Measuring the principal of defect debt

Author:

Akbarinasaji Shirin1,Bener Ayse Basar1,Erdem Atakan1

Affiliation:

1. Ryerson University, Toronto, ON, Canada

Publisher

ACM Press

Reference33 articles.

1. S. Akbarinasaji. Toward measuring defect debt and developing a recommender system for their prioritization. InProceedings of the 13th International Doctoral Symposium on Empirical Software Engineering, pages 1--6, 2015.

2. N. S. Altman. An introduction to kernel and nearest-neighbor nonparametric regression.The American Statistician, 46(3):175--185, 1992.

3. N. S. Alves, T. S. Mendes, M. G. de Mendonça, R. O. Spínola, F. Shull, and C. Seaman. Identification and management of technical debt: A systematic mapping study.Information and Software Technology, 70:100--121, 2016.

4. A. Ampatzoglou, A. Ampatzoglou, A. Chatzigeorgiou, and P. Avgeriou. The financial aspect of managing technical debt: A systematic literature review.Information and Software Technology, 64:52--73, 2015.

5. P. Anbalagan and M. Vouk. On predicting the time taken to correct bug reports in open source projects. InSoftware Maintenance, 2009. ICSM 2009. IEEE International Conference on, pages 523--526. IEEE, 2009.

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Ways of applying artificial intelligence in software engineering;Proceedings of the 6th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering;2018-05-28

2. From lasagna to spaghetti, a decision model to manage defect debt;Proceedings of the 2018 International Conference on Technical Debt;2018-05-27

3. Prioritizing lingering bugs;ACM SIGSOFT Software Engineering Notes;2018-03-28

4. An empirical assessment of technical debt practices in industry;Journal of Software: Evolution and Process;2017-08-25

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