Authors
Priyan Vaithilingam, Elena L Glassman, Peter Groenwegen, Sumit Gulwani, Austin Z Henley, Rohan Malpani, David Pugh, Arjun Radhakrishna, Gustavo Soares, Joey Wang, Aaron Yim
Publication date
2023/5/14
Conference
2023 IEEE/ACM 45th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP)
Pages
185-195
Publisher
IEEE
Description
AI-driven code editor extensions such as Visual Studio IntelliCode and Github CoPilot have become extremely popular. These tools recommend inserting chunks of code, with the lines to be inserted presented inline at the current cursor location as gray text. In contrast to their popularity, other AI-driven code recommendation tools that suggest code changes (as opposed to code completions) have remained woefully underused. We conducted lab studies at Microsoft to understand this disparity and found one major cause: discoverability. Code change suggestions are hard to surface through bold, inline interfaces and hence, developers often do not even notice them.Towards a systematic understanding of code change interfaces, we performed a thorough design exploration for various categories of code changes: additive single-line changes, single-line changes, and multi-line changes. Overall, we explored 19 …
Total citations
Scholar articles