Spectrum-based multi-fault localization using Chaotic Genetic Algorithm

Ghosh, Debolina; Singh, Jagannath

doi:10.1016/j.infsof.2021.106512

Cited by 35 publications

(17 citation statements)

References 32 publications

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“…Also, it has been found that some SBFL formulas are more robust to multiple-faults and showed the best performance among all others. In general, pure SBFL is not always sufficient for effective fault localization in multi-fault programs [60], [61]. Other ways to address the issue of multiple bugs in a program is to design novel suspiciousness formulas as in [62], or to divide the failed test cases into different clusters.…”

Section: G Single and Multiple Bugsmentioning

confidence: 99%

A Survey of Challenges in Spectrum-Based Software Fault Localization

Sarhan

Beszedes

2022

IEEE Access

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In software debugging, fault localization is the most difficult, expensive, tedious, and timeconsuming task, particularly for large-scale software systems. This is due to the fact that it requires significant human participation and it is difficult to automate its sub-tasks. Therefore, there is a high demand for automatic fault localization techniques that can help software engineers effectively find the locations of faults with minimal human intervention. This has led to the proposal of implementing different types of such techniques. However, Spectrum Based Fault Localization (SBFL) is considered amongst the most prominent techniques in this respect due to its efficiency and effectiveness. In SBFL, the probability of each program element (e.g., statement, block, or function) being faulty is calculated based on the results of executing test cases and their corresponding code coverage information. However, SBFL techniques are not yet widely adopted in the industry. The rationale behind this is that they pose a number of issues and their performance is affected by several influential factors. For example, the characteristics of bugs, target programs, test suites, and supporting tools make their effectiveness differ dramatically from one case to another. There are massive studies on SBFL that cover its usage, formulas, performance, etc. So far, no dedicated survey points out comprehensively the issues of SBFL. In this paper, various SBFL challenges and issues have been identified, categorized, and discussed alongside many directions. Also, the paper raises awareness of the works being achieved to address the identified issues and suggests some potential solutions too.INDEX TERMS Program spectra, spectrum based fault localization, software testing, challenges and issues, survey.

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Section: G Single and Multiple Bugsmentioning

confidence: 99%

A Survey of Challenges in Spectrum-Based Software Fault Localization

Sarhan

Beszedes

2022

IEEE Access

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“…Simalarly, Dutta et al [16] proposed a modified Fisher's test-based statistical method that maked use of test execution results as well as statement coverage information to determine the suspiciousness of executable statements. Ghosh et al [17] used logistic mapping function to achieve chaotic sequence, which first calculated the suspiciousness score for each program statement and then assigned ranks according to that score. Considering that the interactive behaviors among software entities implied some fault patterns, Zhao et al [18] introduced the fault influence of interactive entities and developed a novel synthetical fault localization approach based on the software network.…”

Section: Spectrum-based Fault Localization (Sbfl)mentioning

confidence: 99%

An Innovative Framework for Coincidental Correctness Impacting on Fault Localization

Cao

Sun

2022

Symmetry

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An important research aspect of Spectrum-Based Fault Localization (SBFL) is the influence factors of the effectiveness of suspiciousness formulas from the perspective of symmetry. Coincidental correctness is one of the most important factors impacting the effectiveness of suspiciousness formulas. The influence of fault localization by coincidental correctness has attracted a large amount of research in the perspective of empirical study; however, it can hardly be considered as sufficiently comprehensive when there are a large number of the symmetrical suspiciousness formulas. Therefore, we first develop an innovative theoretical framework with function derivation investigating suspiciousness formulas impacted by coincidental correctness. We define three types of relations between formulas affected by coincidental correctness: namely, improved type, invariant type and uncertain type. We investigated 30 suspiciousness formulas using this framework and group them into three categories. Furthermore, we conduct an empirical study to verify the effectiveness of SBFL affected by coincidental correctness on four relatively large C programs. We proved that coincidental correctness has a positive effect on 23 out of these 30 formulas, no effect on 5 of them, and the effect on the remaining 2 of them depend on certain conditions. The experimental results show that the effectiveness of some suspiciousness formulas can be enhanced and that of some suspiciousness formulas remain unchanged.

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“…A framework for fault localization using a multivariate logistic regression model that combines static and dynamic features collected from the program being debugged by Ju et al (2020) . Ghosh & Singh (2021b) proposed an automated framework using chaos-based genetic algorithm for multi-fault localization based on SBFL technique.…”

Section: Related Workmentioning

confidence: 99%

The improved dynamic slicing for spectrum-based fault localization

Cao

Wang

Deng

et al. 2022

PeerJ Computer Science

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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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Spectrum-based multi-fault localization using Chaotic Genetic Algorithm

Cited by 35 publications

References 32 publications

A Survey of Challenges in Spectrum-Based Software Fault Localization

A Survey of Challenges in Spectrum-Based Software Fault Localization

An Innovative Framework for Coincidental Correctness Impacting on Fault Localization

The improved dynamic slicing for spectrum-based fault localization

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