Mining Patterns in Source Code Using Tree Mining Algorithms

H.S. Pham, Siegfried Nijssen, Kim Mens, Dario Di Nucci, Tim Molderez, Coen De Roover, Johan Fabry, Vadim Zaytsev

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    2 Citations (Scopus)

    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.
    Original languageEnglish
    Title of host publicationDS 2019: Discovery Science
    DOIs
    Publication statusPublished - 2019

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