Locality-based security bug report identification via active learning

Author:

Ge Xiuting,Fang ChunrongORCID,Qian Meiyuan,Ge Yu,Qing Mingshuang

Publisher

Elsevier BV

Subject

Computer Science Applications,Information Systems,Software

Reference57 articles.

1. A survey on bug-report analysis;Zhang;Sci. China Inf. Sci.,2015

2. L. Chen, J. Yang, T. Lin, M. Hafiz, R2Fix: Automatically generating bug fixes from bug reports, in: Proceedings of the 2013 6th IEEE International Conference on Software Testing, 2013, pp. 282–291.

3. Automatic bug labeling using semantic information from LSI;Chawla,2014

4. Security impact ratings considered harmful lessons from history exploits can require extremely little evaluation;Arnold,2009

5. D. Behl, S. Handa, A. Arora, A bug Mining tool to identify and analyze security bugs using Naive Bayes and TF-IDF, in: Proceedings of the 2014 International Conference on Optimization, Reliabilty, and Information Technology, 2014, pp. 294–299.

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1. Why and how bug blocking relations are breakable: An empirical study on breakable blocking bugs;Information and Software Technology;2024-02

2. An Empirical Study of Class Rebalancing Methods for Actionable Warning Identification;IEEE Transactions on Reliability;2023-12

3. An Empirical Analysis of Rebalancing Methods for Security Issue Report Identification;2023 IEEE 28th Pacific Rim International Symposium on Dependable Computing (PRDC);2023-10-24

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