Abstract
Discovering regularities in source code is of great interest to software engineers, both in academia and in industry, as regularities can provide useful information to help in a variety of tasks such as code comprehension, code refactoring, and fault localisation. However, traditional pattern mining algorithms often find too many patterns of little use and hence are not suitable for discovering useful regularities. In this paper we propose FREQTALS, a new algorithm for mining patterns in source code based on the FREQT tree mining algorithm. First, we introduce several constraints that effectively enable us to find more useful patterns; then, we show how to efficiently include them in FREQT. To illustrate the usefulness of the constraints we carried out a case study in collaboration with software engineers, where we identified a number of interesting patterns in a repository of Java code.
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Acknowledgments
This work was conducted in the context of an industry-university research project between UCLouvain, Vrije Universiteit Brussel and Raincode Labs, funded by the Belgian Innoviris TeamUp project INTiMALS (2017-TEAM-UP-7).
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Pham, H.S. et al. (2019). Mining Patterns in Source Code Using Tree Mining Algorithms. In: Kralj Novak, P., Šmuc, T., Džeroski, S. (eds) Discovery Science. DS 2019. Lecture Notes in Computer Science(), vol 11828. Springer, Cham. https://doi.org/10.1007/978-3-030-33778-0_35
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DOI: https://doi.org/10.1007/978-3-030-33778-0_35
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