 2003.03172","","C:\Users\sant_si\Zotero\storage\93VIEDLS\Dey et al. - 2020 - Detecting and Characterizing Bots that Commit Code.pdf","","software engineering; included; bots; devbot; MSR; ML; ref; detection; design; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"ZYT3JXGJ","conferencePaper","2020","Okanović, Dušan; Beck, Samuel; Merz, Lasse; Zorn, Christoph; Merino, Leonel; van Hoorn, André; Beck, Fabian","Can a Chatbot Support Software Engineers with Load Testing? Approach and Experiences","Proceedings of the ACM/SPEC International Conference on Performance Engineering","978-1-4503-6991-6","","10.1145/3358960.3375792","https://dl.acm.org/doi/10.1145/3358960.3375792","Even though load testing is an established technique to assess loadrelated quality properties of software systems, it is applied only seldom and with questionable results. Indeed, configuring, executing, and interpreting results of a load test require high effort and expertise. Since chatbots have shown promising results for interactively supporting complex tasks in various domains (including software engineering), we hypothesize that chatbots can provide developers suitable support for load testing.","2020-04-20","2020-06-23 09:57:26","2021-05-29 18:25:19","2020-06-23 09:57:26","120-129","","","","","","Can a Chatbot Support Software Engineers with Load Testing?","","","","","ACM","Edmonton AB Canada","en","","","","","DOI.org (Crossref)","","tex.ids: okanovicCanChatbotSupport2020","","C:\Users\sant_si\Zotero\storage\BI4A839E\Okanović et al. - 2020 - Can a Chatbot Support Software Engineers with Load.pdf","","software engineering; included; bots; devbot; ref; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","ICPE '20: ACM/SPEC International Conference on Performance Engineering","","","","","","","","","","","","","","",""
"5RXBGXIE","conferencePaper","2019","Sharma, Vibhu Saujanya; Mehra, Rohit; Kaulgud, Vikrant; Podder, Sanjay","A Smart Advisor for Software Delivery - A Bot Framework for Awareness, Alerts and Advice","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","978-1-72812-262-5","","10.1109/BotSE.2019.00014","https://ieeexplore.ieee.org/document/8823628/","Software engineers typically rely on mental models of their project and peers for project-specific insights important to their work. Ever expanding software size and complexity makes it strenuous to maintain such mental models and leads to subjectivity. At the same time, consistent peer interactions lead to interrupts, thereby hampering productivity. Moreover, due to client mandates, typical project environments employ a plethora of heterogeneous tools, thus making the information retrieval process fairly complex. We believe that ‘digital coworkers’ leveraging Human-AI collaboration, have huge potential here to help out with such challenges. In this paper, we introduce the concept of Smart Advisor, an intelligence augmentation bot that employs domain and knowledge modeling and in-process analytics to automatically provide important insights (alerts and advice) and answer queries (awareness), using a conversational and interactive user interface.","2019","2020-06-23 09:57:54","2021-02-17 16:52:19","2020-06-23 09:57:54","22-23","","","","","","","","","","","IEEE","Montreal, QC, Canada","en","","","","","DOI.org (Crossref)","","tex.ids: sharmaSmartAdvisorSoftware2019","","C:\Users\sant_si\Zotero\storage\ZQ9D63LQ\sharma2019.pdf","","chatbot; software engineering; productivity; included; Useful; botse; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","","","","","","","","","","","","","","",""
"3LF78GV8","journalArticle","2017","Lebeuf, Carlene; Storey, Margaret-Anne; Zagalsky, Alexey","How Software Developers Mitigate Collaboration Friction with Chatbots","arXiv:1702.07011 [cs]","","","","http://arxiv.org/abs/1702.07011","Modern software developers rely on an extensive set of social media tools and communication channels. The adoption of team communication platforms has led to the emergence of conversation-based tools and integrations, many of which are chatbots. Understanding how software developers manage their complex constellation of collaborators in conjunction with the practices and tools they use can bring valuable insights into socio-technical collaborative work in software development and other knowledge work domains.","2017-02-22","2020-06-17 07:48:44","2020-10-15 15:19:56","2020-06-17 07:48:44","","","","","","","","","","","","","","en","","","","","arXiv.org","","tex.ids: lebeuf2017, lebeufHowSoftwareDevelopers2017a, lebeufHowSoftwareDevelopers2017b arXiv: 1702.07011","","C:\Users\sant_si\Zotero\storage\WLVJ23UB\Lebeuf et al. - 2017 - How Software Developers Mitigate Collaboration Fri.pdf; C:\Users\sant_si\Zotero\storage\VIEHVZPK\Lebeuf et al. - 2017 - How Software Developers Mitigate Collaboration Fri.pdf; C:\Users\sant_si\Zotero\storage\JB4Z6T4J\Lebeuf et al. - 2017 - How Software Developers Mitigate Collaboration Fri.pdf; C:\Users\sant_si\Zotero\storage\5WXTRD9L\Lebeuf et al. - 2017 - How Software Developers Mitigate Collaboration Fri.pdf","","chatbot; software engineering; included; HCI; social; ref; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"RRB9YEPQ","conferencePaper","2020","Carvalho, Antonio; Luz, Welder; Marcilio, Diego; Bonifacio, Rodrigo; Pinto, Gustavo; Dias Canedo, Edna","C-3PR: A Bot for Fixing Static Analysis Violations via Pull Requests","2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER)","978-1-72815-143-4","","10.1109/SANER48275.2020.9054842","https://ieeexplore.ieee.org/document/9054842/","Static analysis tools are frequently used to detect common programming mistakes or bad practices. Yet, the existing literature reports that these tools are still underused in the industry, which is partly due to (1) the frequent high number of false positives generated, (2) the lack of automated repairing solutions, and (3) the possible mismatches between tools and workflows of development teams. In this study we explored the question: “How could a bot-based approach allow seamless integration of static analysis tools into developers’ workflows?” To this end we introduce C-3PR, an event-based bot infrastructure that automatically proposes fixes to static analysis violations through pull requests (PRs). We have been using C-3PR in an industrial setting for a period of eight months. To evaluate C-3PR usefulness, we monitored its operation in response to 2179 commits to the code base of the tracked projects. The bot autonomously executed 201346 analyses, yielding 610 pull requests. Among them, 346 (57%) were merged into the projects’ code bases. We observed that, on average, these PRs are evaluated faster than general-purpose PRs (2.58 and 5.78 business days, respectively). Accepted transformations take even shorter time (1.56 days). Among the reasons for rejection, bugs in C-3PR and in the tools it uses are the most common ones. PRs that require the resolution of a merge conflict are almost always rejected as well. We also conducted a focus group to assess how C-3PR affected the development workflow. We observed that developers perceived C-3PR as efficient, reliable, and useful. For instance, the participants mentioned that, given the chance, they would keep using C-3PR. Our findings bring new evidence that a bot-based infrastructure could mitigate some challenges that hinder the wide adoption of static analysis tools.","2020-02","2020-06-23 09:59:42","2020-11-12 17:34:29","2020-06-23 09:59:42","161-171","","","","","","C-3PR","","","","","IEEE","London, ON, Canada","en","","","","","DOI.org (Crossref)","","tex.ids: carvalho2020a, carvalhoC3PRBotFixing2020","","C:\Users\sant_si\Zotero\storage\AGEZA4UV\Carvalho et al. - 2020 - C-3PR A Bot for Fixing Static Analysis Violations.pdf; C:\Users\sant_si\Zotero\storage\XL2K2J5W\Carvalho et al. - 2020 - C-3PR A Bot for Fixing Static Analysis Violations.pdf","","software engineering; included; bots; devbot; sonarqube; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER)","","","","","","","","","","","","","","",""
"QKN2D98C","conferencePaper","2017","Xu, Bowen; Xing, Zhenchang; Xia, Xin; Lo, David","AnswerBot: Automated generation of answer summary to developers' technical questions","2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE)","978-1-5386-2684-9","","10.1109/ASE.2017.8115681","http://ieeexplore.ieee.org/document/8115681/","","2017-10","2020-08-07 09:22:44","2021-05-18 16:10:37","2020-08-07 09:22:44","706-716","","","","","","AnswerBot","","","","","IEEE","Urbana, IL","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\JEZTE692\Xu et al. - 2017 - AnswerBot Automated generation of answer summary .pdf","","software development; included; bots; Useful; devbot; QnA; stackoverflow; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE)","","","","","","","","","","","","","","",""
"HP52HLYU","conferencePaper","2019","Matthies, Christoph; Dobrigkeit, Franziska; Hesse, Guenter","An Additional Set of (Automated) Eyes: Chatbots for Agile Retrospectives","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","978-1-72812-262-5","","10.1109/BotSE.2019.00017","https://ieeexplore.ieee.org/document/8823641/","Recent advances in natural-language processing and data analysis allow software bots to become virtual team members, providing an additional set of automated eyes and additional perspectives for informing and supporting teamwork. In this paper, we propose employing chatbots in the domain of software development with a focus on supporting analyses and measurements of teams’ project data. The software project artifacts produced by agile teams during regular development activities, e.g. commits in a version control system, represent detailed information on how a team works and collaborates. Analyses of this data are especially relevant for agile retrospective meetings, where adaptations and improvements to the executed development process are discussed. Development teams can use these measurements to track the progress of identified improvement actions over development iterations. Chatbots provide a convenient user interface for interacting with the outcomes of retrospectives and the associated measurements in a chat-based channel that is already being employed by team members.","2019-05","2020-06-23 09:57:03","2020-08-20 19:36:56","2020-06-23 09:57:03","34-37","","","","","","An Additional Set of (Automated) Eyes","","","","","IEEE","Montreal, QC, Canada","en","","","","","DOI.org (Crossref)","","tex.ids: matthies2019b, matthiesAdditionalSetAutomated2019","","C:\Users\sant_si\Zotero\storage\FZC7PZ8I\Matthies et al. - 2019 - An Additional Set of (Automated) Eyes Chatbots fo.pdf; C:\Users\sant_si\Zotero\storage\DXJU3MWQ\Matthies et al. - 2019 - An Additional Set of (Automated) Eyes Chatbots fo.pdf","","chatbot; software development; included; agile; collaboration; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","","","","","","","","","","","","","","",""
"GJJD3DRP","conferencePaper","2019","Subramanian, Venkatesh; Ramachandra, Nisha; Dubash, Neville","TutorBot: Contextual Learning Guide for Software Engineers","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","978-1-72812-262-5","","10.1109/BotSE.2019.00011","https://ieeexplore.ieee.org/document/8823619/","This document is poster submission on using conversational chat bot to guide a software engineer in their learning journey and keeping pace with the technology changes. We describe the motivation, technical approach, and experience of building, piloting such a Bot in a controlled setting and capturing the user feedback. The document also discusses future opportunities to extend and enhance the functionality.","2019-05","2020-06-23 09:58:09","2021-02-16 09:09:29","2020-06-23 09:58:09","16-17","","","","","","TutorBot","","","","","IEEE","Montreal, QC, Canada","en","","","","","DOI.org (Crossref)","","tex.ids: subramanianTutorBotContextualLearning2019","","C:\Users\sant_si\Zotero\storage\NLIHEW7G\Subramanian et al. - 2019 - TutorBot Contextual Learning Guide for Software E.pdf","","chatbot; software engineering; included; ASR; bots; poster; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","","","","","","","","","","","","","","",""
"MPI33XZ8","conferencePaper","2019","Rebai, Soumaya; Ben Sghaier, Oussama; Alizadeh, Vahid; Kessentini, Marouane; Chater, Meriem","Interactive Refactoring Documentation Bot","2019 19th International Working Conference on Source Code Analysis and Manipulation (SCAM)","978-1-72814-937-0","","10.1109/SCAM.2019.00026","https://ieeexplore.ieee.org/document/8930873/","The documentation of code changes is significantly important but developers ignore it, most of the time, due to the pressure of the deadlines. While developers may document the most important features modification or bugs fixing, recent empirical studies show that the documentation of quality improvements and/or refactoring is often omitted or not accurately described. However, the automated or semi-automated documentation of refactorings has not been yet explored despite the extensive work on the remaining steps of refactoring including the detection, prioritization and recommendation. In this paper, we propose a semi-automated refactoring documentation bot that helps developers to interactively check and validate the documentation of the refactorings and/or quality improvements at the file level for each opened pull-request before being reviewed or merged to the master. The bot starts by checking the pullrequest if there are significant quality changes and refactorings at the file level and whether they are documented by the developer. Then, it checks the validity of the developers description of the refactorings, if any. Based on that analysis, the documentation bot will recommend a message to document the refactorings, their locations and the quality improvement for that pull-request when missing information is found. Then, the developer can modify his pull request description by interacting with the bot to accept/modify/reject part of the proposed documentation. Since refactoring do not happen in isolation most of the time, the bot is documenting the impact of a sequence of refactorings, in a pull-request, on quality and not each refactoring in isolation. We conducted a human survey with 14 active developers to manually evaluate the relevance and the correctness of our tool on different pull requests of 5 open source projects and one industrial system. The results show that the participants found that our bot facilitates the documentation of their quality-related changes and refactorings.","2019-09","2020-08-07 09:21:10","2020-08-20 11:04:40","2020-08-07 09:21:10","152-162","","","","","","","","","","","IEEE","Cleveland, OH, USA","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\ZT6FE8NV\rebai2019.pdf","","software development; included; devbot; MSR; documentation; GithubApps; refactoring; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2019 IEEE 19th International Working Conference on Source Code Analysis and Manipulation (SCAM)","","","","","","","","","","","","","","",""
"J63B58KH","conferencePaper","2019","Wyrich, Marvin; Bogner, Justus","Towards an Autonomous Bot for Automatic Source Code Refactoring","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","978-1-72812-262-5","","10.1109/BotSE.2019.00015","https://ieeexplore.ieee.org/document/8823629/","Continuous refactoring is necessary to maintain source code quality and to cope with technical debt. Since manual refactoring is inefficient and error-prone, various solutions for automated refactoring have been proposed in the past. However, empirical studies have shown that these solutions are not widely accepted by software developers and most refactorings are still performed manually. For example, developers reported that refactoring tools should support functionality for reviewing changes. They also criticized that introducing such tools would require substantial effort for configuration and integration into the current development environment.","2019-05","2020-06-23 09:58:31","2020-10-31 00:10:39","2020-06-23 09:58:31","24-28","","","","","","","","","","","IEEE","Montreal, QC, Canada","en","","","","","DOI.org (Crossref)","","tex.ids: wyrich2019a, wyrichAutonomousBotAutomatic2019","","C:\Users\sant_si\Zotero\storage\8KURFXFU\Wyrich and Bogner - 2019 - Towards an Autonomous Bot for Automatic Source Cod.pdf; C:\Users\sant_si\Zotero\storage\UDIRXZ9Z\Wyrich and Bogner - 2019 - Towards an Autonomous Bot for Automatic Source Cod.pdf","","software engineering; included; bots; devbot; MSR; GithubApps; refactoring; github; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","","","","","","","","","","","","","","",""
"KWQSJ3DW","journalArticle","2020","Wessel, Mairieli; Steinmacher, Igor","The Inconvenient Side of Software Bots on Pull Requests","","","","","","Software bots are applications that integrate their work with humans’ tasks, serving as conduits between users and other tools. Due to their ability to automate tasks, bots have been widely adopted by Open Source Software (OSS) projects hosted on GitHub. Commonly, OSS projects use bots to automate a variety of routine tasks to save time from maintainers and contributors. Although bots can be useful for supporting maintainers’ work, sometimes their comments are seen as spams, and are quickly ignored by contributors. In fact, the way that these bots interact on pull requests can be disruptive and perceived as unwelcoming. In this paper, we propose the concept of a meta-bot to deal with current problems on the human-bot interaction on pull requests. Besides providing additional value to this interaction, meta-bot will reduce interruptions and help maintainers and contributors stay aware of important information.","2020","2020-06-23 09:58:27","2020-08-18 18:39:30","","6","","","","","","","","","","","","","en","","","","","Zotero","","tex.ids: wessel2020a, wesselInconvenientSideSoftware2020","","C:\Users\sant_si\Zotero\storage\C2DE6T8F\Wessel and Steinmacher - 2020 - The Inconvenient Side of Software Bots on Pull Req.pdf; C:\Users\sant_si\Zotero\storage\HGGMU4BZ\Wessel and Steinmacher - 2020 - The Inconvenient Side of Software Bots on Pull Req.pdf","","included; bots; devbot; MSR; GithubApps; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"4LKPY9GP","conferencePaper","2019","Wessel, Mairieli; Steinmacher, Igor; Wiese, Igor; Gerosa, Marco A.","Should I Stale or Should I Close? An Analysis of a Bot That Closes Abandoned Issues and Pull Requests","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","978-1-72812-262-5","","10.1109/BotSE.2019.00018","https://ieeexplore.ieee.org/document/8823598/","On GitHub, projects use bots to automate predefined and repetitive tasks related to issues and pull requests. Our research investigates the adoption of the stale bot, which helps maintainers triaging abandoned issues and pull requests. We analyzed the bots’ configuration settings and their modifications over time. These settings define the time for tagging issues and pull request as stale and closing them. We collected data from 765 OSS projects hosted on GitHub. Our results indicate that most of the studied projects made no more than three modifications in the configurations file, issues tagged as bug reports are exempt from being considered stale, while the same occurs with pull requests that need some input to be processed.","2019-05","2020-06-23 09:58:22","2020-08-18 14:24:40","2020-06-23 09:58:22","38-42","","","","","","Should I Stale or Should I Close?","","","","","IEEE","Montreal, QC, Canada","en","","","","","DOI.org (Crossref)","","tex.ids: wessel2019a, wesselShouldStaleShould2019","","C:\Users\sant_si\Zotero\storage\P24BPLAF\Wessel et al. - 2019 - Should I Stale or Should I Close An Analysis of a.pdf","","software engineering; included; devbot; MSR; GithubApps; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","","","","","","","","","","","","","","",""
