Code comments are a key software component containing information about the underlying implementation. Several studies have shown that code comments enhance the readability of the code. Nevertheless, not all the comments have the same goal and target audience. In this paper, we investigate how six diverse Java OSS projects use code comments, with the aim of understanding their purpose. Through our analysis, we produce a taxonomy of source code comments, subsequently, we investigate how often each category occur by manually classifying more than 2,000 code comments from the aforementioned projects. In addition, we conduct an initial evaluation on how to automatically classify code comments at line level into our taxonomy using machine learning, initial results are promising and suggest that an accurate classification is within reach.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE/ACM 14th International Conference on Mining Software Repositories, MSR 2017
PublisherIEEE Computer Society
Number of pages11
ISBN (Electronic)9781538615447
StatePublished - 29 Jun 2017
Event14th IEEE/ACM International Conference on Mining Software Repositories, - Buenos Aires, Argentina


Conference14th IEEE/ACM International Conference on Mining Software Repositories,
Abbreviated titleMSR 2017
CityBuenos Aires

    Research areas

  • comment taxonomy, software quality, source code comments

ID: 23948900