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Frontiers of Computer Science

, Volume 12, Issue 5, pp 908–922 | Cite as

Software design pattern mining using classification-based techniques

  • Ashish Kumar Dwivedi
  • Anand Tirkey
  • Santanu Kumar Rath
Research Article
  • 59 Downloads

Abstract

Design patterns are often used in the development of object-oriented software. It offers reusable abstract information that is helpful in solving recurring design problems. Detecting design patterns is beneficial to the comprehension and maintenance of object-oriented software systems. Several pattern detection techniques based on static analysis often encounter problems when detecting design patterns for identical structures of patterns. In this study, we attempt to detect software design patterns by using software metrics and classification-based techniques. Our study is conducted in two phases: creation of metrics-oriented dataset and detection of software design patterns. The datasets are prepared by using software metrics for the learning of classifiers. Then, pattern detection is performed by using classification-based techniques. To evaluate the proposed method, experiments are conducted using three open source software programs, JHotDraw, QuickUML, and JUnit, and the results are analyzed.

Keywords

design patterns design pattern mining machine learning techniques object-oriented metrics 

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Copyright information

© Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Ashish Kumar Dwivedi
    • 1
  • Anand Tirkey
    • 1
  • Santanu Kumar Rath
    • 1
  1. 1.Department of Computer Science and EngineeringNational Institute of TechnologyRourkelaIndia

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