"95EACIQJ","conferencePaper","2017","PerezSoler, Sara; Guerra, Esther; de Lara, Juan; Jurado, Francisco","The rise of the (modelling) bots: Towards assisted modelling via social networks","2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE)","978-1-5386-2684-9","","10.1109/ASE.2017.8115683","http://ieeexplore.ieee.org/document/8115683/","We are witnessing a rising role of mobile computing and social networks to perform all sorts of tasks. This way, social networks like Twitter or Telegram are used for leisure, and they frequently serve as a discussion media for work-related activities. In this paper, we propose taking advantage of social networks to enable the collaborative creation of models by groups of users. The process is assisted by modelling bots that orchestrate the collaboration and interpret the users’ inputs (in natural language) to incrementally build a (meta-)model. The advantages of this modelling approach include ubiquity of use, automation, assistance, natural user interaction, traceability of design decisions, possibility to incorporate coordination protocols, and seamless integration with the user’s normal daily usage of social networks. We present a prototype implementation called SOCIO, able to work over several social networks like Twitter and Telegram, and a preliminary evaluation showing promising results.","2017-10","2020-08-07 09:21:38","2021-05-28 19:58:47","2020-08-07 09:21:38","723-728","","","","","","The rise of the (modelling) bots","","","","","IEEE","Urbana, IL","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\QDEL5II7\Perez-Soler et al. - 2017 - The rise of the (modelling) bots Towards assisted.pdf","","duplicate; included; bots; devbot; collaboration; communication; stanford nlp parser; wordnet; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE)","","","","","","","","","","","","","","",""
"BANXPY5N","journalArticle","2018","PerezSoler, Sara; Guerra, Esther; de Lara, Juan","Collaborative Modeling and Group Decision Making Using Chatbots in Social Networks","IEEE Software","","0740-7459, 1937-4194","10.1109/MS.2018.290101511","https://ieeexplore.ieee.org/document/8409918/","","2018-11","2020-08-07 09:21:43","2021-05-28 19:59:04","2020-08-07 09:21:43","48-54","","6","35","","IEEE Softw.","","","","","","","","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\36ZF8ASZ\Perez-Soler et al. - 2018 - Collaborative Modeling and Group Decision Making U.pdf","","duplicate; included; bots; devbot; collaboration; communication; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"JTFCV38M","journalArticle","2020","Wyrich, Marvin; Hebig, Regina; Wagner, Stefan; Scandariato, Riccardo","Perception and Acceptance of an Autonomous Refactoring Bot","Proceedings of the 12th International Conference on Agents and Artificial Intelligence","","","10.5220/0009168803030310","http://arxiv.org/abs/2001.02553","The use of autonomous bots for automatic support in software development tasks is increasing. In the past, however, they were not always perceived positively and sometimes experienced a negative bias compared to their human counterparts. We conducted a qualitative study in which we deployed an autonomous refactoring bot for 41 days in a student software development project. In between and at the end, we conducted semi-structured interviews to find out how developers perceive the bot and whether they are more or less critical when reviewing the contributions of a bot compared to human contributions. Our findings show that the bot was perceived as a useful and unobtrusive contributor, and developers were no more critical of it than they were about their human colleagues, but only a few team members felt responsible for the bot.","2020","2020-06-23 09:58:39","2020-10-30 15:21:31","2020-06-23 09:58:39","303-310","","","","","","","","","","","","","en","","","","","arXiv.org","","tex.ids: wyrich2020a, wyrichPerceptionAcceptanceAutonomous2020 arXiv: 2001.02553","","C:\Users\sant_si\Zotero\storage\F7YALV6I\Wyrich et al. - 2020 - Perception and Acceptance of an Autonomous Refacto.pdf","","software engineering; included; study; bots; devbot; refactoring; ref; extension; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"WLBWG8MP","journalArticle","2018","Wessel, Mairieli; de Souza, Bruno Mendes; Steinmacher, Igor; Wiese, Igor S.; Polato, Ivanilton; Chaves, Ana Paula; Gerosa, Marco A.","The Power of Bots: Characterizing and Understanding Bots in OSS Projects","Proceedings of the ACM on Human-Computer Interaction","","2573-0142, 2573-0142","10.1145/3274451","https://dl.acm.org/doi/10.1145/3274451","","2018-11","2020-06-23 09:58:18","2020-12-02 06:25:56","2020-06-23 09:58:18","1-19","","CSCW","2","","Proc. ACM Hum.-Comput. Interact.","The Power of Bots","","","","","","","en","","","","","DOI.org (Crossref)","","tex.ids: wessel2018a, wesselPowerBotsCharacterizing2018","","C:\Users\sant_si\Zotero\storage\M8NZ5MRB\Wessel et al. - 2018 - The Power of Bots Characterizing and Understandin.pdf","","software engineering; included; study; bots; devbot; MSR; github; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"2XPEY3LR","conferencePaper","2019","Lebeuf, Carlene; Zagalsky, Alexey; Foucault, Matthieu; Storey, Margaret-Anne","Defining and Classifying Software Bots: A Faceted Taxonomy","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","978-1-72812-262-5","","10.1109/BotSE.2019.00008","https://ieeexplore.ieee.org/document/8823642/","While bots have been around for many decades, recent technological advancements and the increasing adoption of language-based communication platforms have led to a surge of new software bots, which have become increasingly pervasive in our everyday lives. Although many novel bots are being designed and deployed, the terms used to describe them and their properties are vast, diverse, and often inconsistent. Even the concept of what is or is not a bot is unclear. This hinders our ability to study, understand, design, and classify bots.","2019-05","2020-05-18 15:24:53","2021-05-18 16:09:49","2020-05-18 15:24:53","1-6","","","","","","Defining and Classifying Software Bots","","","","","IEEE","Montreal, QC, Canada","en","","","","","DOI.org (Crossref)","","tex.ids: lebeuf2019a, lebeufDefiningClassifyingSoftware2019a, lebeufDefiningClassifyingSoftware2019b","","C:\Users\sant_si\Zotero\storage\SBSDT6UQ\Lebeuf et al. - 2019 - Defining and Classifying Software Bots A Faceted .pdf","","software engineering; included; bots; terminology; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","","","","","","","","","","","","","","",""
"QSE8F36W","conferencePaper","2016","Storey, Margaret-Anne; Zagalsky, Alexey","Disrupting developer productivity one bot at a time","Proceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering","","","","","","2016","2020-03-27 10:49:54","2021-05-18 16:08:37","","928-931","","","","","","","","","","","","","","","","","","","","tex.ids: storey2016, storeyDisruptingDeveloperProductivitya type: Conference Proceedings","","C:\Users\sant_si\Zotero\storage\S6BD4JKF\Storey and Zagalsky - 2016 - Disrupting developer productivity one bot at a tim.pdf","","software engineering; productivity; included; study; bots; Useful; ref; classification; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"MNRLUQLX","journalArticle","2019","PerezSoler, Sara; Guerra, Esther; de Lara, Juan","Assisted modelling over social networks with","","","","","","Social networks are intensively used nowadays for both leisure and work. They have become a natural communication mechanism which helps users in coordinating and collaborating in their daily life activities.","2019","2020-08-07 09:21:40","2021-05-28 19:58:57","","5","","","","","","","","","","","","","en","","","","","Zotero","","","","C:\Users\sant_si\Zotero\storage\ANEQZVGV\Perez-Soler et al. - Assisted modelling over social networks with.pdf","","duplicate; included; bots; devbot; collaboration; communication; telegram; twitter; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"LSGW94W4","journalArticle","2019","Matera, Maristella; Thesis, M; Castaldo, Nicola","A Conceptual Modeling Approach for the Rapid Development of Chatbots for Conversational Data Exploration","","","","","","","2019","2020-06-23 10:05:47","2020-12-02 04:56:17","","130","","","","","","","","","","","","","en","","","","","Zotero","","tex.ids: materaConceptualModelingApproach","","C:\Users\sant_si\Zotero\storage\MUTHU7UE\Matera et al. - A Conceptual Modeling Approach for the Rapid Devel.pdf","","chatbot; software engineering; included; thesis; bots; telegram; rasa; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"4M9F5TUU","journalArticle","2019","Alizadeh, Vahid; Ouali, Mohamed Amine; Kessentini, Marouane; Chater, Meriem","Interactive Software Refactoring Bot","","","","","","The adoption of refactoring techniques for continuous integration received much less attention from the research community comparing to root-canal refactoring to fix the quality issues in the whole system. Several recent empirical studies show that developers, in practice, are applying refactoring incrementally when they are fixing bugs or adding new features. There is an urgent need for refactoring tools that can support continuous integration and some recent development processes such as DevOps that are based on rapid releases. Furthermore, several studies show that manual refactoring is expensive and existing automated refactoring tools are challenging to configure and integrate into the development pipelines with significant disruption cost.","2019","2020-06-23 09:59:08","2020-09-25 14:49:09","","12","","","","","","","","","","","","","en","","","","","Zotero","","tex.ids: alizadehInteractiveSoftwareRefactoring","","C:\Users\sant_si\Zotero\storage\NILSEL7P\Alizadeh et al. - Interactive Software Refactoring Bot.pdf","","duplicate; software engineering; included; devbot; MSR; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"VLPAZT55","journalArticle","2019","Brown, Dwayne Christian","Digital Nudges for Encouraging Developer Behaviors","","","","","","Software engineering researchers create tools and practices designed to help developers accomplish programming tasks. Unfortunately, software engineers often ignore these useful resources in practice. While automated recommender systems have been created to automatically increase awareness and encourage adoption of developer actions, research shows that face-to-face recommendations between colleagues is still the most effective mode of discovery for software engineers. To improve the effectiveness of automated tool recommendations, I propose integrating concepts from nudge theory, a behavioral science framework that examines how to influence human behavior and improve decisionmaking. This work seeks to apply this theory into software engineering to explore the impact of nudges for improving developer behavior and introducing developer recommendation choice architectures to design and frame decisions in the context of adopting programming tools and practices. The contributions of this work are: 1) a conceptual framework explaining how to apply concepts from nudge theory when making recommendations to software developers, 2) a set of experiments that support and evaluate the conceptual framework, and 3) an automated recommender system, nudge-bot, that utilizes the proposed framework to recommend useful developer behaviors. My goal is to demonstrate that automated nudges can encourage software engineers to adopt beneficial developer behaviors.","2019","2020-06-23 09:59:17","2020-11-17 13:42:09","","50","","","","","","","","","","","","","en","","","","","Zotero","","tex.ids: brownDigitalNudgesEncouraging","","C:\Users\sant_si\Zotero\storage\P4I5LYII\Brown - Digital Nudges for Encouraging Developer Behaviors.pdf","","duplicate; framework; software engineering; included; thesis; bots; devbot; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"58I3W3H4","journalArticle","2020","Storey, Margaret-Anne; Serebrenik, Alexander; Rosé, Carolyn Penstein; Zimmermann, Thomas; Herbsleb, James D","BOTse: Bots in Software Engineering","","","","","","This report documents the program and the outcomes of the Dagstuhl Seminar 19471 “BOTse: Bots in Software Engineering”. This Dagstuhl seminar brought researchers and practitioners together from multiple research communities with disparate views of what bots are and what they can do for software engineering. The goals were to understand how bots are used today, how they could be used in innovative ways in the future, how the use of bots can be compared and synthesized, and to identify and share risks and challenges that may emerge from using bots in practice. The report briefly summarizes the goals and format of the seminar and provides selected insights and results collected during the seminar.","2020","2020-06-23 09:58:05","2021-01-07 02:52:48","","13","","","","","","","","","","","","","en","","","","","Zotero","","tex.ids: storeyBOTseBotsSoftware","","C:\Users\sant_si\Zotero\storage\PPK45WLI\Storey et al. - BOTse Bots in Software Engineering.pdf","","software engineering; included; bots; terminology; ref; classification; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"338GSSPA","journalArticle","2020","Alizadeh, Vahid","A User-aware Intelligent Refactoring for Discrete and Continuous Software Integration","","","","","","","2020","2020-06-23 09:59:14","2020-11-30 17:55:25","","251","","","","","","","","","","","","","en","","","","","Zotero","","tex.ids: alizadehUserawareIntelligentRefactoring","","C:\Users\sant_si\Zotero\storage\4H5KED3Q\Alizadeh - A User-aware Intelligent Refactoring for Discrete .pdf","","software engineering; included; thesis; GithubApps; refactoring; phd; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"DGZV27SB","journalArticle","2020","Beck, Samuel; Merz, Lasse; Zorn, Christoph; Beck, Fabian; Merino, Leonel; Okanović, Dušan; van Hoorn, André","“PerformoBot, please help me!” – Chatbot-supported Performance Evaluation","","","","","","","2020","2020-06-23 09:59:15","2021-04-14 10:42:51","","2","","","","","","","","","","","","","en","","","","","Zotero","","tex.ids: beckPerformoBotPleaseHelp","","C:\Users\sant_si\Zotero\storage\95UFFVU2\Beck et al. - “PerformoBot, please help me!” – Chatbot-supported.pdf","","software engineering; included; extended abstract; performobot; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"H44MAZ27","journalArticle","2018","Pena, Carles Miralles; Cabot, Jordi; Gomez, Sergi","AI on software engineering processes","","","","","","","2018","2020-06-23 09:45:53","2020-11-28 07:43:06","","65","","","","","","","","","","","","","en","","","","","Zotero","","tex.ids: penaAISoftwareEngineering","","C:\Users\sant_si\Zotero\storage\QB5ZPFKX\Pena et al. - AI on software engineering processes.pdf; C:\Users\sant_si\Zotero\storage\DTCEESTC\Pena et al. - AI on software engineering processes.pdf","","chatbot; software engineering; included; thesis; virtual assistants; rasa; Botkit; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"GRI2F9S3","journalArticle","2020","Erlenhov, Linda; Neto, Francisco Gomes de Oliveira; Leitner, Philipp","An Empirical Study of Bots in Software Development – Characteristics and Challenges from a Practitioner's Perspective","arXiv:2005.13969 [cs]","","","","http://arxiv.org/abs/2005.13969","Software engineering bots – automated tools that handle tedious tasks – are increasingly used by industrial and open source projects to improve developer productivity. Current research in this area is held back by a lack of consensus of what software engineering bots (DevBots) actually are, what characteristics distinguish them from other tools, and what benefits and challenges are associated with DevBot usage. In this paper we report on a mixed-method empirical study of DevBot usage in industrial practice. We report on findings from interviewing 21 and surveying a total of 111 developers. We identify three different personas among DevBot users (focusing on autonomy, chat interfaces, and “smartness”), each with different definitions of what a DevBot is, why developers use them, and what they struggle with. We conclude that future DevBot research should situate their work within our framework, to clearly identify what type of bot the work targets, and what advantages practitioners can expect. Further, we find that there currently is a lack of generalpurpose “smart” bots that go beyond simple automation tools or chat interfaces. This is problematic, as we have seen that such bots, if available, can have a transformative effect on the projects that use them.","2020-05","2020-06-23 10:14:53","2020-09-22 16:47:52","2020-06-23","","","","","","","","","","","","","","English","","","","","","","","","C:\Users\sant_si\Zotero\storage\2XWEAUAS\Erlenhov et al. - 2020 - An Empirical Study of Bots in Software Development.pdf","","chatbot; software engineering; included; Useful; devbot; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"2V7DI5XN","journalArticle","2019","PérezSoler, Sara; GonzálezJiménez, Mario; Guerra, Esther; de Lara, Juan","Towards Conversational Syntax for Domain-Specific Languages using Chatbots","The Journal of Object Technology","","1660-1769","10.5381/jot.2019.18.2.a5","","","2019","2020-03-27 10:49:53","2021-05-28 19:59:15","","","","2","18","","","","","","","","","","","","","","","","","tex.ids: perez-soler2019, perez-solerConversationalSyntaxDomainSpecific2019a number: 2 type: Journal Article","","C:\Users\sant_si\Zotero\storage\CM99CI92\Pérez-Soler et al. - 2019 - Towards Conversational Syntax for Domain-Specific .pdf","","chatbot; duplicate; software development; included; conversational agents; devbot; collaboration; communication; telegram; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"W8UDX4NS","conferencePaper","2018","Toxtli, Carlos; MonroyHernández, Andrés; Cranshaw, Justin","Understanding Chatbot-mediated Task Management","Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems  - CHI '18","978-1-4503-5620-6","","10.1145/3173574.3173632","http://dl.acm.org/citation.cfm?doid=3173574.3173632","Effective task management is essential to successful team collaboration. While the past decade has seen considerable innovation in systems that track and manage group tasks, these innovations have typically been outside of the principal communication channels: email, instant messenger, and group chat. Teams formulate, discuss, refine, assign, and track the progress of their collaborative tasks over electronic communication channels, yet they must leave these channels to update their task-tracking tools, creating a source of friction and inefficiency. To address this problem, we explore how bots might be used to mediate task management for individuals and teams. We deploy a prototype bot to eight different teams of information workers to help them create, assign, and keep track of tasks, all within their main communication channel. We derived seven insights for the design of future bots for coordinating work.","2018","2020-08-07 09:21:58","2021-05-28 19:57:11","2020-08-07 09:21:58","1-6","","","","","","","","","","","ACM Press","Montreal QC, Canada","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\Q7BVDTYD\Toxtli et al. - 2018 - Understanding Chatbot-mediated Task Management.pdf","","chatbot; software development; productivity; included; Useful; collaboration; communication; microsoft LUIS; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","the 2018 CHI Conference","","","","","","","","","","","","","","",""
