184 citations · 455 across the 23 of their papers we have counts for
4 papers · 1 filter
Keeping Mutation Test Suites Consistent and Relevant with Long-Standing Mutants
Milos Ojdanic, Mike Papadakis, Mark Harman
Mutation testing has been demonstrated to be one of the most powerful fault-revealing tools in the tester's tool kit. Much previous work implicitly assumed it to be sufficient to r…
Fairness Testing: A Comprehensive Survey and Analysis of Trends
Zhenpeng Chen, Jie M. Zhang, Max Hort +2
Unfair behaviors of Machine Learning (ML) software have garnered increasing attention and concern among software engineers. To tackle this issue, extensive research has been dedica…
Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey
Max Hort, Zhenpeng Chen, Jie M. Zhang +2
This paper provides a comprehensive survey of bias mitigation methods for achieving fairness in Machine Learning (ML) models. We collect a total of 341 publications concerning bias…
A Comprehensive Empirical Study of Bias Mitigation Methods for Machine Learning Classifiers
Zhenpeng Chen, Jie M. Zhang, Federica Sarro +1
Software bias is an increasingly important operational concern for software engineers. We present a large-scale, comprehensive empirical study of 17 representative bias mitigation…