Behavior-Informed Algorithms for Automatic Documentation Generation

摘要

Programmers rely on source code documentation to quickly understand what the source code does and how they would use it. Unfortunately, many programmers do not have the time to write and maintain source code documentation. A solution to this problem is to document and summarize source code automatically. Unfortunately, research efforts to automatically generate documentation have stalled recently because the research community does not know exactly what a summary of source code should include. To solve this problem, my overall strategy is to study programmer behavior in order to write algorithms that mimic that behavior. I have four key areas of work in which I execute that strategy: First, I determine what areas of code programmers read when they create documentation. Second, I find patterns in programmers' eye movements when they reading code. Third, I use recordings of developer-client meetings to extract user story information. Finally, I propose to conduct a grounded theory study at a medium sized software company to determine whether factors outside the code influence source code summarization. This paper discusses the foundation for my career in the software engineering community, and I seek the community's advice.