"CXU6SYRP","journalArticle","2018","Urli, Simon","How to Design a Program Repair Bot? Insights from the Repairnator Project","","","","","","Program repair research has made tremendous progress over the last few years, and software development bots are now being invented to help developers gain productivity. In this paper, we investigate the concept of a “program repair bot” and present Repairnator. The Repairnator bot is an autonomous agent that constantly monitors test failures, reproduces bugs, and runs program repair tools against each reproduced bug. If a patch is found, Repairnator bot reports it to the developers. At the time of writing, Repairnator uses three different program repair systems and has been operating since February 2017. In total, it has studied 11 523 test failures over 1 609 open-source software projects hosted on GitHub, and has generated patches for 15 different bugs. Over months, we hit a number of hard technical challenges and had to make various design and engineering decisions. This gives us a unique experience in this area. In this paper, we reflect upon Repairnator in order to share this knowledge with the automatic program repair community.","2018","2020-08-07 09:22:02","2021-05-18 16:09:38","","10","","","","","","","","","","","","","en","","","","","Zotero","","","","C:\Users\sant_si\Zotero\storage\AL6JRDVT\Urli - 2018 - How to Design a Program Repair Bot Insights from .pdf","","duplicate; software engineering; included; bots; testbots; devbot; repairbot; ref; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"7NBAY4IF","conferencePaper","2018","Peng, Zhenhui; Yoo, Jeehoon; Xia, Meng; Kim, Sunghun; Ma, Xiaojuan","Exploring How Software Developers Work with Mention Bot in GitHub","Proceedings of the Sixth International Symposium of Chinese CHI on   - ChineseCHI '18","978-1-4503-6508-6","","10.1145/3202667.3202694","http://dl.acm.org/citation.cfm?doid=3202667.3202694","Recently, major software development platforms have started to provide automatic reviewer recommendation (ARR) services for pull requests, to improve the collaborative coding review process. However, the user experience of ARR is under-investigated. In this paper, we use a two-stage mixed-methods approach to study how software developers perceive and work with the Facebook mention bot, one of the most popular ARR bots in GitHub. Specifically, in Stage I, we conduct archival analysis on projects employing mention bot and a user survey to investigate the bot’s performance. A year later, in Stage II, we revisit these projects and conduct additional surveys and interviews with three user groups: project owners, contributors and reviewers. Results show that developers appreciate mention bot saving their effort, but are bothered by its unstable setting and unbalanced workload allocation. We conclude with design considerations for improving ARR services.","2018","2020-08-07 09:21:01","2020-11-02 19:32:16","2020-08-07 09:21:01","152-155","","","","","","","","","","","ACM Press","Montreal, QC, Canada","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\RDVK9XMB\Peng et al. - 2018 - Exploring How Software Developers Work with Mentio.pdf","","software engineering; included; bots; devbot; MSR; github; ref; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","the Sixth International Symposium of Chinese CHI","","","","","","","","","","","","","","",""
"L9SIXB7N","journalArticle","2020","Romero, Ricardo; Parra, Esteban; Haiduc, Sonia","Experiences Building an Answer Bot for Gitter","","","","","","","2020","2020-08-07 09:21:25","2020-10-16 15:38:58","","6","","","","","","","","","","","","","en","","","","","Zotero","","","","C:\Users\sant_si\Zotero\storage\N9DTD76H\Romero et al. - 2020 - Experiences Building an Answer Bot for Gitter.pdf","","chatbot; included; QnA; stackoverflow; communication; Gitter; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"V8SGJFGM","conferencePaper","2019","Brown, Chris","Digital Nudges for Encouraging Developer Actions","2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","978-1-72811-764-5","","10.1109/ICSE-Companion.2019.00082","https://ieeexplore.ieee.org/document/8802635/","Researchers have examined a wide variety of practices to help software engineers complete different programming tasks. Despite the fact that studies show software engineering practices and tools created to improve the software development process are useful for preventing bugs, decreasing debugging costs, reducing debugging time, and providing additional benefits, software engineers rarely use them in practice. To persuade humans to alter and adopt new behaviors, psychologists have studied the concept of nudges. My research aims to investigate how digital nudges, or the process of using technology to automatically create nudges, can be beneficial in helping software developers and teams adopt software engineering activities and integrate them into their normal workflow.","2019-05","2020-08-07 09:23:24","2020-11-17 09:52:40","2020-08-07 09:23:24","202-205","","","","","","","","","","","IEEE","Montreal, QC, Canada","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\FMY3XF3G\Brown - 2019 - Digital Nudges for Encouraging Developer Actions.pdf","","software engineering; included; devbot; nudge theory; github; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","","","","","","","","","","","","","","",""
"GNVPWBSM","journalArticle","2018","Wood, Andrew; Rodeghero, Paige; Armaly, Ameer; McMillan, Collin","Detecting Speech Act Types in Developer Question/Answer Conversations During Bug Repair","arXiv:1806.05130 [cs]","","","","http://arxiv.org/abs/1806.05130","This paper targets the problem of speech act detection in conversations about bug repair. We conduct a ""Wizard of Oz"" experiment with 30 professional programmers, in which the programmers fix bugs for two hours, and use a simulated virtual assistant for help. Then, we use an open coding manual annotation procedure to identify the speech act types in the conversations. Finally, we train and evaluate a supervised learning algorithm to automatically detect the speech act types in the conversations. In 30 two-hour conversations, we made 2459 annotations and uncovered 26 speech act types. Our automated detection achieved 69% precision and 50% recall. The key application of this work is to advance the state of the art for virtual assistants in software engineering. Virtual assistant technology is growing rapidly, though applications in software engineering are behind those in other areas, largely due to a lack of relevant data and experiments. This paper targets this problem in the area of developer Q/A conversations about bug repair.","2018-07-03","2020-08-07 09:22:27","2021-05-29 18:15:01","2020-08-07 09:22:27","","","","","","","","","","","","","","en","","","","","arXiv.org","","arXiv: 1806.05130","","C:\Users\sant_si\Zotero\storage\NXVEMJL4\Wood et al. - 2018 - Detecting Speech Act Types in Developer QuestionA.pdf","","software engineering; included; virtual assistants; Useful; devbot; ref; wizard of oz; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"AD5R3NCA","conferencePaper","2018","Bradley, Nick C.; Fritz, Thomas; Holmes, Reid","Context-aware conversational developer assistants","Proceedings of the 40th International Conference on Software Engineering","978-1-4503-5638-1","","10.1145/3180155.3180238","https://dl.acm.org/doi/10.1145/3180155.3180238","Building and maintaining modern software systems requires developers to perform a variety of tasks that span various tools and information sources. The crosscutting nature of these development tasks requires developers to maintain complex mental models and forces them (a) to manually split their high-level tasks into low-level commands that are supported by the various tools, and (b) to (re)establish their current context in each tool. In this paper we present Devy, a Conversational Developer Assistant (CDA) that enables developers to focus on their high-level development tasks. Devy reduces the number of manual, often complex, low-level commands that developers need to perform, freeing them to focus on their high-level tasks. Specifically, Devy infers high-level intent from developer’s voice commands and combines this with an automatically-generated context model to determine appropriate workflows for invoking lowlevel tool actions; where needed, Devy can also prompt the developer for additional information. Through a mixed methods evaluation with 21 industrial developers, we found that Devy provided an intuitive interface that was able to support many development tasks while helping developers stay focused within their development environment. While industrial developers were largely supportive of the automation Devy enabled, they also provided insights into several other tasks and workflows CDAs could support to enable them to better focus on the important parts of their development tasks.","2018-05-27","2020-08-07 09:23:19","2020-10-06 15:31:44","2020-08-07 09:23:19","993-1003","","","","","","","","","","","ACM","Gothenburg Sweden","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\NMD87G22\Bradley et al. - 2018 - Context-aware conversational developer assistants.pdf","","software engineering; conversational AI; included; ASR; virtual assistants; bots; Useful; devbot; Alexa; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","ICSE '18: 40th International Conference on Software Engineering","","","","","","","","","","","","","","",""
"7REHYPBS","journalArticle","2017","Carr, Scott A.; Logozzo, Francesco; Payer, Mathias","Automatic Contract Insertion with CCBot","IEEE Transactions on Software Engineering","","0098-5589, 1939-3520","10.1109/TSE.2016.2625248","http://ieeexplore.ieee.org/document/7736073/","Existing static analysis tools require significant programmer effort. On large code bases, static analysis tools produce thousands of warnings. It is unrealistic to expect users to review such a massive list and to manually make changes for each warning. To address this issue we propose CCBot (short for CodeContractsBot), a new tool that applies the results of static analysis to existing code through automatic code transformation. Specifically, CCBot instruments the code with method preconditions, postconditions, and object invariants which detect faults at runtime or statically using a static contract checker. The only configuration the programmer needs to perform is to give CCBot the file paths to code she wants instrumented. This allows the programmer to adopt contract-based static analysis with little effort. CCBot’s instrumented version of the code is guaranteed to compile if the original code did. This guarantee means the programmer can deploy or test the instrumented code immediately without additional manual effort. The inserted contracts can detect common errors such as null pointer dereferences and out-of-bounds array accesses. CCBot is a robust largescale tool with an open-source C# implementation. We have tested it on real world projects with tens of thousands of lines of code. We discuss several projects as case studies, highlighting undiscovered bugs found by CCBot, including 22 new contracts that were accepted by the project authors.","2017-08-01","2020-08-07 09:23:34","2020-10-02 16:41:48","2020-08-07 09:23:34","701-714","","8","43","","IIEEE Trans. Software Eng.","","","","","","","","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\9GU3H3ZP\Carr et al. - 2017 - Automatic Contract Insertion with CCBot.pdf","","software engineering; included; testbots; devbot; static code analysis; code contracts; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"Y54AD76E","conferencePaper","2017","Tian, Yuan; Thung, Ferdian; Sharma, Abhishek; Lo, David","APIBot: Question answering bot for API documentation","2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE)","978-1-5386-2684-9","","10.1109/ASE.2017.8115628","http://ieeexplore.ieee.org/document/8115628/","As the carrier of Application Programming Interfaces (APIs) knowledge, API documentation plays a crucial role in how developers learn and use an API. It is also a valuable information resource for answering API-related questions, especially when developers cannot find reliable answers to their questions online/offline. However, finding answers to API-related questions from API documentation might not be easy because one may have to manually go through multiple pages before reaching the relevant page, and then read and understand the information inside the relevant page to figure out the answers. To deal with this challenge, we develop APIBot, a bot that can answer API questions given API documentation as an input. APIBot is built on top of SiriusQA, the QA system from Sirius, a state of the art intelligent personal assistant. To make SiriusQA work well under software engineering scenario, we make several modifications over SiriusQA by injecting domain specific knowledge. We evaluate APIBot on 92 API questions, answers of which are known to be present in Java 8 documentation. Our experiment shows that APIBot can achieve a Hit@5 score of 0.706.","2017-10","2020-08-07 09:44:02","2020-10-01 21:59:20","2020-08-07 09:44:02","153-158","","","","","","APIBot","","","","","IEEE","Urbana, IL","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\QNL244NH\Tian et al. - 2017 - APIBot Question answering bot for API documentati.pdf","","included; virtual assistants; Useful; devbot; QnA; API; SiriusQA; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE)","","","","","","","","","","","","","","",""
"8BJR8GX9","conferencePaper","2016","Murgia, Alessandro; Janssens, Daan; Demeyer, Serge; Vasilescu, Bogdan","Among the Machines: Human-Bot Interaction on Social Q&A Websites","Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems  - CHI EA '16","978-1-4503-4082-3","","10.1145/2851581.2892311","http://dl.acm.org/citation.cfm?doid=2851581.2892311","With the rise of social media and advancements in AI technology, human-bot interaction will soon be commonplace. In this paper we explore human-bot interaction in STACK OVERFLOW, a question and answer website for developers. For this purpose, we built a bot emulating an ordinary user answering questions concerning the resolution of git error messages. In a first run this bot impersonated a human, while in a second run the same bot revealed its machine identity. Despite being functionally identical, the two bot variants elicited quite different reactions.","2016","2020-08-07 09:20:53","2020-10-01 10:07:03","2020-08-07 09:20:53","1272-1279","","","","","","Among the Machines","","","","","ACM Press","San Jose, California, USA","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\AV394YJJ\Murgia et al. - 2016 - Among the Machines Human-Bot Interaction on Socia.pdf","","included; HCI; devbot; QnA; stackoverflow; persona; trust; botse; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","the 2016 CHI Conference Extended Abstracts","","","","","","","","","","","","","","",""
"M249QC9D","conferencePaper","2017","Beschastnikh, Ivan; Lungu, Mircea F.; Zhuang, Yanyan","Accelerating Software Engineering Research Adoption with Analysis Bots","2017 IEEE/ACM 39th International Conference on Software Engineering: New Ideas and Emerging Technologies Results Track (ICSE-NIER)","978-1-5386-2675-7","","10.1109/ICSE-NIER.2017.17","http://ieeexplore.ieee.org/document/7966875/","An important part of software engineering (SE) research is to develop new analysis techniques and to integrate these techniques into software development practice. However, since access to developers is non-trivial and research tool adoption is slow, new analyses are typically evaluated as follows: a prototype tool that embeds the analysis is implemented, a set of projects is identified, their revisions are selected, and the tool is run in a controlled environment, rarely involving the developers of the software. As a result, research artifacts are brittle and it is unclear if an analysis tool would actually be adopted.","2017-05","2020-08-07 09:23:11","2020-09-30 17:23:37","2020-08-07 09:23:11","35-38","","","","","","","","","","","IEEE","Buenos Aires, Argentina","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\UH792PI2\Beschastnikh et al. - 2017 - Accelerating Software Engineering Research Adoptio.pdf","","software engineering; software development; included; bots; devbot; GithubApps; botse; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2017 IEEE/ACM 39th International Conference on Software Engineering: New Ideas and Emerging Technologies Results Track (ICSE-NIER)","","","","","","","","","","","","","","",""
"4BIN9WIR","conferencePaper","2020","Liu, Dongyu; Smith, Micah J.; Veeramachaneni, Kalyan","Understanding User-Bot Interactions for Small-Scale Automation in Open-Source Development","Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems","978-1-4503-6819-3","","10.1145/3334480.3382998","https://dl.acm.org/doi/10.1145/3334480.3382998","Small-scale automation tools, or “bots,” have been widely deployed in open-source software development to support manual project maintenance tasks. Though interactions between these bots and human developers can have significant effects on user experience, previous research has instead mostly focused on project outcomes. We reviewed existing small-scale bots in wide use on GitHub. After an indepth qualitative and quantitative evaluation, we compiled several important design principles for human-bot interaction in this context. Following the requirements, we further propose a workflow to support bot developers.","2020-04-25","2020-06-23 09:56:58","2020-10-15 16:21:29","2020-06-23 09:56:58","1-8","","","","","","","","","","","ACM","Honolulu HI USA","en","","","","","DOI.org (Crossref)","","tex.ids: liu2020a, liuUnderstandingUserBotInteractions2020","","C:\Users\sant_si\Zotero\storage\I7SYWXYF\Liu et al. - 2020 - Understanding User-Bot Interactions for Small-Scal.pdf; C:\Users\sant_si\Zotero\storage\GZURQFMV\Liu et al. - 2020 - Understanding User-Bot Interactions for Small-Scal.pdf","","software engineering; included; study; bots; HCI; behavioral science; MSR; github; so; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","CHI '20: CHI Conference on Human Factors in Computing Systems","","","","","","","","","","","","","","",""
"FPUNWX8S","conferencePaper","2019","van Tonder, Rijnard; Le Goues, Claire","Towards s/engineer/bot: Principles for Program Repair Bots","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","978-1-72812-262-5","","10.1109/BotSE.2019.00019","https://ieeexplore.ieee.org/document/8823644/","Of the hundreds of billions of dollars spent on developer wages, up to 25% accounts for fixing bugs. Companies like Google save significant human effort and engineering costs with automatic bug detection tools, yet automatically fixing them is still a nascent endeavour. Very recent work (including our own) demonstrates the feasibility of automatic program repair in practice. As automated repair technology matures, it presents great appeal for integration into developer workflows. We believe software bots are a promising vehicle for realizing this integration, as they bridge the gap between human software development and automated processes. We envision repair bots orchestrating automated refactoring and bug fixing. To this end, we explore what building a repair bot entails. We draw on our understanding of patch generation, validation, and real world software development interactions to identify six principles that bear on engineering repair bots and discuss related design challenges for integrating human workflows. Ultimately, this work aims to foster critical focus and interest for making repair bots a reality.","2019-05","2020-06-23 09:58:13","2021-05-29 08:09:20","2020-06-23 09:58:13","43-47","","","","","","Towards s/engineer/bot","","","","","IEEE","Montreal, QC, Canada","en","","","","","DOI.org (Crossref)","","tex.ids: vantonder2019a, vantonderEngineerBotPrinciples2019","","C:\Users\sant_si\Zotero\storage\7BQCY9E6\van Tonder and Le Goues - 2019 - Towards sengineerbot Principles for Program Rep.pdf; C:\Users\sant_si\Zotero\storage\CLJKVDR9\van Tonder and Le Goues - 2019 - Towards sengineerbot Principles for Program Rep.pdf","","software engineering; included; devbot; repairbot; MSR; ref; principles; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","","","","","","","","","","","","","","",""
