articleMay 1, 2010Closed access

An extensive comparison of bug prediction approaches

Università della Svizzera italiana · University of Chile

Indexed incrossref

Abstract

Reliably predicting software defects is one of software engineering's holy grails. Researchers have devised and implemented a plethora of bug prediction approaches varying in terms of accuracy, complexity and the input data they require. However, the absence of an established benchmark makes it hard, if not impossible, to compare approaches. We present a benchmark for defect prediction, in the form of a publicly available data set consisting of several software systems, and provide an extensive comparison of the explanative and predictive power of well-known bug prediction approaches, together with novel approaches we devised. Based on the results, we discuss the performance and stability of the approaches…

Citation impact

642
total citations
FWCI
50.67
Percentile
100%
References
34
Citations per year

Authors

3

Topics & keywords

Keywords
  • Benchmark (surveying)
  • Computer science
  • Software bug
  • Software
  • Set (abstract data type)
  • Data mining
  • Predictive modelling
  • Machine learning
No related works found for this paper.