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Rule-based detection of design patterns in program code

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Abstract

The process of understanding and reusing software is often time-consuming, especially in legacy code and open-source libraries. While some core code of open-source libraries may be well-documented, it is frequently the case that open-source libraries lack informative API documentation and reliable design information. As a result, the source code itself is often the sole reliable source of information for program understanding activities. In this article, we propose a reverse-engineering approach that can provide assistance during the process of understanding software through the automatic recovery of hidden design patterns in software libraries. Specifically, we use ontology formalism to represent the conceptual knowledge of the source code and semantic rules to capture the structures and behaviors of the design patterns in the libraries. Several software libraries were examined with this approach and the evaluation results show that effective and flexible detection of design patterns can be achieved without using hard-coded heuristics.

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Notes

  1. Although they have a few distinguishing features, we use the terms ‘library’, ‘framework’, and ‘software system’ interchangeably.

  2. http://protege.stanford.edu/.

  3. http://simile.mit.edu.

  4. http://www.w3.org/DesignIssues/Notation3.

  5. http://www.jhotdraw.org/.

  6. http://jena.apache.org/.

  7. http://www.junit.org.

  8. http://jrefactory.sourceforge.net/.

  9. The Mediator pattern is also supported but no results included since Semaptrec did not recover any pattern instances in these frameworks and other tools do not support this pattern.

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Authors and Affiliations

  1. Indiana University, Kokomo, IN, 46904, USA

    Awny Alnusair

  2. University of Wisconsin-Milwaukee, Milwaukee, WI, 53201, USA

    Tian Zhao

  3. University of Southern Indiana, Evansville, IN, 47712, USA

    Gongjun Yan

Authors
  1. Awny Alnusair
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  2. Tian Zhao
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  3. Gongjun Yan
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Corresponding author

Correspondence to Awny Alnusair.

Additional information

A. Alnusair was partially supported by the Indiana University fellowship research grant.

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Alnusair, A., Zhao, T. & Yan, G. Rule-based detection of design patterns in program code. Int J Softw Tools Technol Transfer 16, 315–334 (2014). https://doi.org/10.1007/s10009-013-0292-z

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