Warning-Introducing Commits vs Bug-Introducing Commits: A tool, statistical models, and a preliminary user study

摘要

This paper partially replicates prior works on building historical commits [1], commit risk modeling [2], and a comparison of statistical bug models and static bug finders [3].We examine 8 Maven-based projects with an average lifespan of 5.8 years. To historically build these projects across a total of 45k commits, we develop a series of techniques, such as flexibly selecting the version of a library that is closest to the commit date. We are able to build a per project average of 78.4% of all commits, a doubling in buildability compared to prior work. We also develop a git blame strategy to assign warnings even when a commit does not build.We run JLint and FindBugs and create a logistic regression model to predict if a commit that introduces a warning has higher odds of introducing a bug. The static bug finders model accounted for only 13% of the deviance, while the statistical bug model accounted for 19.5%. We had expected static bug finder warnings to improve the predictive power of models of bug introducing changes, but we clearly attained a negative result.To understand this negative result, we perform a preliminary user study of developers who introduced new warnings in 37 projects. We found that while warnings might not predict bugs, 53% and 21% of warnings in Findbugs and Jlint respectively are useful. We also study whether just-in-time warnings presentation on each commit impacted usefulness. We find that the later a warning is shown to a developer, the less useful it is perceived to be (a median of 11.5 days versus 23 days for non useful warnings).Based on our findings, we modify the existing COMMITGURU interface to add new warnings to the specific line in a changed file. The empirical study data [4] and WARNINGSGURU tool [5] are publicly available.