A systematic review of machine learning techniques for software fault prediction

- Reviews studies from 1991-2013 to assess application of ML techniques for SFP.
- Identifies seven categories of the ML techniques.
- Identifies 64 studies to answer the established research questions.
- Selects primary studies according to the quality assessment of the studies.
- Systematic literature review performs the following:
- Summarize ML techniques for SFP models.
- Assess performance accuracy and capability of ML techniques for constructing SFP models.
- Provide comparison between the ML and statistical techniques.
- Provide comparison of performance accuracy of different ML techniques.
- Summarize the strength and weakness of the ML techniques.
- Provides future guidelines to software practitioners and researchers.