Developing Fault-Prediction Models: What the research can show industry

Tracy Hall; Sarah Beecham; David Bowes; David Gray; Steve Counsell

doi:10.1109/MS.2011.138

Developing Fault-Prediction Models: What the research can show industry

Tracy Hall, Sarah Beecham, David Bowes, David Gray, Steve Counsell

Research output: Contribution to journal › Article › peer-review

15 Citations (Scopus)

Abstract

A systematic review of the research literature on fault-prediction models from 2000 through 2010 identified 36 studies that sufficiently defined their models and development context and methodology. The authors quantitatively analyzed 19 of these studies and the 206 models they presented. They identified several key features to help industry software developers build or optimize fault-prediction models suitable to their specific contexts.

Original language	English
Pages (from-to)	96-99
Number of pages	4
Journal	IEEE Software
Volume	28
Issue number	6
DOIs	https://doi.org/10.1109/MS.2011.138
Publication status	Published - 2011

Keywords

fault-prediction models

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10.1109/MS.2011.138

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abstract = "A systematic review of the research literature on fault-prediction models from 2000 through 2010 identified 36 studies that sufficiently defined their models and development context and methodology. The authors quantitatively analyzed 19 of these studies and the 206 models they presented. They identified several key features to help industry software developers build or optimize fault-prediction models suitable to their specific contexts.",

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Developing Fault-Prediction Models: What the research can show industry

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Keywords

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