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International Conference on Software Reuse

ICSR 2013: Safe and Secure Software Reuse pp 239–254Cite as

Mining Cohesive Domain Topics from Source Code

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 7925))

Abstract

Using topic models to mine domain topics from source code has been a promising way for developers to comprehend the functional concerns implemented in the source code of a software system. However, not all the topics mined from source code are domain topics that represent functional concerns of the software. Besides domain topics, other topics may represent cross-cutting concerns or other concerns. These topics are noises in the context of helping developers to comprehend the functional concerns. In this paper, we propose an approach to filter out noises and mine Cohesive Domain Topics (CDTs) from source code. A topic is a CDT if its associated words represent certain functional concern and its associated source code elements collaboratively implement the functional concern. Firstly, we propose a series of Filtering Heuristics to filter out programming related information in source code which may bring in noises. Then, we mine raw topics from source code using Latent Dirichlet Allocation. Finally, based on the structural relationships among the source code elements associated to a topic, we propose a novel metric called Topic Cohesion to identify CDTs from the raw topics. Experimental results on a set of open source software show that our approach can effectively filter out noises and obtain CDTs from source code.

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Author information

Authors and Affiliations

  1. Software Institute, School of Electronics Engineering and Computer Science, Peking University, Beijing, 100871, China

    Bing Xie, Meng Li, Jing Jin, Junfeng Zhao & Yanzhen Zou

  2. Key Laboratory of High Confidence Software Technologies, Ministry of Education, Beijing, 100871, China

    Bing Xie, Meng Li, Jing Jin, Junfeng Zhao & Yanzhen Zou

Authors
  1. Bing Xie
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  2. Meng Li
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  3. Jing Jin
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  4. Junfeng Zhao
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  5. Yanzhen Zou
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Editor information

Editors and Affiliations

  1. Intecs SpA, Via Umberto Forti 5, 56121, Pisa, Italy

    John Favaro

  2. Dipartimento di Automatica e Informatica, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129, Torino, Italy

    Maurizio Morisio

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Xie, B., Li, M., Jin, J., Zhao, J., Zou, Y. (2013). Mining Cohesive Domain Topics from Source Code. In: Favaro, J., Morisio, M. (eds) Safe and Secure Software Reuse. ICSR 2013. Lecture Notes in Computer Science, vol 7925. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38977-1_16

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  • DOI: https://doi.org/10.1007/978-3-642-38977-1_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38976-4

  • Online ISBN: 978-3-642-38977-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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