Data Mining Static Code Attributes to Learn Defect Predictors

  title={Data Mining Static Code Attributes to Learn Defect Predictors},
  author={Tim Menzies and Jeremy Greenwald and Art Frank},
  journal={IEEE Trans. Software Eng.},
Highly Influential
This paper has highly influenced 141 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 1,082 citations. REVIEW CITATIONS

From This Paper

Topics from this paper.


Publications citing this paper.
Showing 1-10 of 660 extracted citations

A Semi-supervised Approach to Software Defect Prediction

2014 IEEE 38th Annual Computer Software and Applications Conference • 2014
View 8 Excerpts
Highly Influenced

Reducing false alarms in software defect prediction by decision threshold optimization

2009 3rd International Symposium on Empirical Software Engineering and Measurement • 2009
View 13 Excerpts
Highly Influenced

Cross-Project and Within-Project Semisupervised Software Defect Prediction: A Unified Approach

IEEE Transactions on Reliability • 2018
View 6 Excerpts
Highly Influenced

A Large-Scale Study of the Impact of Feature Selection Techniques on Defect Classification Models

2017 IEEE/ACM 14th International Conference on Mining Software Repositories (MSR) • 2017
View 4 Excerpts
Highly Influenced

1,082 Citations

Citations per Year
Semantic Scholar estimates that this publication has 1,082 citations based on the available data.

See our FAQ for additional information.

Similar Papers

Loading similar papers…