Software fault localisation: a systematic mapping study

Software fault localisation (SFL) is recognised to be one of the most tedious, costly, and critical activities in program debugging. Due to the increase in software complexity, there is a huge interest in advanced SFL techniques that aid software engineers in locating program bugs. This interest pav...

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Published in:IET software Vol. 13; no. 1; pp. 60 - 74
Main Authors: Zakari, Abubakar, Lee, Sai Peck, Alam, Khubaib Amjad, Ahmad, Rodina
Format: Journal Article
Language:English
Published: The Institution of Engineering and Technology 01.02.2019
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ISSN:1751-8806, 1751-8814, 1751-8814
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Abstract Software fault localisation (SFL) is recognised to be one of the most tedious, costly, and critical activities in program debugging. Due to the increase in software complexity, there is a huge interest in advanced SFL techniques that aid software engineers in locating program bugs. This interest paves a way to the existence of a large amount of literature in the SFL research domain. This study aims to investigate the overall research productivity, demographics, and trends shaping the landscape of SFL research domain. The research also aims to classify existing fault localisation techniques and identify trends in the field of study. Accordingly, a systematic mapping study of 273 primary selected studies is conducted with the adoption of an evidence-based systematic methodology to ensure coverage of all relevant studies. The results of this systematic mapping study show that SFL research domain is gaining more attention since 2010, with an increasing number of publications per year. Three main research facets were identified, i.e. validation research, evaluation research, and solution research, with solution research type getting more attention. Hence, various contribution facets were identified as well. In totality, general demographics of SFL research domain were highlighted and discussed.
AbstractList Software fault localisation (SFL) is recognised to be one of the most tedious, costly, and critical activities in program debugging. Due to the increase in software complexity, there is a huge interest in advanced SFL techniques that aid software engineers in locating program bugs. This interest paves a way to the existence of a large amount of literature in the SFL research domain. This study aims to investigate the overall research productivity, demographics, and trends shaping the landscape of SFL research domain. The research also aims to classify existing fault localisation techniques and identify trends in the field of study. Accordingly, a systematic mapping study of 273 primary selected studies is conducted with the adoption of an evidence‐based systematic methodology to ensure coverage of all relevant studies. The results of this systematic mapping study show that SFL research domain is gaining more attention since 2010, with an increasing number of publications per year. Three main research facets were identified, i.e. validation research, evaluation research, and solution research, with solution research type getting more attention. Hence, various contribution facets were identified as well. In totality, general demographics of SFL research domain were highlighted and discussed.
Author Ahmad, Rodina
Zakari, Abubakar
Alam, Khubaib Amjad
Lee, Sai Peck
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Issue 1
Keywords program debugging
software fault localisation
software engineers
software complexity
SFL research domain
software engineering
software maintenance
software fault tolerance
SFL techniques
fault localisation techniques
Language English
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Snippet Software fault localisation (SFL) is recognised to be one of the most tedious, costly, and critical activities in program debugging. Due to the increase in...
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StartPage 60
SubjectTerms fault localisation techniques
program debugging
Review Article
SFL research domain
SFL techniques
software complexity
software engineering
software engineers
software fault localisation
software fault tolerance
software maintenance
Title Software fault localisation: a systematic mapping study
URI http://digital-library.theiet.org/content/journals/10.1049/iet-sen.2018.5137
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Volume 13
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