articleIEEE Transactions on Software EngineeringOct 11, 2011Closed access

A Systematic Literature Review on Fault Prediction Performance in Software Engineering

Brunel University of London · University of Limerick · +1 more institution

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Abstract

Background

The accurate prediction of where faults are likely to occur in code can help direct test effort, reduce costs, and improve the quality of software.

Objective

We investigate how the context of models, the independent variables used, and the modeling techniques applied influence the performance of fault prediction models. Method: We used a systematic literature review to identify 208 fault prediction studies published from January 2000 to December 2010. We synthesize the quantitative and qualitative results of 36 studies which report sufficient contextual and methodological information according to the criteria we develop and apply.

Citation impact

1,139
total citations
FWCI
93.97
Percentile
100%
References
250
Citations per year

Authors

5

Topics & keywords

Keywords
  • Computer science
  • Predictive modelling
  • Data mining
  • Software quality
  • Context (archaeology)
  • Machine learning
  • Feature selection
  • Logistic regression
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Funding