Autonomy Is An Acquired Taste: Exploring Developer Preferences for GitHub Bots
Software bots fulfill an important role in collective software development, and their adoption by developers promises increased productivity. Past research has identified that bots that communicate too often can irritate developers, which affects the utility of the bot. However, it is not clear what other properties of human-bot collaboration affect developers’ preferences, or what impact these properties might have. The main idea of this paper is to explore characteristics affecting developer preferences for interactions between humans and bots, in the context of GitHub pull requests. We carried out an exploratory sequential study with interviews and a subsequent vignette-based survey. We find developers generally prefer bots which are personable but show little autonomy, however more experienced developers tend to prefer more autonomous bots. Based on our empirical evidence we recommend bot developers increase configuration options for bots such that individual developers and projects can configure bots to best align with their own preferences and project culture.
Thu 18 MayDisplayed time zone: Hobart change
13:45 - 15:15 | Recommender systemsDEMO - Demonstrations / Technical Track / SEIP - Software Engineering in Practice / Journal-First Papers at Level G - Plenary Room 1 Chair(s): Kevin Moran George Mason University | ||
13:45 15mTalk | Autonomy Is An Acquired Taste: Exploring Developer Preferences for GitHub Bots Technical Track Amir Ghorbani University of Victoria, Nathan Cassee Eindhoven University of Technology, Derek Robinson University of Victoria, Adam Alami Aalborg University, Neil Ernst University of Victoria, Alexander Serebrenik Eindhoven University of Technology, Andrzej Wąsowski IT University of Copenhagen, Denmark Pre-print | ||
14:00 15mTalk | Flexible and Optimal Dependency Management via Max-SMT Technical Track Donald Pinckney Northeastern University, Federico Cassano Northeastern University, Arjun Guha Northeastern University and Roblox Research, Jonathan Bell Northeastern University, Massimiliano Culpo np-complete, S.r.l., Todd Gamblin Lawrence Livermore National Laboratory Pre-print | ||
14:15 15mTalk | Towards More Effective AI-assisted Programming: A Systematic Design Exploration to Improve Visual Studio IntelliCode's User Experience SEIP - Software Engineering in Practice Priyan Vaithilingam Harvard University, Elena Glassman Harvard University, Peter Groenwegen , Sumit Gulwani Microsoft, Austin Z. Henley Microsoft, Rohan Malpani , David Pugh , Arjun Radhakrishna Microsoft, Gustavo Soares Microsoft, Joey Wang , Aaron Yim | ||
14:30 7mTalk | DeepLog: Deep-Learning-Based Log Recommendation DEMO - Demonstrations Yang Zhang Hebei University of Science and Technology, Xiaosong Chang Hebei University of Science and Technology, Lining Fang Hebei University of Science and Technology, Yifan Lu Hebei University of Science and Technology | ||
14:37 7mTalk | ShellFusion: An Answer Generator for Shell Programming Tasks via Knowledge Fusion DEMO - Demonstrations Zhongqi Chen School of Software Engineering, Sun Yat-sen University, Neng Zhang School of Software Engineering, Sun Yat-sen University, Pengyue Si School of Software Engineering, Sun Yat-sen University, ChenQinde School of Software Engineering, Sun Yat-sen University, Chao Liu Chongqing University, Zibin Zheng School of Software Engineering, Sun Yat-sen University | ||
14:45 7mTalk | Revisiting, Benchmarking and Exploring API Recommendation: How Far are We? Journal-First Papers Yun Peng Chinese University of Hong Kong, Shuqing Li The Chinese University of Hong Kong, Wenwei Gu The Chinese University of Hong Kong, Yichen LI The Chinese University of Hong Kong, Wenxuan Wang The Chinese University of Hong Kong, Cuiyun Gao Harbin Institute of Technology, Michael Lyu The Chinese University of Hong Kong | ||
14:52 7mTalk | Semantically-enhanced Topic Recommendation Systems for Software Projects Journal-First Papers Maliheh Izadi Delft University of Technology, Mahtab Nejati University of Waterloo, Abbas Heydarnoori Bowling Green State University | ||
15:00 7mTalk | Code Librarian: A Software Package Recommendation System SEIP - Software Engineering in Practice Lili Tao JP Morgan Chase & Co, Alexandru-Petre Cazan JP Morgan Chase & Co, Senad Ibraimoski JP Morgan Chase & Co, Sean Moran JP Morgan Chase & Co |