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Research on Object-Oriented Design Defect Detection Method Based on Machine Learning

  • Yiming Wang
  • Tie FengEmail author
  • Yanfang Cheng
  • Haiyan Che
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1084)

Abstract

Design defects are one of the main reasons for the decline of software design quality. Effective detection of design defects plays an important role in improving software maintainability and scalability. On the basis of defining software design defects, according to C&K design metrics and heuristics, this paper extracts the relevant features of design defects. Based on classical machine learning methods, classifiers are trained for design defect, and candidate designs are classified by classifiers, so as to identify whether there is a design defect in the design. Experiments show that the method has high accuracy and recall rate in identifying design defects.

Keywords

Design defect detection Object-oriented metrics Feature extraction Machine learning Classifier 

Notes

Acknowledgments

At the end of this paper, I would like to thank the teachers and classmates who have contributed to this paper, and secondly to those who came to help me.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Yiming Wang
    • 1
  • Tie Feng
    • 2
    Email author
  • Yanfang Cheng
    • 1
  • Haiyan Che
    • 2
  1. 1.Department of SoftwareJilin UniversityChangchunChina
  2. 2.Department of Computer Science and TechnologyJilin UniversityChangchunChina

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