DeepMutation
Author:
Affiliation:
1. Microsoft
2. William & Mary
3. Washington and Lee University
4. Università della Svizzera italiana (USI), Lugano, Switzerland
5. University of Sannio, Benevento, Italy
Funder
National Science Foundation
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3377812.3382146
Reference26 articles.
1. 2019. DeepMutation - GitHub. https://github.com/micheletufano/DeepMutation 2019. DeepMutation - GitHub. https://github.com/micheletufano/DeepMutation
2. Using Mutation Analysis for Assessing and Comparing Testing Coverage Criteria
3. Assessing and improving state-based class testing: a series of experiments
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1. Equivalent Mutants in the Wild: Identifying and Efficiently Suppressing Equivalent Mutants for Java Programs;Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis;2024-09-11
2. Benchmarking Automated Program Repair: An Extensive Study on Both Real-World and Artificial Bugs;Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis;2024-09-11
3. Neural-MBFL: Improving Mutation-Based Fault Localization by Neural Mutation;2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC);2024-07-02
4. Syntactic Versus Semantic Similarity of Artificial and Real Faults in Mutation Testing Studies;IEEE Transactions on Software Engineering;2023-07
5. On Comparing Mutation Testing Tools through Learning-based Mutant Selection;2023 IEEE/ACM International Conference on Automation of Software Test (AST);2023-05
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