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Applying learning-based methods for recognizing design patterns

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Abstract

Recognizing design patterns in source code helps in improving the aspect of reusability and maintainability that play an essential role during analysis and design phases of software development process. Software patterns provide design-level documents, which are applied for the recurring design issues. Analysis of design patterns is often carried out by using forward engineering as well as reverse engineering. In this study, a reverse engineering approach has been applied for recognizing design patterns. The study is comprised of two phases such as preparation of requisite dataset based on object-oriented software metrics and recognition of design patterns. The first phase, i.e., dataset preparation, is carried out by various object-oriented metrics. Design pattern recognition is performed by using learning-based algorithms such as artificial neural network and logistic regression. The presented method is validated by using three case studies such as JRefactory, JUnit and Quaqua.

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Acknowledgements

Authors hereby acknowledge sincere thanks to the sponsor of the Web engineering and Cloud Computing Lab. Project sanctioned by FIST programme, Department of Science and Technology, Govt. of India.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Gayatri Vidya Parishad College of Engineering, Visakhapatnam, Andhra Pradesh, 530048, India

    Ashish Kumar Dwivedi

  2. Department of Computer Science and Engineering, National Institute of Technology, Rourkela, Odisha, 769008, India

    Anand Tirkey & Santanu Kumar Rath

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  1. Ashish Kumar Dwivedi
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  2. Anand Tirkey
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  3. Santanu Kumar Rath
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Correspondence to Ashish Kumar Dwivedi.

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Dwivedi, A.K., Tirkey, A. & Rath, S.K. Applying learning-based methods for recognizing design patterns. Innovations Syst Softw Eng 15, 87–100 (2019). https://doi.org/10.1007/s11334-019-00329-3

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