"98UR883Y","conferencePaper","2019","Brown, Chris; Parnin, Chris","Sorry to Bother You: Designing Bots for Effective Recommendations","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","978-1-72812-262-5","","10.1109/BotSE.2019.00021","https://ieeexplore.ieee.org/document/8823645/","Bots have been proposed as a way to encourage developer actions and support software development activities. Many bots make recommendations to users, however humans may find these recommendations ineffective or problematic. In this paper, we argue that while bots can help automate many tasks, ultimately bots still need to find ways to interact with humans and handle all of the associated social and cognitive problems entailed. To illustrate this problem, we performed a small study where we generated 52 pull requests making tool recommendation to developers. As a result, we only convinced two developers to accept the pull request, while receiving several forms of feedback on why the pull request was ineffective. We summarize this feedback and suggest design principles for bot recommendations, including how psychology frameworks, such as nudge theory, can be used to improve human-bot interactions.","2019-05","2020-06-23 09:59:21","2020-09-24 09:09:05","2020-06-23 09:59:21","54-58","","","","","","Sorry to Bother You","","","","","IEEE","Montreal, QC, Canada","en","","","","","DOI.org (Crossref)","","tex.ids: brown2019b, brownSorryBotherYou2019","","C:\Users\sant_si\Zotero\storage\WVYGC7JH\Brown and Parnin - 2019 - Sorry to Bother You Designing Bots for Effective .pdf","","included; bots; devbot; MSR; nudge theory; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","","","","","","","","","","","","","","",""
"5RUZ9RX4","conferencePaper","2019","Alizadeh, Vahid; Ouali, Mohamed Amine; Kessentini, Marouane; Chater, Meriem","RefBot: Intelligent Software Refactoring Bot","2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE)","978-1-72812-508-4","","10.1109/ASE.2019.00081","https://ieeexplore.ieee.org/document/8952287/","The adoption of refactoring techniques for continuous integration received much less attention from the research community comparing to root-canal refactoring to fix the quality issues in the whole system. Several recent empirical studies show that developers, in practice, are applying refactoring incrementally when they are fixing bugs or adding new features. There is an urgent need for refactoring tools that can support continuous integration and some recent development processes such as DevOps that are based on rapid releases. Furthermore, several studies show that manual refactoring is expensive and existing automated refactoring tools are challenging to configure and integrate into the development pipelines with significant disruption cost.","2019-11","2020-06-23 09:59:12","2020-10-02 11:22:58","2020-06-23 09:59:12","823-834","","","","","","RefBot","","","","","IEEE","San Diego, CA, USA","en","","","","","DOI.org (Crossref)","","tex.ids: alizadeh2019a, alizadehRefBotIntelligentSoftware2019","","C:\Users\sant_si\Zotero\storage\GBDISQ5F\Alizadeh et al. - 2019 - RefBot Intelligent Software Refactoring Bot.pdf","","duplicate; software engineering; included; devbot; MSR; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE)","","","","","","","","","","","","","","",""
"96R6FH5L","journalArticle","2020","Abdellatif, Ahmad; Badran, Khaled; Shihab, Emad","MSRBot: Using bots to answer questions from software repositories","Empirical Software Engineering","","1382-3256, 1573-7616","10.1007/s10664-019-09788-5","http://link.springer.com/10.1007/s10664-019-09788-5","Software repositories contain a plethora of useful information that can be used to enhance software projects. Prior work has leveraged repository data to improve many aspects of the software development process, such as, help extract requirement decisions, identify potentially defective code and improve maintenance and evolution. However, in many cases, project stakeholders are not able to fully benefit from their software repositories due to the fact that they need special expertise to mine their repositories. Also, extracting and linking data from different types of repositories (e.g., source code control and bug repositories) requires dedicated effort and time, even if the stakeholder has the expertise to perform such a task. Therefore, in this paper, we use bots to automate and ease the process of extracting useful information from software repositories. Particularly, we lay out an approach of how bots, layered on top of software repositories, can be used to answer some of the most common software development/maintenance questions facing developers. We perform a preliminary study with 12 participants to validate the effectiveness of the bot. Our findings indicate that using bots achieves very promising results compared to not using the bot (baseline). Most of the participants (90.0%) find the bot to be either useful or very useful. Also, they completed 90.8% of the tasks correctly using the bot with a median time of 40 seconds per task. On the other hand, without the bot, the participants completed 25.2% of the tasks with a median time of 240 seconds per task. Our work has the potential to transform the MSR field by significantly lowering the barrier to entry, making the extraction of useful information from software repositories as easy as chatting with a bot.","2020-05","2020-06-17 07:48:58","2020-11-16 13:20:52","2020-06-17 07:48:58","1834-1863","","3","25","","Empir Software Eng","MSRBot","","","","","","","en","","","","","DOI.org (Crossref)","","tex.ids: abdellatif2020, abdellatif2020b, abdellatif2020c, abdellatifMSRBotUsingBots2020a, abdellatifMSRBotUsingBots2020b, abdellatifMSRBotUsingBots2020c number: 3","","C:\Users\sant_si\Zotero\storage\DNCZCCRK\Abdellatif et al. - 2020 - MSRBot Using bots to answer questions from softwa.pdf","","chatbot; framework; included; MSR; dialogflow; ref; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"VW35WQ9B","conferencePaper","2019","Monperrus, Martin","Explainable Software Bot Contributions: Case Study of Automated Bug Fixes","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","978-1-72812-262-5","","10.1109/BotSE.2019.00010","https://ieeexplore.ieee.org/document/8823632/","In a software project, esp. in open-source, a contribution is a valuable piece of work made to the project: writing code, reporting bugs, translating, improving documentation, creating graphics, etc. We are now at the beginning of an exciting era where software bots will make contributions that are of similar nature than those by humans.","2019-05","2020-06-23 09:57:20","2020-11-05 18:01:10","2020-06-23 09:57:20","12-15","","","","","","Explainable Software Bot Contributions","","","","","IEEE","Montreal, QC, Canada","en","","","","","DOI.org (Crossref)","","tex.ids: monperrus2019b, monperrusExplainableSoftwareBot2019","","C:\Users\sant_si\Zotero\storage\Q7PDA8QM\Monperrus - 2019 - Explainable Software Bot Contributions Case Study.pdf; C:\Users\sant_si\Zotero\storage\IMV2JKLE\Monperrus - 2019 - Explainable Software Bot Contributions Case Study.pdf","","duplicate; software engineering; included; bots; devbot; repairbot; ref; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","","","","","","","","","","","","","","",""
"AJ9IFD8G","conferencePaper","2019","Erlenhov, Linda; Gomes de Oliveira Neto, Francisco; Scandariato, Riccardo; Leitner, Philipp","Current and Future Bots in Software Development","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","978-1-72812-262-5","","10.1109/BotSE.2019.00009","https://ieeexplore.ieee.org/document/8823643/","Bots that support software development (“DevBots”) are seen as a promising approach to deal with the ever-increasing complexity of modern software engineering and development. Existing DevBots are already able to relieve developers from routine tasks such as building project images or keeping dependencies up-to-date. However, advances in machine learning and artificial intelligence hold the promise of future, significantly more advanced, DevBots. In this paper, we introduce the terminology of contemporary and ideal DevBots. Contemporary DevBots represent the current state of practice, which we characterise using a facet-based taxonomy. We exemplify this taxonomy using 11 existing, industrial-strength bots. We further provide a vision and definition of future (ideal) DevBots, which are not only autonomous, but also adaptive, as well as technically and socially competent. These properties may allow ideal DevBots to act more akin to artificial team mates than simple development tools.","2019-05","2020-06-23 10:00:06","2021-05-18 16:10:00","2020-06-23 10:00:06","7-11","","","","","","","","","","","IEEE","Montreal, QC, Canada","en","","","","","DOI.org (Crossref)","","tex.ids: erlenhov2019a, erlenhovCurrentFutureBots2019","","C:\Users\sant_si\Zotero\storage\ZHPXGYKZ\Erlenhov et al. - 2019 - Current and Future Bots in Software Development.pdf; C:\Users\sant_si\Zotero\storage\Y9C2HMG5\Erlenhov et al. - 2019 - Current and Future Bots in Software Development.pdf","","software development; included; bots; devbot; terminology; ref; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","","","","","","","","","","","","","","",""
"7JL7QXUD","journalArticle","2020","Abdellatif, Ahmad; Costa, Diego; Badran, Khaled; Abdalkareem, Rabe; Shihab, Emad","Challenges in Chatbot Development: A Study of Stack Overflow Posts","","","","","","Chatbots are becoming increasingly popular due to their benefits in saving costs, time, and effort. This is due to the fact that they allow users to communicate and control different services easily through natural language. Chatbot development requires special expertise (e.g., machine learning and conversation design) that differ from the development of traditional software systems. At the same time, the challenges that chatbot developers face remain mostly unknown since most of the existing studies focus on proposing chatbots to perform particular tasks rather than their development.","2020","2020-06-23 09:59:06","2020-10-06 15:12:13","","12","","","","","","","","","","","","","en","","","","","Zotero","","tex.ids: abdellatif2020b, abdellatif2020c, abdellatifChallengesChatbotDevelopment2020, abdellatifChallengesChatbotDevelopment2020a","","C:\Users\sant_si\Zotero\storage\3MFVBTJS\Abdellatif et al. - 2020 - Challenges in Chatbot Development A Study of Stac.pdf; C:\Users\sant_si\Zotero\storage\PHP2IEGK\Abdellatif et al. - 2020 - Challenges in Chatbot Development A Study of Stac.pdf","","chatbot; software engineering; included; study; stackoverflow; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"ZQVLPVDI","journalArticle","2020","Erlenhov, Linda; Neto, Francisco Gomes de Oliveira; Chukaleski, Martin; Daknache, Samer","Challenges and guidelines on designing test cases for test bots","arXiv:2004.10143 [cs]","","","10.1145/3387940.3391535","http://arxiv.org/abs/2004.10143","Test bots are automated testing tools that autonomously and periodically run a set of test cases that check whether the system under test meets the requirements set forth by the customer. The automation decreases the amount of time a development team spends on testing. As development projects become larger, it is important to focus on improving the test bots by designing more effective test cases because otherwise time and usage costs can increase greatly and misleading conclusions from test results might be drawn, such as false positives in the test execution. However, literature currently lacks insights on how test case design affects the effectiveness of test bots. This paper uses a case study approach to investigate those effects by identifying challenges in designing tests for test bots. Our results include guidelines for test design schema for such bots that support practitioners in overcoming the challenges mentioned by participants during our study.","2020-04-21","2020-06-23 10:00:17","2020-10-06 10:06:47","2020-06-23 10:00:17","","","","","","","","","","","","","","en","","","","","arXiv.org","","tex.ids: erlenhov2020b, erlenhovChallengesGuidelinesDesigning2020 arXiv: 2004.10143","","C:\Users\sant_si\Zotero\storage\NINUKQ5X\Erlenhov et al. - 2020 - Challenges and guidelines on designing test cases .pdf; C:\Users\sant_si\Zotero\storage\F96XLPPB\Erlenhov et al. - 2020 - Challenges and guidelines on designing test cases .pdf","","software engineering; included; bots; testbots; devbot; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"S6TT57DV","conferencePaper","2019","Kumar, Rahul; Bansal, Chetan; Maddila, Chandra; Sharma, Nitin; Martelock, Shawn; Bhargava, Ravi","Building Sankie: An AI Platform for DevOps","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","978-1-72812-262-5","","10.1109/BotSE.2019.00020","https://ieeexplore.ieee.org/document/8823620/","There has been a fundamental shift amongst software developers and engineers in the past few years. The software development life cycle (SDLC) for a developer has increased in complexity and scale. Changes that were developed and deployed over a matter of days or weeks are now deployed in a matter of hours. Due to greater availability of compute, storage, better tooling, and the necessity to react, developers are constantly looking to increase their velocity and throughput of developing and deploying changes. Consequently, there is a great need for more intelligent and context sensitive DevOps tools and services that help developers increase their efficiency while developing and debugging. Given the vast amounts of heterogeneous data available from the SDLC, such intelligent tools and services can now be built and deployed at a large scale to help developers achieve their goals and be more productive. In this paper, we present Sankie, a scalable and general service that has been developed to assist and impact all stages of the modern SDLC. Sankie provides all the necessary infrastructure (back-end and front-end bots) to ingest data from repositories and services, train models based on the data, and eventually perform decorations or provide information to engineers to help increase the velocity and throughput of changes, bug fixes etc. This paper discusses the architecture as well as some of the key observations we have made from wide scale deployment of Sankie within Microsoft.","2019-05","2020-06-23 09:56:47","2020-10-06 09:40:32","2020-06-23 09:56:47","48-53","","","","","","Building Sankie","","","","","IEEE","Montreal, QC, Canada","en","","","","","DOI.org (Crossref)","","tex.ids: kumar2019a, kumarBuildingSankieAI2019","","C:\Users\sant_si\Zotero\storage\XPRM6AVP\Kumar et al. - 2019 - Building Sankie An AI Platform for DevOps.pdf; C:\Users\sant_si\Zotero\storage\7NH3IETL\Kumar et al. - 2019 - Building Sankie An AI Platform for DevOps.pdf","","framework; software engineering; productivity; included; virtual assistants; devbot; MSR; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","","","","","","","","","","","","","","",""
"MFJSNTG7","conferencePaper","2019","Cerezo, Jhonny; Kubelka, Juraj; Robbes, Romain; Bergel, Alexandre","Building an Expert Recommender Chatbot","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","978-1-72812-262-5","","10.1109/BotSE.2019.00022","https://ieeexplore.ieee.org/document/8823626/","This paper presents our experience in implementing a chatbot for expert recommendation tasks. The chatbot was developed for the Pharo software ecosystem, and is integrated with the Discord chat service, which is used by the Pharo Community. We also report on a preliminary evaluation for which; the recommendation system was welcomed, though the conversational behavior was not; users expected a fully conversational chatbot, capable of following the conversation flow that the user handles. We discuss that such expectations might be hard to meet because of the uncanny valley effect.","2019-05","2020-06-23 09:59:46","2020-10-05 18:16:28","2020-06-23 09:59:46","59-63","","","","","","","","","","","IEEE","Montreal, QC, Canada","en","","","","","DOI.org (Crossref)","","tex.ids: cerezo2019a, cerezoBuildingExpertRecommender2019","","C:\Users\sant_si\Zotero\storage\Y7JZPFRF\Cerezo et al. - 2019 - Building an Expert Recommender Chatbot.pdf; C:\Users\sant_si\Zotero\storage\PHG42IWK\Cerezo et al. - 2019 - Building an Expert Recommender Chatbot.pdf","","chatbot; software engineering; included; communication; ref; discord; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","","","","","","","","","","","","","","",""
"RMEBN99R","journalArticle","2020","Golzadeh, Mehdi; Legay, Damien; Decan, Alexandre; Mens, Tom","Bot or not? Detecting bots in GitHub pull request activity based on comment similarity","","","","","","Many empirical studies focus on socio-technical activity in social coding platforms such as GitHub, for example to study the onboarding, abandonment, productivity and collaboration among team members. Such studies face the difficulty that GitHub activity can also be generated automatically by bots of a different nature. It therefore becomes imperative to distinguish such bots from human users. We propose an automated approach to detect bots in GitHub pull request (PR) activity. Relying on the assumption that bots contain repetitive message patterns in their PR comments, we analyse the similarity between multiple messages from the same GitHub identity, using a clustering method that combines the Jaccard and Levenshtein distance. We empirically evaluate our approach by analysing 20,090 PR comments of 250 users and 42 bots in 1,262 GitHub repositories. Our results show that the method is able to clearly separate bots from human users.","2020","2020-06-23 09:56:27","2020-10-05 16:15:06","","5","","","","","","","","","","","","","en","","","","","Zotero","","tex.ids: golzadeh2020a, golzadehBotNotDetecting2020","","C:\Users\sant_si\Zotero\storage\YDQ82EIU\golzadeh.pdf","","software engineering; included; bots; MSR; github; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"SBPIMM5B","journalArticle","2020","Dey, Tapajit; Vasilescu, Bogdan; Mockus, Audris","An Exploratory Study of Bot Commits","arXiv:2003.07961 [cs]","","","","http://arxiv.org/abs/2003.07961","Background: Bots help automate many of the tasks performed by software developers and are widely used to commit code in various social coding platforms. At present, it is not clear what types of activities these bots perform and understanding it may help design better bots, and find application areas which might benefit from bot adoption. Aim: We aim to categorize the Bot Commits by the type of change (files added, deleted, or modified), find the more commonly changed file types, and identify the groups of file types that tend to get updated together. Method: 12,326,137 commits made by 461 popular bots (that made at least 1000 commits) were examined to identify the frequency and the type of files added/ deleted/ modified by the commits, and association rule mining was used to identify the types of files modified together. Result: Majority of the bot commits modify an existing file, a few of them add new files, while deletion of a file is very rare. Commits involving more than one type of operation are even rarer. Files containing data, configuration, and documentation are most frequently updated, while HTML is the most common type in terms of the number of files added, deleted, and modified. Files of the type “Markdown”,“Ignore List”, “YAML”, “JSON” were the types that are updated together with other types of files most frequently. Conclusion: We observe that majority of bot commits involve single file modifications, and bots primarily work with data, configuration, and documentation files. A better understanding if this is a limitation of the bots and, if overcome, would lead to different kinds of bots remains an open question.","2020-03-27","2020-06-23 10:00:02","2021-01-05 14:52:54","2020-06-23 10:00:02","","","","","","","","","","","","","","en","","","","","arXiv.org","","tex.ids: dey2020b, deyExploratoryStudyBot2020 arXiv: 2003.07961","","C:\Users\sant_si\Zotero\storage\NY6GP9SN\Dey et al. - 2020 - An Exploratory Study of Bot Commits.pdf; C:\Users\sant_si\Zotero\storage\YAN65N2N\Dey et al. - 2020 - An Exploratory Study of Bot Commits.pdf","","software engineering; included; study; bots; MSR; github; ref; botse; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"FI3RHEH6","conferencePaper","2019","Seipel, Peter; Stock, Adrian; Santhanam, Sivasurya; Baranowski, Artur; Hochgeschwender, Nico; Schreiber, Andreas","Adopting Conversational Interfaces for Exploring OSGi-Based Software Architectures in Augmented Reality","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","978-1-72812-262-5","","10.1109/BotSE.2019.00013","https://ieeexplore.ieee.org/document/8823630/","We propose conversational interfaces as a convenient and complementary way for users to explore OSGi-based software architectures in immersive Augmented Reality (AR). By providing a conversational interface we aim to remedy some peculiarities of AR devices, but also enhancing the exploration task at hand. We exemplify a use case and sketch how different user utterances can be used to retrieve information about the to-be-explored OSGi-based software architecture. We identify crucial components such as natural language generation and intent recognition which are required to implement the user story and we outline the status of our implementation.","2019-05","2020-06-23 09:57:51","2020-10-06 09:40:47","2020-06-23 09:57:51","20-21","","","","","","","","","","","IEEE","Montreal, QC, Canada","en","","","","","DOI.org (Crossref)","","tex.ids: seipel2019a, seipelAdoptingConversationalInterfaces2019","","C:\Users\sant_si\Zotero\storage\4IYARYXT\Seipel et al. - 2019 - Adopting Conversational Interfaces for Exploring O.pdf; C:\Users\sant_si\Zotero\storage\VH85VYJD\Seipel et al. - 2019 - Adopting Conversational Interfaces for Exploring O.pdf","","chatbot; software engineering; conversational AI; included; ASR; rasa; botse; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","","","","","","","","","","","","","","",""
