FIESTA uses bandit algorithms to adaptively decide how many seeds and splits to run for each candidate model, focusing effort on promising ones while providing guarantees on selecting the optimal model.
A hitchhiker’s guide to statistical tests for assessing randomized algorithms in software engineering.Software Testing, Verification and Reliability, 24(3):219–250
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Noise from quantum hardware simulators significantly alters mutant detection distances, making equivalent mutants harder to separate from faults, with output-distribution metrics reaching 73.03% accuracy and 74.89% F1-score under device-specific thresholds.
MR-Scout extracts over 11,000 metamorphic-relation-encoded test cases from 701 OSS projects, codifies 97% of them as high-quality generators, and shows they raise line coverage by 13.52% and mutation score by 9.42% on programs that already have developer tests.
A research roadmap analyzing the current state of search-based software engineering with foundation models, outlining challenges and directions across three integration aspects.
citing papers explorer
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FIESTA: Fast IdEntification of State-of-The-Art models using adaptive bandit algorithms
FIESTA uses bandit algorithms to adaptively decide how many seeds and splits to run for each candidate model, focusing effort on promising ones while providing guarantees on selecting the optimal model.
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Robust Mutation Analysis of Quantum Programs Under Noise
Noise from quantum hardware simulators significantly alters mutant detection distances, making equivalent mutants harder to separate from faults, with output-distribution metrics reaching 73.03% accuracy and 74.89% F1-score under device-specific thresholds.
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MR-Scout: Automated Synthesis of Metamorphic Relations from Existing Test Cases
MR-Scout extracts over 11,000 metamorphic-relation-encoded test cases from 701 OSS projects, codifies 97% of them as high-quality generators, and shows they raise line coverage by 13.52% and mutation score by 9.42% on programs that already have developer tests.
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Search-Based Software Engineering and AI Foundation Models: Current Landscape and Future Roadmap
A research roadmap analyzing the current state of search-based software engineering with foundation models, outlining challenges and directions across three integration aspects.