SZZ unleashed: an open implementation of the SZZ algorithm - featuring example usage in a study of just-in-time bug prediction for the Jenkins project-Reference-Cited by-同舟云学术

SZZ unleashed: an open implementation of the SZZ algorithm - featuring example usage in a study of just-in-time bug prediction for the Jenkins project

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 3rd ACM SIGSOFT International Workshop on Machine Learning Techniques for Software Quality Evaluation - MaLTeSQuE 2019
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Author:

Borg Markus¹,Svensson Oscar²,Berg Kristian²,Hansson Daniel³

Affiliation:

1. RISE SICS, Sweden

2. Lund University, Sweden

3. Verifyter, Sweden

Funder

ITEA3

Publisher

ACM Press

Reference27 articles.

1. K. Berg and O. Svensson. 2018. SZZ Unleashed: Bug Prediction on the Jenkins Core Repository (Open Source Implementations of Bug Prediction Tools on Commit Level). Msc Thesis, Lund University, Sweden.

2. G. Canfora, L. Cerulo, and M. Di Penta. 2007. Identifying Changed Source Code Lines from Version Repositories. In Proc. of the 4th International Workshop on Mining Software Repositories.

3. Y. Cavalcanti, P. Silveira Neto, I. Machado, T. Vale, E. Almeida, and S. Meira. 2014. Challenges and Opportunities for Software Change Request Repositories: A Systematic Mapping Study. Journal of Software: Evolution and Process 26, 7 (2014), 620–653.

4. J. Correia. 2017. old-szz. https://github.com/intelligentagents/old-szz

5. J. Czerwonka, R. Das, N. Nagappan, A. Tarvo, and A. Teterev. 2011. CRANE: Failure Prediction, Change Analysis and Test Prioritization in Practice âĂŞ Experiences from Windows. In Proc. of the 4th Conference on Software Testing, Verification and Validation. 357–366.

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