PeerJ Computer Science (Sep 2022)

The improved dynamic slicing for spectrum-based fault localization

  • Heling Cao,
  • Fei Wang,
  • Miaolei Deng,
  • Lei Li

DOI
https://doi.org/10.7717/peerj-cs.1071
Journal volume & issue
Vol. 8
p. e1071

Abstract

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Background Spectrum-based Fault localization have proven to be useful in the process of software testing and debugging. However, how to improve the effectiveness of software fault localization has always been a research hot spot in the field of software engineering. Dynamic slicing can extract program dependencies under certain conditions. Thus, this technology is expected to benefit for locating fault. Methods We propose an improved dynamic slicing for spectrum-based fault localization under a general framework. We first obtain the dynamic slice of program execution. Secondly, we construct a mixed slice spectrum matrix from the dynamic slice of each test case and the corresponding test results. Finally, we compute the suspiciousness value of each statement in the mixed-slice spectram matrix. Results To verify the performance of our method, we conduct an empirical study on 15 widely used open-source programs. Experimental results show that our approach achieves significant improvement than the compared techniques. Conclusions Our approach can reduce approximately 1% to 17.79% of the average cost of code examined significantly.

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