Simultaneous Localization of Software Faults Based on Complex Network Theory

Effective debugging is necessary for producing high quality and reliable software. Fault localization plays a vital role in the debugging process. However, fault localization is the most tedious and expensive activity in program debugging, as such, effective fault localization techniques that can id...

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Main Authors: Zakari, Abubakar, Lee, Sai Peck, Chong, Chun Yong
Format: Article
Published: Institute of Electrical and Electronics Engineers 2018
Subjects:
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author Zakari, Abubakar
Lee, Sai Peck
Chong, Chun Yong
author_facet Zakari, Abubakar
Lee, Sai Peck
Chong, Chun Yong
author_sort Zakari, Abubakar
collection UM
description Effective debugging is necessary for producing high quality and reliable software. Fault localization plays a vital role in the debugging process. However, fault localization is the most tedious and expensive activity in program debugging, as such, effective fault localization techniques that can identify the exact location of faults is eminent. Despite various fault localization techniques proposed, their application in multiple-fault programs is limited. The presence of multiple faults in a program reduces the efficacy of the existing fault localization techniques to locate faults effectively due to fault interference. Moreover, most of these techniques are unable to localize faults simultaneously. This has led researchers to adopt alternative approaches, such as one-fault-at-a-time debugging and parallel debugging. In this paper, we propose a novel fault localization technique based on complex network theory (FLCN) to improve localization effectiveness in programs with single-fault and multiple-fault and to aid developers to localize multiple faults simultaneously in a single diagnosis rank list. The proposed technique ranks faulty statements based on their behavioral abnormalities and distance between faulty statements in both passed and failed test executions. Two graph-based centrality measures are adopted for fault diagnosis, namely, degree centrality and closeness centrality and a new ranking formula is proposed. FLCN is evaluated across 14 subjects with both single-fault and multiple-fault programs. Our experimental results show that FLCN is more effective at locating faults when compared with existing state-of-the-art fault localization techniques with improvement of fault localization effectiveness in both single-fault and multiple-fault programs.
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spelling um.eprints-201882019-01-28T03:41:53Z http://eprints.um.edu.my/20188/ Simultaneous Localization of Software Faults Based on Complex Network Theory Zakari, Abubakar Lee, Sai Peck Chong, Chun Yong QA75 Electronic computers. Computer science Effective debugging is necessary for producing high quality and reliable software. Fault localization plays a vital role in the debugging process. However, fault localization is the most tedious and expensive activity in program debugging, as such, effective fault localization techniques that can identify the exact location of faults is eminent. Despite various fault localization techniques proposed, their application in multiple-fault programs is limited. The presence of multiple faults in a program reduces the efficacy of the existing fault localization techniques to locate faults effectively due to fault interference. Moreover, most of these techniques are unable to localize faults simultaneously. This has led researchers to adopt alternative approaches, such as one-fault-at-a-time debugging and parallel debugging. In this paper, we propose a novel fault localization technique based on complex network theory (FLCN) to improve localization effectiveness in programs with single-fault and multiple-fault and to aid developers to localize multiple faults simultaneously in a single diagnosis rank list. The proposed technique ranks faulty statements based on their behavioral abnormalities and distance between faulty statements in both passed and failed test executions. Two graph-based centrality measures are adopted for fault diagnosis, namely, degree centrality and closeness centrality and a new ranking formula is proposed. FLCN is evaluated across 14 subjects with both single-fault and multiple-fault programs. Our experimental results show that FLCN is more effective at locating faults when compared with existing state-of-the-art fault localization techniques with improvement of fault localization effectiveness in both single-fault and multiple-fault programs. Institute of Electrical and Electronics Engineers 2018 Article PeerReviewed Zakari, Abubakar and Lee, Sai Peck and Chong, Chun Yong (2018) Simultaneous Localization of Software Faults Based on Complex Network Theory. IEEE Access, 6. pp. 23990-24002. ISSN 2169-3536, DOI https://doi.org/10.1109/ACCESS.2018.2829541 <https://doi.org/10.1109/ACCESS.2018.2829541>. https://doi.org/10.1109/ACCESS.2018.2829541 doi:10.1109/ACCESS.2018.2829541
spellingShingle QA75 Electronic computers. Computer science
Zakari, Abubakar
Lee, Sai Peck
Chong, Chun Yong
Simultaneous Localization of Software Faults Based on Complex Network Theory
title Simultaneous Localization of Software Faults Based on Complex Network Theory
title_full Simultaneous Localization of Software Faults Based on Complex Network Theory
title_fullStr Simultaneous Localization of Software Faults Based on Complex Network Theory
title_full_unstemmed Simultaneous Localization of Software Faults Based on Complex Network Theory
title_short Simultaneous Localization of Software Faults Based on Complex Network Theory
title_sort simultaneous localization of software faults based on complex network theory
topic QA75 Electronic computers. Computer science
work_keys_str_mv AT zakariabubakar simultaneouslocalizationofsoftwarefaultsbasedoncomplexnetworktheory
AT leesaipeck simultaneouslocalizationofsoftwarefaultsbasedoncomplexnetworktheory
AT chongchunyong simultaneouslocalizationofsoftwarefaultsbasedoncomplexnetworktheory