Summarizing software artifacts: a case study of bug reports

TitleSummarizing software artifacts: a case study of bug reports
Publication TypeConference Paper
Year of Publication2010
AuthorsRastkar, Sarah, Murphy Gail C., and Murray Gabriel
Secondary TitleProceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1
Place PublishedNew York, NY, USA
ISBN Number978-1-60558-719-6
Keywordsbug reports, eclipse, gnome, human-centric software engineering, kde, machine learning, mozilla

Many software artifacts are created, maintained and evolved as part of a software development project. As software developers work on a project, they interact with existing project artifacts, performing such activities as reading previously filed bug reports in search of duplicate reports. These activities often require a developer to peruse a substantial amount of text. In this paper, we investigate whether it is possible to summarize software artifacts automatically and effectively so that developers could consult smaller summaries instead of entire artifacts. To provide focus to our investigation, we consider the generation of summaries for bug reports. We found that existing conversation-based generators can produce better results than random generators and that a generator trained specifically on bug reports can perform statistically better than existing conversation-based generators. We demonstrate that humans also find these generated summaries reasonable indicating that summaries might be used effectively for many tasks.