"5HWU3H56","conferencePaper","2019","Paikari, Elahe; Choi, JaeEun; Kim, SeonKyu; Baek, Sooyoung; Kim, MyeongSoo; Lee, SeungEon; Han, ChaeYeon; Kim, YoungJae; Ahn, KaHye; Cheong, Chan; van der hoek, Andre","A Chatbot for Conflict Detection and Resolution","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","978-1-72812-262-5","","10.1109/BotSE.2019.00016","https://ieeexplore.ieee.org/document/8823615/","","2019-05","2020-06-23 09:57:30","2021-04-14 10:47:51","2020-06-23 09:57:30","29-33","","","","","","","","","","","IEEE","Montreal, QC, Canada","","","","","","DOI.org (Crossref)","","tex.ids: paikari2019a, paikariChatbotConflictDetection2019","","C:\Users\sant_si\Zotero\storage\AB9NJ6K3\Paikari - 2019 - A Chatbot for Conflict Detection and resolution.pdf; C:\Users\sant_si\Zotero\storage\4DQCNT8T\Paikari et al. - 2019 - A Chatbot for Conflict Detection and Resolution.pdf","","chatbot; software engineering; included; slack; collaboration; communication; dialogflow; botse; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE)","","","","","","","","","","","","","","",""
"W5M4RSR3","journalArticle","2021","Bansal, Aakash; Eberhart, Zachary; Wu, Lingfei; McMillan, Collin","A Neural Question Answering System for Basic Questions about Subroutines","arXiv:2101.03999 [cs]","","","","http://arxiv.org/abs/2101.03999","A question answering (QA) system is a type of conversational AI that generates natural language answers to questions posed by human users. QA systems often form the backbone of interactive dialogue systems, and have been studied extensively for a wide variety of tasks ranging from restaurant recommendations to medical diagnostics. Dramatic progress has been made in recent years, especially from the use of encoderdecoder neural architectures trained with big data input. In this paper, we take initial steps to bringing state-of-the-art neural QA technologies to Software Engineering applications by designing a context-based QA system for basic questions about subroutines. We curate a training dataset of 10.9 million question/context/answer tuples based on rules we extract from recent empirical studies. Then, we train a custom neural QA model with this dataset and evaluate the model in a study with professional programmers. We demonstrate the strengths and weaknesses of the system, and lay the groundwork for its use in eventual dialogue systems for software engineering.","2021-01-11","2021-05-18 16:27:13","2021-05-18 16:27:13","2021-05-18 16:27:13","","","","","","","","","","","","","","en","","","","","arXiv.org","","arXiv: 2101.03999","","C:\Users\sant_si\Zotero\storage\ZZM23KV4\Bansal et al. - 2021 - A Neural Question Answering System for Basic Quest.pdf","","included; Snowballing; repo","Computer Science - Machine Learning; Computer Science - Software Engineering","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"A5ETQUF6","conferencePaper","2020","Nakagawa, Tasuku; Higo, Yoshiki; Kusumoto, Shinji","CLIONE: Clone Modification Support for Pull Request Based Development","2020 27th Asia-Pacific Software Engineering Conference (APSEC)","978-1-72819-553-7","","10.1109/APSEC51365.2020.00055","https://ieeexplore.ieee.org/document/9359312/","A code clone (clone) is known as one of the factors that makes software maintenance difficult. Thus, in software maintenance, clone modification is essential. An existing study proposed a tool that notifies developers of information about clone changes so that the developers can modify clones efficiently. However, the existing tool is premised on regular execution and not designed to be triggered by external factors except for time. Hence, the existing tool is difficult to be executed triggered by development workflow, such as modifying source code or merging branches , and we think this causes some issues. Consequently, in this study, we propose a new clone modification support technique aimed to integrate into pull request (PR) based development for solving those issues. The proposed technique detects code fragments that need modifications by tracking clones at the time of creating PRs. Moreover, we made three improvements for more accurate clone change tracking. Additionally, we implemented the proposed technique as a software tool, CLIONE. To evaluate CLIONE, we investigated the proportion of PRs in which clones have been modified non-simultaneously, and also we compared the results of clone change tracking with the existing tool. As a result, 11.9%∼30.4% of PRs included non-simultaneously modified clones, and we confirmed that CLIONE was able to track clone changes more accurately than the existing tool. CLIONE is available at https://github.com/T45K/CLIONE.","2020-12","2021-05-18 16:28:48","2021-05-18 16:28:48","2021-05-18 16:28:48","455-459","","","","","","CLIONE","","","","","IEEE","Singapore, Singapore","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\Y2J37PIU\Nakagawa et al. - 2020 - CLIONE Clone Modification Support for Pull Reques.pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2020 27th Asia-Pacific Software Engineering Conference (APSEC)","","","","","","","","","","","","","","",""
"JLSYBXUB","conferencePaper","2018","Paikari, Elahe; van der Hoek, André","A framework for understanding chatbots and their future","Proceedings of the 11th International Workshop on Cooperative and Human Aspects of Software Engineering","978-1-4503-5725-8","","10.1145/3195836.3195859","https://dl.acm.org/doi/10.1145/3195836.3195859","Chatbots have rapidly become a mainstay in software development. A range of chatbots contribute regularly to the creation of actual production software. It is somewhat difficult, however, to precisely delineate hype from reality. Questions arise as to what distinguishes a chatbot from an ordinary software tool, what might be desirable properties of chatbots, and where their future may lie. This position paper introduces a starting framework through which we examine the current state of chatbots and identify directions for future work.","2018-05-27","2021-05-18 16:28:49","2021-05-18 16:28:50","2021-05-18 16:28:49","13-16","","","","","","","","","","","ACM","Gothenburg Sweden","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\TKC6KG28\Paikari and van der Hoek - 2018 - A framework for understanding chatbots and their f.pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","ICSE '18: 40th International Conference on Software Engineering","","","","","","","","","","","","","","",""
"6MBA38AZ","conferencePaper","2018","Peng, Xin; Zhao, Yifan; Liu, Mingwei; Zhang, Fengyi; Liu, Yang; Wang, Xin; Xing, Zhenchang","Automatic Generation of API Documentations for Open-Source Projects","2018 IEEE Third International Workshop on Dynamic Software Documentation (DySDoc3)","978-1-5386-7570-0","","10.1109/DySDoc3.2018.00010","https://ieeexplore.ieee.org/document/8530111/","Open-source projects often have only incomplete and insufficient API documentations. To improve the efficiency of development and ensure the correctness of API usage, it is desired that the developers can be supported with automatically generated documentation based on a combination of knowledge from different sources. In this paper, we describe OpenAPIDocGen, a system that can automatically generate API Documentations for open-source projects, including an overview of the system and the data sources and techniques used to generate different parts of the documentation.","2018-09","2021-05-18 16:28:51","2021-05-18 16:28:51","2021-05-18 16:28:51","7-8","","","","","","","","","","","IEEE","Madrid","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\TMX72NY6\Peng et al. - 2018 - Automatic Generation of API Documentations for Ope.pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2018 IEEE Third International Workshop on Dynamic Software Documentation (DySDoc3)","","","","","","","","","","","","","","",""
"KJLEZT8G","conferencePaper","2019","Pinheiro, Andre M.; Rabello, Caio S.; Furtado, Leonardo B.; Pinto, Gustavo; de Souza, Cleidson R.B.","Expecting the Unexpected: Distilling Bot Development, Challenges, and Motivations","2019 IEEE/ACM 12th International Workshop on Cooperative and Human Aspects of Software Engineering (CHASE)","978-1-72812-239-7","","10.1109/CHASE.2019.00021","https://ieeexplore.ieee.org/document/8817003/","Software bots are becoming an increasingly popular tool in the software development landscape, which is particularly due to their potential of use in several different contexts. More importantly, software developers interested in transitioning to bot development may have to face challenges intrinsic related to bot software development. However, so far, it is still unclear what is the profile of bot developers, what motivate them, or what challenges do they face when dealing with bot development. To shed an initial light on this direction, we conducted a survey with 43 Github users who have been involved (showing their interest or actively contributing to) in bot software projects.","2019-05","2021-05-18 16:28:53","2021-05-18 16:28:53","2021-05-18 16:28:53","51-52","","","","","","Expecting the Unexpected","","","","","IEEE","Montreal, QC, Canada","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\C6JRAP2Y\Pinheiro et al. - 2019 - Expecting the Unexpected Distilling Bot Developme.pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2019 IEEE/ACM 12th International Workshop on Cooperative and Human Aspects of Software Engineering (CHASE)","","","","","","","","","","","","","","",""
"4YXHCEY3","journalArticle","2021","Qasse, Ilham; Mishra, Shailesh; Hamdaqa, Mohammad","iContractBot: A Chatbot for Smart Contracts' Specification and Code Generation","arXiv:2103.09314 [cs]","","","","http://arxiv.org/abs/2103.09314","Recently, Blockchain technology adoption has expanded to many application areas due to the evolution of smart contracts. However, developing smart contracts is non-trivial and challenging due to the lack of tools and expertise in this field. A promising solution to overcome this issue is to use ModelDriven Engineering (MDE), however, using models still involves a learning curve and might not be suitable for non-technical users. To tackle this challenge, chatbot or conversational interfaces can be used to assess the non-technical users to specify a smart contract in gradual and interactive manner.","2021-03-16","2021-05-18 16:28:56","2021-05-18 16:28:56","2021-05-18 16:28:56","","","","","","","iContractBot","","","","","","","en","","","","","arXiv.org","","arXiv: 2103.09314","","C:\Users\sant_si\Zotero\storage\4K7TIMBF\Qasse et al. - 2021 - iContractBot A Chatbot for Smart Contracts' Speci.pdf","","included; Snowballing; repo","Computer Science - Software Engineering","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"5Z3KTHHM","conferencePaper","2020","Ren, Ranci; Castro, John W.; Santos, Adrián; Pérez-Soler, Sara; Acuña, Silvia T.; de Lara, Juan","Collaborative Modelling: Chatbots or On-Line Tools? An Experimental Study","Proceedings of the Evaluation and Assessment in Software Engineering","978-1-4503-7731-7","","10.1145/3383219.3383246","https://dl.acm.org/doi/10.1145/3383219.3383246","Modelling is a fundamental activity in software engineering, which is often performed in collaboration. For this purpose, on-line tools running on the cloud are frequently used. However, recent advances in Natural Language Processing have fostered the emergence of chatbots, which are increasingly used for all sorts of software engineering tasks, including modelling. To evaluate to what extent chatbots are suitable for collaborative modelling, we conducted an experimental study with 54 participants, to evaluate the usability of a modelling chatbot called SOCIO, comparing it with the on-line tool Creately. We employed a within-subjects cross-over design of 2 sequences and 2 periods. Usability was determined by attributes of efficiency, effectiveness, satisfaction and quality of the results. We found that SOCIO saved time and reduced communication effort over Creately. SOCIO satisfied users to a greater extent than Creately, while in effectiveness results were similar. With respect to diagram quality, SOCIO outperformed Creately in terms of precision, while solutions with Creately had better recall and perceived success. However, in terms of accuracy and error scores, both tools were similar.","2020-04-15","2021-05-18 16:28:58","2021-05-18 16:28:58","2021-05-18 16:28:58","260-269","","","","","","Collaborative Modelling","","","","","ACM","Trondheim Norway","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\F5QXW77X\Ren et al. - 2020 - Collaborative Modelling Chatbots or On-Line Tools.pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","EASE '20: Evaluation and Assessment in Software Engineering","","","","","","","","","","","","","","",""
"PB9SW463","journalArticle","2021","Saadat, Samaneh; Colmenares, Natalia; Sukthankar, Gita","Do Bots Modify the Workflow of GitHub Teams?","arXiv:2103.09319 [cs]","","","","http://arxiv.org/abs/2103.09319","The ever-increasing complexity of modern software engineering projects makes the usage of automated assistants imperative. Bots can be used to complete repetitive tasks during development and testing, as well as promoting communication between team members through issue reporting and documentation. Although the ultimate aim of these automated assistants is to speed taskwork completion, their inclusion into GitHub repositories may affect teamwork as well. This paper studies the question of how bots modify the team workflow. We examined the event sequences of repositories with bots and without bots using a contrast motif discovery method to detect subsequences that are more prevalent in one set of event sequences vs. the other. Our study reveals that teams with bots are more likely to intersperse comments throughout their coding activities, while not actually being more prolific commenters.","2021-03-16","2021-05-18 16:29:01","2021-05-18 16:29:01","2021-05-18 16:29:01","","","","","","","","","","","","","","en","","","","","arXiv.org","","arXiv: 2103.09319","","C:\Users\sant_si\Zotero\storage\P2WIGBGI\Saadat et al. - 2021 - Do Bots Modify the Workflow of GitHub Teams.pdf","","included; Snowballing; repo","Computer Science - Software Engineering; Computer Science - Human-Computer Interaction","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"J6YKAY52","conferencePaper","2020","Saini, Rijul","Artificial intelligence empowered domain modelling bot","Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings","978-1-4503-8135-2","","10.1145/3417990.3419486","https://dl.acm.org/doi/10.1145/3417990.3419486","With the increasing adoption of Model-Based Software Engineering (MBSE) to handle the complexity of modern software systems in industry and inclusion of modelling topics in academic curricula, it is no longer a question of whether to use MBSE but how to use it. Acquiring modelling skills to properly build and use models with the help of modelling formalisms are non-trivial learning objectives, which novice modellers struggle to achieve for several reasons. For example, it is difficult for novice modellers to learn to use their abstraction abilities. Also, due to high student-teacher ratios in a typical classroom setting, novice modellers may not receive personalized and timely feedback on their modelling decisions. These issues hinder the novice modellers in improving their modelling skills. Furthermore, a lack of modelling skills among modellers inhibits the adoption and practice of modelling in industry. Therefore, an automated and intelligent solution is required to help modellers and other practitioners in improving their modelling skills. This doctoral research builds an automated and intelligent solution for one modelling formalism - domain models, in an avatar of a domain modelling bot. The bot automatically extracts domain models from problem descriptions written in natural language and generates intelligent recommendations, particularly for teaching modelling literacy to novice modellers. For this domain modelling bot, we leverage the capabilities of various Artificial Intelligence techniques such as Natural Language Processing and Machine Learning.","2020-10-16","2021-05-18 16:29:03","2021-05-18 16:29:03","2021-05-18 16:29:03","1-6","","","","","","","","","","","ACM","Virtual Event Canada","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\R4642HKH\Saini - 2020 - Artificial intelligence empowered domain modelling.pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","MODELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems","","","","","","","","","","","","","","",""
"7AU7W43R","conferencePaper","2020","Saini, Rijul; Mussbacher, Gunter; Guo, Jin L. C.; Kienzle, Jörg","DoMoBOT: a bot for automated and interactive domain modelling","Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings","978-1-4503-8135-2","","10.1145/3417990.3421385","https://dl.acm.org/doi/10.1145/3417990.3421385","Domain modelling transforms domain problem descriptions written in natural language (NL) into analyzable and concise domain models (class diagrams) during requirements analysis or the early stages of design in software development. Since the practice of domain modelling requires time in addition to modelling skills and experience, several approaches have been proposed to automate or semi-automate the construction of domain models from problem descriptions expressed in NL. Despite the existing work on domain model extraction, some significant challenges remain unaddressed: (i) the extracted domain models are not accurate enough to be used directly or with minor modifications in software development, (ii) existing approaches do not facilitate the tracing of the rationale behind the modelling decisions taken by the model extractor, and (iii) existing approaches do not provide interactive interfaces to update the extracted domain models. Therefore, in this paper, we introduce a domain modelling bot called DoMoBOT, explain its architecture, and implement it in the form of a web-based prototype tool. The bot automatically extracts a domain model from a problem description written in NL with an accuracy higher than existing approaches. Furthermore, the bot enables modellers to update a part of the extracted domain model and in response the bot re-configures the other parts of the domain model pro-actively. To improve the accuracy of extracted domain models, we combine the techniques of Natural Language Processing and Machine Learning. Finally, we evaluate the accuracy of the extracted domain models.","2020-10-16","2021-05-18 16:29:05","2021-05-18 16:29:05","2021-05-18 16:29:05","1-10","","","","","","DoMoBOT","","","","","ACM","Virtual Event Canada","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\FFBDKXZR\Saini et al. - 2020 - DoMoBOT a bot for automated and interactive domai.pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","MODELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems","","","","","","","","","","","","","","",""
