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The improved dynamic slicing for spectrum-based fault localization
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 prog...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9575932/ https://www.ncbi.nlm.nih.gov/pubmed/36262143 http://dx.doi.org/10.7717/peerj-cs.1071 |
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author | Cao, Heling Wang, Fei Deng, Miaolei Li, Lei |
author_facet | Cao, Heling Wang, Fei Deng, Miaolei Li, Lei |
author_sort | Cao, Heling |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9575932 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95759322022-10-18 The improved dynamic slicing for spectrum-based fault localization Cao, Heling Wang, Fei Deng, Miaolei Li, Lei PeerJ Comput Sci Algorithms and Analysis of Algorithms 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. PeerJ Inc. 2022-09-07 /pmc/articles/PMC9575932/ /pubmed/36262143 http://dx.doi.org/10.7717/peerj-cs.1071 Text en © 2022 Cao et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited. |
spellingShingle | Algorithms and Analysis of Algorithms Cao, Heling Wang, Fei Deng, Miaolei Li, Lei The improved dynamic slicing for spectrum-based fault localization |
title | The improved dynamic slicing for spectrum-based fault localization |
title_full | The improved dynamic slicing for spectrum-based fault localization |
title_fullStr | The improved dynamic slicing for spectrum-based fault localization |
title_full_unstemmed | The improved dynamic slicing for spectrum-based fault localization |
title_short | The improved dynamic slicing for spectrum-based fault localization |
title_sort | improved dynamic slicing for spectrum-based fault localization |
topic | Algorithms and Analysis of Algorithms |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9575932/ https://www.ncbi.nlm.nih.gov/pubmed/36262143 http://dx.doi.org/10.7717/peerj-cs.1071 |
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