Perception and Acceptance of an Autonomous Refactoring Bot

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.

[1]  Witold Pedrycz,et al.  A Case Study on the Impact of Refactoring on Quality and Productivity in an Agile Team , 2008, CEE-SET.

[2]  Miryung Kim,et al.  An empirical investigation into the role of API-level refactorings during software evolution , 2011, 2011 33rd International Conference on Software Engineering (ICSE).

[3]  Miryung Kim,et al.  A field study of refactoring challenges and benefits , 2012, SIGSOFT FSE.

[4]  Gabriele Bavota,et al.  When Does a Refactoring Induce Bugs? An Empirical Study , 2012, 2012 IEEE 12th International Working Conference on Source Code Analysis and Manipulation.

[5]  Aiko Fallas Yamashita,et al.  Do developers care about code smells? An exploratory survey , 2013, 2013 20th Working Conference on Reverse Engineering (WCRE).

[6]  David Westerman,et al.  Welcoming Our Robot Overlords: Initial Expectations About Interaction With a Robot , 2014 .

[7]  H. Markus,et al.  Social Psychology [Australia and New Zealand edition] , 2015 .

[8]  Ipek Ozkaya,et al.  Managing Technical Debt in Software Engineering (Dagstuhl Seminar 16162) , 2016, Dagstuhl Reports.

[9]  Serge Demeyer,et al.  Among the Machines: Human-Bot Interaction on Social Q&A Websites , 2016, CHI Extended Abstracts.

[10]  Emerson Murphy-Hill,et al.  Gender differences and bias in open source: pull request acceptance of women versus men , 2017, PeerJ Comput. Sci..

[11]  Mauricio A. Saca Refactoring improving the design of existing code , 2017, 2017 IEEE 37th Central America and Panama Convention (CONCAPAN XXXVII).

[12]  Bruno Mendes de Souza,et al.  The Power of Bots: Understanding Bots in OSS Projects , 2018 .

[13]  Alexander Serebrenik,et al.  Beyond the Code Itself: How Programmers Really Look at Pull Requests , 2019, 2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering in Society (ICSE-SEIS).

[14]  Marvin Wyrich,et al.  Towards an Autonomous Bot for Automatic Source Code Refactoring , 2019, 2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE).

[15]  Carlo A. Furia,et al.  Automatically Generating Fix Suggestions in Response to Static Code Analysis Warnings , 2019, 2019 19th International Working Conference on Source Code Analysis and Manipulation (SCAM).