"6SJRMN8C","conferencePaper","2019","Sharma, Vibhu Saujanya; Mehra, Rohit; Podder, Sanjay; Burden, Adam P.","A Journey Towards Providing Intelligence and Actionable Insights to Development Teams in Software Delivery","2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE)","978-1-72812-508-4","","10.1109/ASE.2019.00142","https://ieeexplore.ieee.org/document/8952441/","For delivering high-quality artifacts within the budget and on schedule, software delivery teams ideally should have a holistic and in-process view of the current health and future trajectory of the project. However, such insights need to be at the right level of granularity and need to be derived typically from a heterogeneous project environment, in a way that helps development team members with their tasks at hand. Due to client mandates, software delivery project environments employ many disparate tools and teams tend to be distributed, thus making the relevant information retrieval, insight generation, and developer intelligence augmentation process fairly complex. In this paper, we discuss our journey in this area spanning across facets like software project modelling and new development metrics, studying developer priorities, adoption of new metrics, and different approaches of developer intelligence augmentation. Finally, we present our exploration of new immersive technologies for human-centered software engineering.","2019-11","2021-05-18 16:29:07","2021-05-18 16:29:07","2021-05-18 16:29:07","1214-1215","","","","","","","","","","","IEEE","San Diego, CA, USA","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\8IJ2UAMN\Sharma et al. - 2019 - A Journey Towards Providing Intelligence and Actio.pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE)","","","","","","","","","","","","","","",""
"6Y8VBUUW","journalArticle","2021","Shihab, Emad; Wagner, Stefan; Aurélio Gerosa, Marco","Summary of the 2nd International Workshop on Bots in Software Engineering (BotSE 2020)","ACM SIGSOFT Software Engineering Notes","","0163-5948","10.1145/3437479.3437484","https://dl.acm.org/doi/10.1145/3437479.3437484","Bots automate many tasks in software engineering projects often in the form of chatbots. Bots have been proposed, for example, for testing, maintenance, or automating bug fixes. Following the success of the first BotSE workshop, we organized this second edition collocated with ICSE 2020 to bring together the research community that investigates bots for software engineering. Specifically, the workshop's goal was to share experiences and challenges, discuss new types of bots, and map out future directions. The workshop program comprised the presentation of 8 papers and 2 keynotes, followed by extensive discussion. Overall, the community matured by discussing how to design, build, and evaluate bots. The community aims to organise a 3rd edition of the workshop. Website: http://botse.org/","2021-02","2021-05-18 16:29:09","2021-05-18 16:29:09","2021-05-18 16:29:09","20-22","","1","46","","SIGSOFT Softw. Eng. Notes","","","","","","","","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\MG2GCA4C\Shihab et al. - 2021 - Summary of the 2nd International Workshop on Bots .pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"JGLGAAPG","journalArticle","2019","Silva, Rodrigo F. G.; Roy, Chanchal K.; Rahman, Mohammad Masudur; Schneider, Kevin A.; Paixao, Klerisson; Maia, Marcelo de Almeida","Recommending Comprehensive Solutions for Programming Tasks by Mining Crowd Knowledge","arXiv:1903.07662 [cs]","","","","http://arxiv.org/abs/1903.07662","Developers often search for relevant code examples on the web for their programming tasks. Unfortunately, they face two major problems. First, the search is impaired due to a lexical gap between their query (task description) and the information associated with the solution. Second, the retrieved solution may not be comprehensive, i.e., the code segment might miss a succinct explanation. These problems make the developers browse dozens of documents in order to synthesize an appropriate solution. To address these two problems, we propose CROKAGE (Crowd Knowledge Answer Generator), a tool that takes the description of a programming task (the query) and provides a comprehensive solution for the task. Our solutions contain not only relevant code examples but also their succinct explanations. Our proposed approach expands the task description with relevant API classes from Stack Overflow Q&A threads and then mitigates the lexical gap problems. Furthermore, we perform natural language processing on the top quality answers and then return such programming solutions containing code examples and code explanations unlike earlier studies. We evaluate our approach using 97 programming queries, of which 50% was used for training and 50% was used for testing, and show that it outperforms six baselines including the state-of-art by a statistically significant margin. Furthermore, our evaluation with 29 developers using 24 tasks (queries) confirms the superiority of CROKAGE over the state-of-art tool in terms of relevance of the suggested code examples, benefit of the code explanations and the overall solution quality (code + explanation).","2019-03-20","2021-05-18 16:29:12","2021-05-18 16:29:12","2021-05-18 16:29:12","","","","","","","","","","","","","","en","","","","","arXiv.org","","arXiv: 1903.07662","","C:\Users\sant_si\Zotero\storage\EKYW5JGC\Silva et al. - 2019 - Recommending Comprehensive Solutions for Programmi.pdf","","included; Snowballing; repo","Computer Science - Software Engineering","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"FB95VSXU","bookSection","2020","PérezSoler, Sara; Daniel, Gwendal; Cabot, Jordi; Guerra, Esther; de Lara, Juan","Towards Automating the Synthesis of Chatbots for Conversational Model Query","Enterprise, Business-Process and Information Systems Modeling","978-3-030-49417-9 978-3-030-49418-6","","","http://link.springer.com/10.1007/978-3-030-49418-6_17","Conversational interfaces (also called chatbots) are being increasingly adopted in various domains such as e-commerce or customer service, as a direct communication channel between companies and end-users. Their advantage is that they can be embedded within social networks, and provide a natural language (NL) interface that enables their use by non-technical users. While there are many emerging platforms for building chatbots, their construction remains a highly technical, challenging task.","2020","2021-05-18 16:29:14","2021-05-28 19:58:13","2021-05-18 16:29:14","257-265","","","387","","","","","","","","Springer International Publishing","Cham","en","","","","","DOI.org (Crossref)","","Series Title: Lecture Notes in Business Information Processing DOI: 10.1007/978-3-030-49418-6_17","","C:\Users\sant_si\Zotero\storage\3TLLWPSD\Pérez-Soler et al. - 2020 - Towards Automating the Synthesis of Chatbots for C.pdf","","included; Snowballing; repo","","Nurcan, Selmin; Reinhartz-Berger, Iris; Soffer, Pnina; Zdravkovic, Jelena","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"TWP69HNW","conferencePaper","2020","Stulova, Nataliia; Blasi, Arianna; Gorla, Alessandra; Nierstrasz, Oscar","Towards Detecting Inconsistent Comments in Java Source Code Automatically","2020 IEEE 20th International Working Conference on Source Code Analysis and Manipulation (SCAM)","978-1-72819-248-2","","10.1109/SCAM51674.2020.00012","https://ieeexplore.ieee.org/document/9252010/","","2020-09","2021-05-18 16:29:17","2021-05-18 16:29:17","2021-05-18 16:29:17","65-69","","","","","","","","","","","IEEE","Adelaide, Australia","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\WGIPBFC6\Stulova et al. - 2020 - Towards Detecting Inconsistent Comments in Java So.pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2020 IEEE 20th International Working Conference on Source Code Analysis and Manipulation (SCAM)","","","","","","","","","","","","","","",""
"JUCPXVKY","conferencePaper","2020","Washizaki, Hironori","Towards Software Value Co-Creation with AI","2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)","978-1-72817-303-0","","10.1109/COMPSAC48688.2020.0-112","https://ieeexplore.ieee.org/document/9202754/","We present a vision called “value co-creation of software by artificial intelligence (AI) and developers.” In this vision, AI and developers work in collaboration as equal partners to co-create business and societal values through software system development and operations. Towards this vision, we discuss AI automation for development focusing on machine learning by introducing examples, including our own. Finally, we envision the future of value co-creation by AI and developers.","2020-07","2021-05-18 16:29:18","2021-05-18 16:29:18","2021-05-18 16:29:18","1117-1118","","","","","","","","","","","IEEE","Madrid, Spain","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\BY95YMPG\Washizaki - 2020 - Towards Software Value Co-Creation with AI.pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)","","","","","","","","","","","","","","",""
"KUJFICYM","conferencePaper","2020","Wessel, Mairieli","Enhancing developers’ support on pull requests activities with software bots","Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering","978-1-4503-7043-1","","10.1145/3368089.3418539","https://dl.acm.org/doi/10.1145/3368089.3418539","Software bots are employed to support developers’ activities, serving as conduits between developers and other tools. Due to their focus on task automation, bots have become particularly relevant for Open Source Software (OSS) projects hosted on GitHub. While bots are adopted to save development cost, time, and effort, the bots’ presence can be disruptive to the community. My research goal is two-fold: (i) identify problems caused by bots that interact in pull requests, and (ii) help bot designers enhance existing bots. Toward this end, we are interviewing maintainers, contributors, and bot developers to understand the problems in the human-bot interaction and how they affect the collaboration in a project. Afterward, we will employ Design Fiction to capture the developers’ vision of bots’ capabilities, in order to define guidelines for the design of bots on social coding platforms, and derive requirements for a meta-bot to deal with the problems. This work contributes more broadly to the design and use of software bots to enhance developers’ collaboration and interaction.","2020-11-08","2021-05-18 16:29:21","2021-05-18 16:29:21","2021-05-18 16:29:21","1674-1677","","","","","","","","","","","ACM","Virtual Event USA","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\QFLWCKVM\Wessel - 2020 - Enhancing developers’ support on pull requests act.pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","ESEC/FSE '20: 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering","","","","","","","","","","","","","","",""
"2CM2UJ6F","conferencePaper","2020","Wessel, Mairieli; Serebrenik, Alexander; Wiese, Igor; Steinmacher, Igor; Gerosa, Marco A.","What to Expect from Code Review Bots on GitHub?: A Survey with OSS Maintainers","Proceedings of the 34th Brazilian Symposium on Software Engineering","978-1-4503-8753-8","","10.1145/3422392.3422459","https://dl.acm.org/doi/10.1145/3422392.3422459","Software bots are used by Open Source Software (OSS) projects to streamline the code review process. Interfacing between developers and automated services, code review bots report continuous integration failures, code quality checks, and code coverage. However, the impact of such bots on maintenance tasks is still neglected. In this paper, we study how project maintainers experience code review bots. We surveyed 127 maintainers and asked about their expectations and perception of changes incurred by code review bots. Our findings reveal that the most frequent expectations include enhancing the feedback bots provide to developers, reducing the maintenance burden for developers, and enforcing code coverage. While maintainers report that bots satisfied their expectations, they also perceived unexpected effects, such as communication noise and newcomers’ dropout. Based on these results, we provide a series of implications for bot developers, as well as insights for future research.","2020-10-21","2021-05-18 16:29:23","2021-05-18 16:29:23","2021-05-18 16:29:23","457-462","","","","","","What to Expect from Code Review Bots on GitHub?","","","","","ACM","Natal Brazil","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\49PN82LZ\Wessel et al. - 2020 - What to Expect from Code Review Bots on GitHub A.pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","SBES '20: 34th Brazilian Symposium on Software Engineering","","","","","","","","","","","","","","",""
"AR7I2HL9","conferencePaper","2020","Wessel, Mairieli; Serebrenik, Alexander; Wiese, Igor; Steinmacher, Igor; Gerosa, Marco A.","Effects of Adopting Code Review Bots on Pull Requests to OSS Projects","2020 IEEE International Conference on Software Maintenance and Evolution (ICSME)","978-1-72815-619-4","","10.1109/ICSME46990.2020.00011","https://ieeexplore.ieee.org/document/9240622/","Software bots, which are widely adopted by Open Source Software (OSS) projects, support developers on several activities, including code review. However, as with any new technology adoption, bots may impact group dynamics. Since understanding and anticipating such effects is important for planning and management, we investigate how several activity indicators change after the adoption of a code review bot. We employed a regression discontinuity design on 1,194 software projects from GitHub. Our results indicate that the adoption of code review bots increases the number of monthly merged pull requests, decreases monthly non-merged pull requests, and decreases communication among developers. Practitioners and maintainers may leverage our results to understand, or even predict, bot effects on their projects’ social interactions.","2020-09","2021-05-18 16:29:25","2021-05-18 16:29:25","2021-05-18 16:29:25","1-11","","","","","","","","","","","IEEE","Adelaide, Australia","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\DMZSFQZV\Wessel et al. - 2020 - Effects of Adopting Code Review Bots on Pull Reque.pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2020 IEEE International Conference on Software Maintenance and Evolution (ICSME)","","","","","","","","","","","","","","",""
"EXQU5U9C","journalArticle","2021","Wessel, Mairieli; Wiese, Igor; Steinmacher, Igor; Gerosa, Marco A.","Don't Disturb Me: Challenges of Interacting with SoftwareBots on Open Source Software Projects","arXiv:2103.13950 [cs]","","","","http://arxiv.org/abs/2103.13950","Software bots are used to streamline tasks in Open Source Software (OSS) projects' pull requests, saving development cost, time, and effort. However, their presence can be disruptive to the community. We identified several challenges caused by bots in pull request interactions by interviewing 21 practitioners, including project maintainers, contributors, and bot developers. In particular, our findings indicate noise as a recurrent and central problem. Noise affects both human communication and development workflow by overwhelming and distracting developers. Our main contribution is a theory of how human developers perceive annoying bot behaviors as noise on social coding platforms. This contribution may help practitioners understand the effects of adopting a bot, and researchers and tool designers may leverage our results to better support human-bot interaction on social coding platforms.","2021-03-25","2021-05-18 16:29:28","2021-05-18 16:29:29","2021-05-18 16:29:28","","","","","","","Don't Disturb Me","","","","","","","en","","","","","arXiv.org","","arXiv: 2103.13950","","C:\Users\sant_si\Zotero\storage\S6SQU4YV\Wessel et al. - 2021 - Don't Disturb Me Challenges of Interacting with S.pdf","","included; Snowballing; repo","Computer Science - Software Engineering","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"S6QDJJU7","conferencePaper","2020","Wood, Andrew; Eberhart, Zachary; McMillan, Collin","Dialogue Act Classification for Virtual Agents for Software Engineers during Debugging","Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops","978-1-4503-7963-2","","10.1145/3387940.3391487","https://dl.acm.org/doi/10.1145/3387940.3391487","A “dialogue act” is a written or spoken action during a conversation. Dialogue acts are usually only a few words long, and are often categorized by researchers into a relatively small set of dialogue act types, such as eliciting information, expressing an opinion, or making a greeting. Research interest into automatic classification of dialogue acts has grown recently due to the proliferation of Virtual Agents (VA) e.g. Siri, Cortana, Alexa. But unfortunately, the gains made into VA development in one domain are generally not applicable to other domains, since the composition of dialogue acts differs in different conversations. In this paper, we target the problem of dialogue act classification for a VA for software engineers repairing bugs. A problem in the SE domain is that very little sample data exists – the only public dataset is a recently-released Wizard of Oz study with 30 conversations. Therefore, we present a transferlearning technique to learn on a much larger dataset for general business conversations, and apply the knowledge to the SE dataset. In an experiment, we observe between 8% and 20% improvement over two key baselines.","2020-06-27","2021-05-18 16:29:31","2021-05-18 16:29:31","2021-05-18 16:29:31","462-469","","","","","","","","","","","ACM","Seoul Republic of Korea","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\GB7JFXDF\Wood et al. - 2020 - Dialogue Act Classification for Virtual Agents for.pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","ICSE '20: 42nd International Conference on Software Engineering","","","","","","","","","","","","","","",""
"TA24Q8WH","journalArticle","2021","Wyrich, Marvin; Ghit, Raoul; Haller, Tobias; Müller, Christian","Bots Don't Mind Waiting, Do They? Comparing the Interaction With Automatically and Manually Created Pull Requests","arXiv:2103.03591 [cs]","","","","http://arxiv.org/abs/2103.03591","As a maintainer of an open source software project, you are usually happy about contributions in the form of pull requests that bring the project a step forward. Past studies have shown that when reviewing a pull request, not only its content is taken into account, but also, for example, the social characteristics of the contributor. Whether a contribution is accepted and how long this takes therefore depends not only on the content of the contribution. What we only have indications for so far, however, is that pull requests from bots may be prioritized lower, even if the bots are explicitly deployed by the development team and are considered useful.","2021-03-05","2021-05-18 16:29:34","2021-05-18 16:29:34","2021-05-18 16:29:34","","","","","","","Bots Don't Mind Waiting, Do They?","","","","","","","en","","","","","arXiv.org","","arXiv: 2103.03591","","C:\Users\sant_si\Zotero\storage\4JPQYFLR\Wyrich et al. - 2021 - Bots Don't Mind Waiting, Do They Comparing the In.pdf","","included; Snowballing; repo","Computer Science - Software Engineering; Computer Science - Human-Computer Interaction","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"244M49SG","conferencePaper","2019","Xu, Congying; Min, Bosen; Sun, Xiaobing; Hu, Jiajun; Li, Bin; Duan, Yucong","MULAPI: A Tool for API Method and Usage Location Recommendation","2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","978-1-72811-764-5","","10.1109/ICSE-Companion.2019.00053","https://ieeexplore.ieee.org/document/8802650/","Software is incrementally evolved as various new feature requests are implemented to meet users’ requirements. To accelerate the incoming feature implementation, developers often utilize existing third-party APIs that encapsulate featurerelated functionality into simple APIs. However, it is non-trivial for developers to choose which APIs to use and where to use them in a target program since the search space of APIs and their usage locations are usually large. In this paper, we introduce a tool, MULAPI, to facilitate the decision of suitable APIs at potential usage locations for implementing the incoming feature requests. MULAPI combines feature localization and information retrieval techniques to accomplish API recommendation and usage location. Empirical studies demonstrate that MULAPI can effectively recommend correct APIs and their usage locations with higher precision than state-of-the-art approaches. The video of our demo is available at https://youtu.be/s3Cs5ltqdvs.","2019-05","2021-05-18 16:29:36","2021-05-18 16:29:36","2021-05-18 16:29:36","119-122","","","","","","MULAPI","","","","","IEEE","Montreal, QC, Canada","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\M6FQIYJM\Xu et al. - 2019 - MULAPI A Tool for API Method and Usage Location R.pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","","","","","","","","","","","","","","",""
