Classifying Code Comments in Java Open-Source Software Systems

Conference Paper (2017)
Author(s)

Luca Pascarella (TU Delft - Software Engineering)

Alberto Bacchelli (TU Delft - Software Engineering)

Research Group
Software Engineering
DOI related publication
https://doi.org/10.1109/MSR.2017.63
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Publication Year
2017
Language
English
Research Group
Software Engineering
Article number
7962372
Pages (from-to)
227-237
ISBN (electronic)
978-1-5386-1544-7
Event
MSR 2017 (2017-05-20 - 2017-05-21), Buenos Aires, Argentina
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Abstract

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.

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