Software Fault Prediction is a software engineering methodology that employs computational models to identify the likelihood of faults in software modules prior to testing, distinguished by its reliance on historical metrics and statistical or machine learning techniques to forecast defect-prone components.
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Institutions
Publications per year
2017–2026
687
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2.9K
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34
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Florida Atlantic University
Boca Raton, United States
34 h-index
124 publications
7.2K citations
Wuhan University
Wuhan, China
29 h-index
127 publications
10.9K citations
Queen's University
Kingston, Canada
25 h-index
55 publications
9.1K citations
Nanjing University
Nanjing, China
25 h-index
134 publications
9K citations
West Virginia University
Morgantown, United States
24 h-index
72 publications
9.1K citations
Beihang University
Beijing, China
22 h-index
84 publications
3.8K citations
City University of Hong Kong
Hong Kong, Hong Kong
22 h-index
54 publications
3.8K citations
Microsoft (United States)
Redmond, United States
21 h-index
37 publications
9.2K citations
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- IEEE Transactions on Software Engineering
TSE · 69 publications · 17.8K citations
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- Information and Software Technology
60 publications · 6.2K citations
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- Journal of Systems and Software
JSS · 47 publications · 4.5K citations
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- Empirical Software Engineering
38 publications · 4.6K citations
30
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- IEEE Transactions on Reliability
35 publications · 2.8K citations
28
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