"L3F2CSTW","journalArticle","2021","Baudry, Benoit; Chen, Zimin; Etemadi, Khashayar; Fu, Han; Ginelli, Davide; Kommrusch, Steve; Martinez, Matias; Monperrus, Martin; Ron, Javier; Ye, He; Yu, Zhongxing","A Software Repair Bot based on Continual Learning","IEEE Software","","0740-7459, 1937-4194","10.1109/ms.2021.3070743","http://arxiv.org/abs/2012.06824","Software bugs are common and correcting them accounts for a significant part of costs in the software development and maintenance process. This calls for automatic techniques to deal with them. One promising direction towards this goal is gaining repair knowledge from historical bug fixing examples. Retrieving insights from software development history is particularly appealing with the constant progress of machine learning paradigms and skyrocketing ‘big’ bug fixing data generated through Continuous Integration (CI). In this paper, we present R-HERO, a novel software repair bot that applies continual learning to acquire bug fixing strategies from continuous streams of source code changes, implemented for the single development platform Github/Travis CI. We describe R-HERO, our novel system for learning how to fix bugs based on continual training, and we uncover initial successes as well as novel research challenges for the community.","2021","2021-05-18 16:29:39","2021-05-18 16:29:39","2021-05-18 16:29:39","0-0","","","","","IEEE Softw.","","","","","","","","en","","","","","arXiv.org","","arXiv: 2012.06824","","C:\Users\sant_si\Zotero\storage\SLGWU83T\Baudry et al. - 2021 - A Software Repair Bot based on Continual Learning.pdf","","included; Snowballing; repo","Computer Science - Software Engineering","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"WK5FNZMQ","journalArticle","2020","Baum, David; Bechert, Stefan; Eisenecker, Ulrich; Meichsner, Isabelle; Müller, Richard","Identifying Usability Issues of Software Analytics Applications in Immersive Augmented Reality","arXiv:2008.06099 [cs]","","","","http://arxiv.org/abs/2008.06099","Software analytics in augmented reality (AR) is said to have great potential. One reason why this potential is not yet fully exploited may be usability problems of the AR user interfaces. We present an iterative and qualitative usability evaluation with 15 subjects of a state-of-the-art application for software analytics in AR. We could identify and resolve numerous usability issues. Most of them were caused by applying conventional user interface elements, such as dialog windows, buttons, and scrollbars. The used city visualization, however, did not cause any usability issues. Therefore, we argue that future work should focus on making conventional user interface elements in AR obsolete by integrating their functionality into the immersive visualization.","2020-08-13","2021-05-18 16:29:43","2021-05-18 16:29:43","2021-05-18 16:29:43","","","","","","","","","","","","","","en","","","","","arXiv.org","","arXiv: 2008.06099","","C:\Users\sant_si\Zotero\storage\N669PXZB\Baum et al. - 2020 - Identifying Usability Issues of Software Analytics.pdf","","included; Snowballing; repo","Computer Science - Human-Computer Interaction","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"BETT6N9Y","conferencePaper","2017","Bieliauskas, Stefan; Schreiber, Andreas","A Conversational User Interface for Software Visualization","2017 IEEE Working Conference on Software Visualization (VISSOFT)","978-1-5386-1003-9","","10.1109/VISSOFT.2017.21","https://ieeexplore.ieee.org/document/8091199/","Software visualizations provide many different complex views with different filters and metrics. But often users have a specific question to which they want to have an answer or they need to find the best visualization by themselves and are not aware of other metrics and possibilities of the visualization tool. We propose an interaction with software visualizations based on a conversational interface. The developed tool extracts meta information from natural language sentences and displays the best fitting software visualization by adjusting metrics and filter settings.","2017-09","2021-05-18 16:29:45","2021-05-18 16:29:45","2021-05-18 16:29:45","139-143","","","","","","","","","","","IEEE","Shanghai","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\UPJT89UE\Bieliauskas and Schreiber - 2017 - A Conversational User Interface for Software Visua.pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2017 IEEE Working Conference on Software Visualization (VISSOFT)","","","","","","","","","","","","","","",""
"XT4SIDPT","conferencePaper","2019","Black, Dana; Rapos, Eric J.; Stephan, Matthew","Voice-Driven Modeling: Software Modeling Using Automated Speech Recognition","2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C)","978-1-72815-125-0","","10.1109/MODELS-C.2019.00040","https://ieeexplore.ieee.org/document/8904620/","Voice-driven programming allows engineers to alleviate physical discomfort, pain, and injury. It also has the potential to be faster than typing and assist those with disabilities. While there are a number of solutions to voice-driven programming, Model-Driven Engineering (MDE) has yet to exploit this non-conventional but high-potential approach to software development. Standard convention in MDE practice involves creating software models using a traditional mouse and keyboard combination, or whiteboard sketch hardware. In this position paper, we introduce our vision and ideas for a Voice-Driven Modeling (VDM) approach. Our vision involves a framework that includes 3 phases: Speech Processing, Natural Language Processing, and Context Specific Modeling. We describe these 3 phases in this paper, which others can apply in their attempts to realize VDM. We additionally include our research plans for developing a VDM solution targeted at Simulink models and our early proof of concept capable of implementing several example commands. We establish the pertinence of this work through a survey that finds negligible work on VDM and highlights the potential impact this can have on the field of MDE as a whole. Specifically, it is our position that it can have a positive impact on modelers in general, modelers with disabilities, and domain experts not familiar with modeling. It is our hope that this work helps fuel research in this area, allowing for a new way to develop software models.","2019-09","2021-05-18 16:29:47","2021-05-18 16:29:47","2021-05-18 16:29:47","252-258","","","","","","Voice-Driven Modeling","","","","","IEEE","Munich, Germany","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\4BCG6FPI\Black et al. - 2019 - Voice-Driven Modeling Software Modeling Using Aut.pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C)","","","","","","","","","","","","","","",""
"L6GWV4WS","conferencePaper","2020","Boubekeur, Younes; Mussbacher, Gunter","Towards a better understanding of interactions with a domain modeling assistant","Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings","978-1-4503-8135-2","","10.1145/3417990.3418742","https://dl.acm.org/doi/10.1145/3417990.3418742","The enrolment of software engineering students has increased rapidly in the past few years following industry demand. At the same time, model-driven engineering (MDE) continues to become relevant to more domains like embedded systems and machine learning. It is therefore important to teach students MDE skills in an effective manner to prepare them for future careers in academia and industry. The use of interactive online tools can help instructors deliver course material to more students in a more efficient manner, allowing them to offload repetitive or tedious tasks to these systems and focus on other teaching activities that cannot be easily automated. Interactive online tools can provide students with a more engaging learning experience than static resources like books or written exercises. Domain modeling with class diagrams is a fundamental modeling activity in MDE. While there exist multiple modeling tools that allow students to build a domain model, none of them offer an interactive learning experience. In this paper, we explore the interactions between a student modeler and an interactive domain modeling assistant with the aim of better understanding the required interaction. We illustrate desired interactions with three examples and then formalize them in a metamodel. Based on the metamodel, we explain how to form a corpus of learning material that supports the assistant interactions.","2020-10-16","2021-05-18 16:29:49","2021-05-18 16:29:49","2021-05-18 16:29:49","1-10","","","","","","","","","","","ACM","Virtual Event Canada","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\TW9F48ST\Boubekeur and Mussbacher - 2020 - Towards a better understanding of interactions wit.pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","MODELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems","","","","","","","","","","","","","","",""
"L8TU2HDF","bookSection","2020","Corti, Giancarlo; Ambrosini, Luca; Guidi, Roberto; Rizzo, Nicola","*Thing: Improve Anything to Anything Collaboration","Advances in Information and Communication","978-3-030-12384-0 978-3-030-12385-7","","","http://link.springer.com/10.1007/978-3-030-12385-7_34","This is a work in the context of Collaborative Working Environment (CWE). In particular, in that of collaboration and productivity software tools. CWEs have seen the adoption of application software to addresses business problems as team communication and workload management. Instant messaging solutions, mobile devices and the virtual assistant paradigm have also come into the picture. Software tools in this context lack nonetheless real collaborative features. The problem that we address in this work is therefore that of a truly collaborating team collaboration and productivity software environment. Our approach leverages recent trends, like that of instant chats, virtual assistants and the Internet of Things, focuses on team members utterances and on a customizable and configurable bot framework to automate routine tasks, provide content over structure information management, and enable workflow management to improve productivity. The result is a prototypical software product which: enables the collaboration of both humans and Internet enabled things alike, provides easy context driven collaboration (i.e. entities graphs), allows the systematic processing of messages exchanged in a concurrent multi-user environment to fulfill team actions, provides a middle layer bot framework that handles the dialog flow for these actions and the interaction with any external systems. All of which distinguishes it from current software solutions. Given the features and the architecture of our original software components, we can confidently state that their adoption would enable software developers to create more effective collaboration and productivity working environment software tools.","2020","2021-05-18 16:29:51","2021-05-18 16:29:51","2021-05-18 16:29:51","453-465","","","70","","","*Thing","","","","","Springer International Publishing","Cham","en","","","","","DOI.org (Crossref)","","Series Title: Lecture Notes in Networks and Systems DOI: 10.1007/978-3-030-12385-7_34","","C:\Users\sant_si\Zotero\storage\EJK87536\Corti et al. - 2020 - Thing Improve Anything to Anything Collaboration.pdf","","included; Snowballing; repo","","Arai, Kohei; Bhatia, Rahul","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"32KSLTU9","conferencePaper","2020","da Silva, Bruno; Hebert, Chloe; Rawka, Abhishu; Sereesathien, Siriwan","Robin: A Voice Controlled Virtual Teammate for Software Developers and Teams","2020 IEEE International Conference on Software Maintenance and Evolution (ICSME)","978-1-72815-619-4","","10.1109/ICSME46990.2020.00092","https://ieeexplore.ieee.org/document/9240682/","Software developers typically collaborate while relying on source code management tools and platforms such as Git and GitHub, which involve process workflow and issue-tracking, for development and maintenance of software-intensive solutions. Developers may lose concentration and productivity when having to navigate through numerous screens to perform daily tasks, which are oftentimes too repetitive, such as applying labels and assigning members to issues, finding who has open pull requests (and how many), closing issues/branches/pull requests, finding open issues, to name a few. Therefore, we hypothesize that current tools need to be improved to increase the developer and team experience and productivity in software projects. Consequently, we have developed Robin, a voice-controlled virtual teammate, to assist developers and teams on projects that strongly rely on source code control and issue tracking. In this short paper, we provide an overview of related work, some design decisions we have made, and insights for the road ahead.","2020-09","2021-05-18 16:29:53","2021-05-18 16:29:53","2021-05-18 16:29:53","789-791","","","","","","Robin","","","","","IEEE","Adelaide, Australia","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\29YPWNFF\da Silva et al. - 2020 - Robin A Voice Controlled Virtual Teammate for Sof.pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2020 IEEE International Conference on Software Maintenance and Evolution (ICSME)","","","","","","","","","","","","","","",""
"XRDGPYPR","conferencePaper","2020","Dominic, James; Houser, Jada; Steinmacher, Igor; Ritter, Charles; Rodeghero, Paige","Conversational Bot for Newcomers Onboarding to Open Source Projects","Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops","978-1-4503-7963-2","","10.1145/3387940.3391534","https://dl.acm.org/doi/10.1145/3387940.3391534","This paper targets the problems newcomers face when onboarding to open source projects and the low retention rate of newcomers. Open source software projects are becoming increasingly more popular. Many major companies have started building open source software. Unfortunately, many newcomers only commit once to an open source project before moving on to another project. Even worse, many novices struggle with joining open source communities and end up leaving quickly, sometimes before their first successful contribution. In this paper, we propose a conversational bot that would recommend projects to newcomers and assist in the onboarding to the open source community. The bot would be able to provide helpful resources, such as Stack Overflow related content. It would also be able to recommend human mentors. We believe that this bot would improve newcomers’ experience by providing support not only during their first contribution, but by acting as an agent to engage them to the project.","2020-06-27","2021-05-18 16:29:55","2021-05-18 16:29:55","2021-05-18 16:29:55","46-50","","","","","","","","","","","ACM","Seoul Republic of Korea","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\JM6IXZHR\Dominic et al. - 2020 - Conversational Bot for Newcomers Onboarding to Ope.pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","ICSE '20: 42nd International Conference on Software Engineering","","","","","","","","","","","","","","",""
"XG24LE6J","bookSection","2020","edDouibi, Hamza; Daniel, Gwendal; Cabot, Jordi","OpenAPI Bot: A Chatbot to Help You Understand REST APIs","Web Engineering","978-3-030-50577-6 978-3-030-50578-3","","","http://link.springer.com/10.1007/978-3-030-50578-3_40","REST APIs are an essential building block in many Web applications. The lack of a standard machine-readable format to describe these REST APIs triggered the creation of several specification languages to formally define REST APIs, with the OpenAPI specification currently taking the lead. OpenAPI definitions are consumed by a growing ecosystem of tools aimed at automating tasks such as generating server/client SDKs and API documentations. However, current OpenAPI documentation tools mostly provide simple descriptive Web pages enumerating all the API operations and corresponding parameters, but do not offer interactive capabilities to help navigate the API and ask relevant information. Therefore, learning how to use an API and how its different parts are interrelated still requires a considerable time investment. To overcome this situation we present our O API B , a chatbot able to read an OpenAPI definition for you and answer the questions you may have about it.","2020","2021-05-18 16:29:57","2021-05-29 08:10:00","2021-05-18 16:29:57","538-542","","","12128","","","OpenAPI Bot","","","","","Springer International Publishing","Cham","en","","","","","DOI.org (Crossref)","","Series Title: Lecture Notes in Computer Science DOI: 10.1007/978-3-030-50578-3_40","","C:\Users\sant_si\Zotero\storage\GDX4BS4V\Ed-Douibi et al. - 2020 - OpenAPI Bot A Chatbot to Help You Understand REST.pdf","","included; Snowballing; repo","","Bielikova, Maria; Mikkonen, Tommi; Pautasso, Cesare","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"TUUQVKHR","journalArticle","2021","Golzadeh, Mehdi; Decan, Alexandre; Legay, Damien; Mens, Tom","A ground-truth dataset and classification model for detecting bots in GitHub issue and PR comments","Journal of Systems and Software","","01641212","10.1016/j.jss.2021.110911","http://arxiv.org/abs/2010.03303","Bots are frequently used in Github repositories to automate repetitive activities that are part of the distributed software development process. They communicate with human actors through comments. While detecting their presence is important for many reasons, no large and representative ground-truth dataset is available, nor are classification models to detect and validate bots on the basis of such a dataset. This paper proposes a ground-truth dataset, based on a manual analysis with high interrater agreement, of pull request and issue comments in 5,000 distinct Github accounts of which 527 have been identified as bots. Using this dataset we propose an automated classification model to detect bots, taking as main features the number of empty and non-empty comments of each account, the number of comment patterns, and the inequality between comments within comment patterns. We obtained a very high weighted average precision, recall and F1-score of 0.98 on a test set containing 40% of the data. We integrated the classification model into an open source command-line tool to allow practitioners to detect which accounts in a given Github repository actually correspond to bots.","2021-05","2021-05-18 16:30:01","2021-05-18 16:30:01","2021-05-18 16:30:01","110911","","","175","","Journal of Systems and Software","","","","","","","","en","","","","","arXiv.org","","arXiv: 2010.03303","","C:\Users\sant_si\Zotero\storage\GHMRF4LS\Golzadeh et al. - 2021 - A ground-truth dataset and classification model fo.pdf","","included; Snowballing; repo","Computer Science - Machine Learning; Computer Science - Software Engineering","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"A64JAQPB","journalArticle","2021","Golzadeh, Mehdi; Decan, Alexandre; Constantinou, Eleni; Mens, Tom","Identifying bot activity in GitHub pull request and issue comments","arXiv:2103.06042 [cs]","","","","http://arxiv.org/abs/2103.06042","Development bots are used on Github to automate repetitive activities. Such bots communicate with human actors via issue comments and pull request comments. Identifying such bot comments allows to prevent bias in socio-technical studies related to software development. To automate their identification, we propose a classification model based on natural language processing. Starting from a balanced ground-truth dataset of 19,282 PR and issue comments, we encode the comments as vectors using a combination of the bag of words and TF-IDF techniques. We train a range of binary classifiers to predict the type of comment (human or bot) based on this vector representation. A multinomial Naive Bayes classifier provides the best results. Its performance on a test set containing 50% of the data achieves an average precision, recall, and F1 score of 0.88. Although the model shows a promising result on the pull request and issue comments, further work is required to generalize the model on other types of activities, like commit messages and code reviews.","2021-03-10","2021-05-18 16:30:04","2021-05-18 16:30:04","2021-05-18 16:30:04","","","","","","","","","","","","","","en","","","","","arXiv.org","","arXiv: 2103.06042","","C:\Users\sant_si\Zotero\storage\42FHCUU8\Golzadeh et al. - 2021 - Identifying bot activity in GitHub pull request an.pdf","","included; Snowballing; repo","Computer Science - Software Engineering","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"CEPPYTP9","conferencePaper","2020","Ilic, Anita; Licina, Ana; Savic, Dusan","Chatbot development using Java tools and libraries","2020 24th International Conference on Information Technology (IT)","978-1-72815-136-6","","10.1109/IT48810.2020.9070294","https://ieeexplore.ieee.org/document/9070294/","The aim of this paper is the development of an intelligent programming robot for help with coding, using Java tools and libraries. This paper will examine the development process of Java software bots and their general objective. For the purpose of the successful development of an intelligent programming robot, the paper will provide theoretical guidance in selecting frameworks and development tools and assist in the development process, training and testing. It will compare existing software development tools for creating the bot that will quickly and reliably answer programming questions to users in the form of a conversation. As a result, it will provide a thorough foundation for the complete development of a chatbot.","2020-02","2021-05-18 16:30:06","2021-05-18 16:30:06","2021-05-18 16:30:06","1-4","","","","","","","","","","","IEEE","Zabljak, Montenegro","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\ETX9TTYR\Ilic et al. - 2020 - Chatbot development using Java tools and libraries.pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2020 24th International Conference on Information Technology (IT)","","","","","","","","","","","","","","",""
