133 citations · 365 across the 73 of their papers we have counts for
8 papers · 1 filter
Syntactic Vs. Semantic similarity of Artificial and Real Faults in Mutation Testing Studies
Milos Ojdanic, Aayush Garg, Ahmed Khanfir +3
Fault seeding is typically used in controlled studies to evaluate and compare test techniques. Central to these techniques lies the hypothesis that artificially seeded faults invol…
A Qualitative Study on the Sources, Impacts, and Mitigation Strategies of Flaky Tests
Sarra Habchi, Guillaume Haben, Mike Papadakis +2
Test flakiness forms a major testing concern. Flaky tests manifest non-deterministic outcomes that cripple continuous integration and lead developers to investigate false alerts. I…
Robust Active Learning: Sample-Efficient Training of Robust Deep Learning Models
Yuejun Guo, Qiang Hu, Maxime Cordy +2
Active learning is an established technique to reduce the labeling cost to build high-quality machine learning models. A core component of active learning is the acquisition functi…
Cerebro: Static Subsuming Mutant Selection
Aayush Garg, Milos Ojdanic, Renzo Degiovanni +3
Mutation testing research has indicated that a major part of its application cost is due to the large number of low utility mutants that it introduces. Although previous research h…
Discerning Legitimate Failures From False Alerts: A Study of Chromium's Continuous Integration
Guillaume Haben, Sarra Habchi, Mike Papadakis +2
Flakiness is a major concern in Software testing. Flaky tests pass and fail for the same version of a program and mislead developers who spend time and resources investigating test…
Smells in System User Interactive Tests
Renaud Rwemalika, Sarra Habchi, Mike Papadakis +2
Test smells are known as bad development practices that reflect poor design and implementation choices in software tests. Over the last decade, test smells were heavily studied to…