Automatic prediction of the severity of bugs using stack traces and categorical features-Reference-Cited by-同舟云学术

Automatic prediction of the severity of bugs using stack traces and categorical features

Published:2020-07 Issue: Volume:123 Page:106205
ISSN:0950-5849
Container-title:Information and Software Technology
language:en
Short-container-title:Information and Software Technology

Author:

Sabor Korosh Koochekian,Hamdaqa Mohammad,Hamou-Lhadj Abdelwahab

Publisher

Elsevier BV

Subject

Computer Science Applications,Information Systems,Software

Reference30 articles.

1. Is it a bug or an enhancement?: a text-based approach to classify change requests;Antoniol,2008

2. P. Bhattacharya, M. Iliofotou, I. Neamtiu, and M. Faloutsos. Graph-based analysis and prediction for software evolution. In Proceedings of the 34th International Conference on Software Engineering (ICSE '12). Piscataway, NJ, USA, 419–429.

3. What makes a good bug report?;Bettenburg,2008

4. Coping with duplicate bug reports in free/open source software projects;Davidson,2011

5. A new distance-weighted k nearest neighbor classifier;Gou;J. Inf. Comput. Sci.,2012

Cited by 29 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. What causes exceptions in machine learning applications? Mining machine learning-related stack traces on Stack Overflow;Empirical Software Engineering;2024-07-03

2. On the value of instance selection for bug resolution prediction performance;Journal of Software: Evolution and Process;2024-07-02

3. The Use of AI in Software Engineering: A Synthetic Knowledge Synthesis of the Recent Research Literature;Information;2024-06-14

4. A Machine Learning Approach for Classifying the Default Bug Severity Level;Arabian Journal for Science and Engineering;2024-05-13

5. Software bug severity and priority prediction using SMOTE and intuitionistic fuzzy similarity measure;Applied Soft Computing;2024-01