A systematic review of machine learning techniques for software fault prediction
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SLRs with single authors can be found in SE and other research areas.
“Despite its disadvantages, we can find SLRs with single authors in SE (Malhotra, 2015) and other research areas (Mitchell, 2011).”
From A software engineering perspective on engineering machine learning systems: State of the art and challenges (2021) · cites this paper as Malhotra, 2015
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Giray, G. (2021) · Journal of Systems and Software · doi:10.1016/j.jss.2021.111031 · Cited by 187 · see citing works
Finding better active learners for faster literature reviews
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- Authors
- Malhotra, R.
- Affiliations
- Delhi Technological University (IN)
- Corresponding author
- Malhotra, Ruchika
- ORCID
- Malhotra, Ruchika
- Venue
- Applied Soft Computing
- Publisher
- Elsevier BV
- Published
- 2015-02
- Volume
- 27
- Pages
- 504-518
- ISSN
- 1568-4946 (ISSN-L)
- OpenAlex
- W2026750231
- Cited by
- 620
- References
- 158
- Citations by year
- 2026: 24 · 2025: 36 · 2024: 49 · 2023: 78 · 2022: 72 · 2021: 88 · 2020: 71 · 2019: 71 · 2018: 65 · 2017: 35 · 2016: 23 · 2015: 8
- FWCI
- 8.72
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Applied Soft Computing (publishedVersion)
- Funders
- National Aeronautics and Space Administration
- Topics
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Physical Sciences › Computer Science › Software › Software Reliability and Analysis Research
- Physical Sciences › Computer Science › Software › Software Testing and Debugging Techniques
- Keywords
- software defect prediction, machine learning methods, software quality prediction
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