"65792HK5","conferencePaper","2019","Kimani, Everlyne; Rowan, Kael; McDuff, Daniel; Czerwinski, Mary; Mark, Gloria","A Conversational Agent in Support of Productivity and Wellbeing at Work","2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII)","978-1-72813-888-6","","10.1109/ACII.2019.8925488","https://ieeexplore.ieee.org/document/8925488/","","2019-09","2021-05-18 16:30:08","2021-05-18 16:30:08","2021-05-18 16:30:08","1-7","","","","","","","","","","","IEEE","Cambridge, United Kingdom","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\E92CDFP2\Kimani et al. - 2019 - A Conversational Agent in Support of Productivity .pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII)","","","","","","","","","","","","","","",""
"GXI7GAYP","journalArticle","2021","Kinsman, Timothy; Wessel, Mairieli; Gerosa, Marco A.; Treude, Christoph","How Do Software Developers Use GitHub Actions to Automate Their Workflows?","arXiv:2103.12224 [cs]","","","","http://arxiv.org/abs/2103.12224","Automated tools are frequently used in social coding repositories to perform repetitive activities that are part of the distributed software development process. Recently, GitHub introduced GitHub Actions, a feature providing automated workflows for repository maintainers. Although several Actions have been built and used by practitioners, relatively little has been done to evaluate them. Understanding and anticipating the effects of adopting such kind of technology is important for planning and management. Our research is the first to investigate how developers use Actions and how several activity indicators change after their adoption. Our results indicate that, although only a small subset of repositories adopted GitHub Actions to date, there is a positive perception of the technology. Our findings also indicate that the adoption of GitHub Actions increases the number of monthly rejected pull requests and decreases the monthly number of commits on merged pull requests. These results are especially relevant for practitioners to understand and prevent undesirable effects on their projects.","2021-03-22","2021-05-18 16:30:11","2021-05-18 16:30:11","2021-05-18 16:30:11","","","","","","","","","","","","","","en","","","","","arXiv.org","","arXiv: 2103.12224","","C:\Users\sant_si\Zotero\storage\SF9I5WER\Kinsman et al. - 2021 - How Do Software Developers Use GitHub Actions to A.pdf","","included; Snowballing; repo","Computer Science - Software Engineering","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"46EMP4XV","journalArticle","2020","Koyuncu, Anil; Bissyandé, Tegawendé F.; Klein, Jacques; Traon, Yves Le","FlexiRepair: Transparent Program Repair with Generic Patches","arXiv:2011.13280 [cs]","","","","http://arxiv.org/abs/2011.13280","Template-based program repair research is in need for a common ground to express fix patterns in a standard and reusable manner. We propose to build on the concept of generic patch (also known as semantic patch), which is widely used in the Linux community to automate code evolution. We advocate that generic patches could provide at the same time a unified representation and a specification for fix patterns. Generic patches are indeed formally defined, and there exists a robust, industry-adapted, and extensible engine that processes generic patches to perform control-flow code matching and automatically generates concretes patches based on the specified change operations.","2020-11-26","2021-05-18 16:30:14","2021-05-18 16:30:14","2021-05-18 16:30:14","","","","","","","FlexiRepair","","","","","","","en","","","","","arXiv.org","","arXiv: 2011.13280","","C:\Users\sant_si\Zotero\storage\ADBXY7XN\Koyuncu et al. - 2020 - FlexiRepair Transparent Program Repair with Gener.pdf","","included; Snowballing; repo","Computer Science - Software Engineering","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"XMJ5KWH5","conferencePaper","2020","Kuttal, Sandeep Kaur; Myers, Jarow; Gurka, Sam; Magar, David; Piorkowski, David; Bellamy, Rachel","Towards Designing Conversational Agents for Pair Programming: Accounting for Creativity Strategies and Conversational Styles","2020 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)","978-1-72816-901-9","","10.1109/VL/HCC50065.2020.9127276","https://ieeexplore.ieee.org/document/9127276/","Established research on pair programming reveals benefits, including increasing communication, creativity, selfefficacy, and promoting gender inclusivity. However, research has reported limitations such as finding a compatible partner, scheduling sessions between partners, and resistance to pairing. Further, pairings can be affected by predispositions to negative stereotypes. These problems can be addressed by replacing one human member of the pair with a conversational agent. To investigate the design space of such a conversational agent, we conducted a controlled remote pair programming study. Our analysis found various creative problem-solving strategies and differences in conversational styles. We further analyzed the transferable strategies from human-human collaboration to human-agent collaboration by conducting a Wizard of Oz study. The findings from the two studies helped us gain insights regarding design of a programmer conversational agent. We make recommendations for researchers and practitioners for designing pair programming conversational agent tools.","2020-08","2021-05-18 16:30:16","2021-05-18 16:30:17","2021-05-18 16:30:16","1-11","","","","","","Towards Designing Conversational Agents for Pair Programming","","","","","IEEE","Dunedin, New Zealand","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\QXNY8JPB\Kuttal et al. - 2020 - Towards Designing Conversational Agents for Pair P.pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2020 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)","","","","","","","","","","","","","","",""
"BD6BR39D","conferencePaper","2017","Mirhosseini, Samim; Parnin, Chris","Can automated pull requests encourage software developers to upgrade out-of-date dependencies?","2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE)","978-1-5386-2684-9","","10.1109/ASE.2017.8115621","http://ieeexplore.ieee.org/document/8115621/","Developers neglect to update legacy software dependencies, resulting in buggy and insecure software. One explanation for this neglect is the difficulty of constantly checking for the availability of new software updates, verifying their safety, and addressing any migration efforts needed when upgrading a dependency. Emerging tools attempt to address this problem by introducing automated pull requests and project badges to inform the developer of stale dependencies. To understand whether these tools actually help developers, we analyzed 7,470 GitHub projects that used these notification mechanisms to identify any change in upgrade behavior. Our results find that, on average, projects that use pull request notifications upgraded 1.6x as often as projects that did not use any tools. Badge notifications were slightly less effective: users upgraded 1.4x more frequently. Unfortunately, although pull request notifications are useful, developers are often overwhelmed by notifications: only a third of pull requests were actually merged. Through a survey, 62 developers indicated that their most significant concerns are breaking changes, understanding the implications of changes, and migration effort. The implications of our work suggests ways in which notifications can be improved to better align with developers’ expectations and the need for new mechanisms to reduce notification fatigue and improve confidence in automated pull requests.","2017-10","2021-05-18 16:30:19","2021-05-18 16:30:19","2021-05-18 16:30:19","84-94","","","","","","","","","","","IEEE","Urbana, IL","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\6ZLQH28G\Mirhosseini and Parnin - 2017 - Can automated pull requests encourage software dev.pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE)","","","","","","","","","","","","","","",""
"8M6NXWTY","journalArticle","2021","Abdellatif, Ahmad; Badran, Khaled; Costa, Diego; Shihab, Emad","A Comparison of Natural Language Understanding Platforms for Chatbots in Software Engineering","IEEE Transactions on Software Engineering","","0098-5589, 1939-3520, 2326-3881","10.1109/TSE.2021.3078384","https://ieeexplore.ieee.org/document/9426404/","","2021","2021-05-18 16:43:16","2021-05-18 16:43:16","2021-05-18 16:43:16","1-1","","","","","IIEEE Trans. Software Eng.","","","","","","","","","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\NH2GUTXU\abdellatif2020.pdf","","included; Snowballing; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"GTI76JYL","journalArticle","2021","Serban, Dragos; Golsteijn, Bart; Holdorp, Ralph; Serebrenik, Alexander","SAW-BOT: Proposing Fixes for Static Analysis Warnings with GitHub Suggestions","","","","","","In this experience report we present SAW-BOT, a bot proposing fixes for static analysis warnings. The bot has been evaluated with five professional software developers by means of a Wizard of Oz experiment, semi-structured interviews and the mTAM questionnaire. We have observed that developers prefer GitHub suggestions to two baseline operation modes. Our study indicates that GitHub suggestions are a viable mechanism for implementing bots proposing fixes for static analysis warnings.","2021","2021-05-28 05:22:49","2021-05-30 09:09:52","","5","","","","","","","","","","","","","en","","","","","Zotero","","","","C:\Users\sant_si\Zotero\storage\BA6WQ6R3\Serban et al. - SAW-BOT Proposing Fixes for Static Analysis Warni.pdf","","included; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"KI6VKXWB","journalArticle","2020","Zhang, Neng; Huang, Qiao; Xia, Xin; Zou, Ying; Lo, David; Xing, Zhenchang","Chatbot4QR: Interactive Query Refinement for Technical Question Retrieval","IEEE Transactions on Software Engineering","","0098-5589, 1939-3520, 2326-3881","10.1109/TSE.2020.3016006","https://ieeexplore.ieee.org/document/9165927/","Technical Q&A sites (e.g., Stack Overflow (SO)) are important resources for developers to search for knowledge about technical problems. Search engines provided in Q&A sites and information retrieval approaches (e.g., word embedding-based) have limited capabilities to retrieve relevant questions when queries are imprecisely specified, such as missing important technical details (e.g., the user’s preferred programming languages). Although many automatic query expansion approaches have been proposed to improve the quality of queries by expanding queries with relevant terms, the information missed in a query is not identified. Moreover, without user involvement, the existing query expansion approaches may introduce unexpected terms and lead to undesired results. In this paper, we propose an interactive query refinement approach for question retrieval, named Chatbot4QR, which can assist users in recognizing and clarifying technical details missed in queries and thus retrieve more relevant questions for users. Chatbot4QR automatically detects missing technical details in a query and generates several clarification questions (CQs) to interact with the user to capture their overlooked technical details. To ensure the accuracy of CQs, we design a heuristic-based approach for CQ generation after building two kinds of technical knowledge bases: a manually categorized result of 1,841 technical tags in SO and the multiple version-frequency information of the tags. We develop a Chatbot4QR prototype that uses 1.88 million SO questions as the repository for question retrieval. To evaluate Chatbot4QR, we conduct six user studies with 25 participants on 50 experimental queries. The results are as follows. (1) On average 60.8% of the CQs generated for a query are useful for helping the participants recognize missing technical details. (2) Chatbot4QR can rapidly respond to the participants after receiving a query within approximately 1.3 seconds. (3) The refined queries contribute to retrieving more relevant SO questions than nine baseline approaches. For more than 70% of the participants who have preferred techniques on the query tasks, Chatbot4QR significantly outperforms the state-of-the-art word embedding-based retrieval approach with an improvement of at least 54.6% in terms of two measurements: Pre@k and NDCG@k. (4) For 48%-88% of the assigned query tasks, the participants obtain more desired results after interacting with Chatbot4QR than directly searching from Web search engines (e.g., the SO search engine and Google) using the original queries.","2020","2021-05-28 05:22:52","2021-05-28 05:22:52","2021-05-28 05:22:52","1-1","","","","","IIEEE Trans. Software Eng.","Chatbot4QR","","","","","","","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\SR5CML45\Zhang et al. - 2020 - Chatbot4QR Interactive Query Refinement for Techn.pdf","","included; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","",""
"LVQ4LG2V","conferencePaper","2021","Chatterjee, Preetha; Damevski, Kostadin; Pollock, Lori","Automatic Extraction of Opinion-based Q&A from Online Developer Chats","2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE)","978-1-66540-296-5","","10.1109/ICSE43902.2021.00115","https://ieeexplore.ieee.org/document/9402078/","Virtual conversational assistants designed specifically for software engineers could have a huge impact on the time it takes for software engineers to get help. Research efforts are focusing on virtual assistants that support specific software development tasks such as bug repair and pair programming. In this paper, we study the use of online chat platforms as a resource towards collecting developer opinions that could potentially help in building opinion Q&A systems, as a specialized instance of virtual assistants and chatbots for software engineers. Opinion Q&A has a stronger presence in chats than in other developer communications, thus mining them can provide a valuable resource for developers in quickly getting insight about a specific development topic (e.g., What is the best Java library for parsing JSON?). We address the problem of opinion Q&A extraction by developing automatic identification of opinion-asking questions and extraction of participants’ answers from public online developer chats. We evaluate our automatic approaches on chats spanning six programming communities and two platforms. Our results show that a heuristic approach to opinion-asking questions works well (.87 precision), and a deep learning approach customized to the software domain outperforms heuristics-based, machine-learning-based and deep learning for answer extraction in community question answering.","2021-05","2021-05-28 05:22:54","2021-05-28 08:10:13","2021-05-28 05:22:54","1260-1272","","","","","","","","","","","IEEE","Madrid, Spain","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\2M8PKQ57\Chatterjee et al. - 2021 - Automatic Extraction of Opinion-based Q&A from Onl.pdf","","included; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE)","","","","","","","","","","","","","","",""
"2U84K9HH","conferencePaper","2020","Khanan, Chaiyakarn; Luewichana, Worawit; Pruktharathikoon, Krissakorn; Jiarpakdee, Jirayus; Tantithamthavorn, Chakkrit; Choetkiertikul, Morakot; Ragkhitwetsagul, Chaiyong; Sunetnanta, Thanwadee","JITBot: an explainable just-in-time defect prediction bot","Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering","978-1-4503-6768-4","","10.1145/3324884.3415295","https://dl.acm.org/doi/10.1145/3324884.3415295","Just-In-Time (JIT) defect prediction is a classification model that is trained using historical data to predict bug-introducing changes. However, recent studies raised concerns related to the explainability of the predictions of many software analytics applications (i.e., practitioners do not understand why commits are risky and how to improve them). In addition, the adoption of Just-In-Time defect prediction is still limited due to a lack of integration into CI/CD pipelines and modern software development platforms (e.g., GitHub). In this paper, we present an explainable Just-In-Time defect prediction framework to automatically generate feedback to developers by providing the riskiness of each commit, explaining why such commit is risky, and suggesting risk mitigation plans. The proposed framework is integrated into the GitHub CI/CD pipeline as a GitHub application to continuously monitor and analyse a stream of commits in many GitHub repositories. Finally, we discuss the usage scenarios and their implications to practitioners. The VDO demonstration is available at https://jitbot-tool.github.io/.","2020-12-21","2021-05-28 05:22:56","2021-05-28 05:22:56","2021-05-28 05:22:56","1336-1339","","","","","","JITBot","","","","","ACM","Virtual Event Australia","en","","","","","DOI.org (Crossref)","","","","C:\Users\sant_si\Zotero\storage\Q52YL8B5\Khanan et al. - 2020 - JITBot an explainable just-in-time defect predict.pdf","","included; botse; repo","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","","ASE '20: 35th IEEE/ACM International Conference on Automated Software Engineering","","","","","","","","","","","","","","",""