Quantitative partial equivalence analysis quantifies behavioral differences between original and patched programs via symbolic analysis and a range-based heuristic for numerical domains.
In: Proceedings of the 2012 International Symposium on Software Testing and Analysis
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ConCovUp uses static analysis to ground LLM test generation and backward tracing to produce concurrent test drivers that raise average shared-memory access pair coverage from 36.6% to 68.1% on nine real-world libraries.
A controlled eye-tracking study finds that code priority affects review time, cognitive load, and perceived quality but not reuse decisions, while author reputation changes visual attention patterns without altering performance or reuse choices.
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Quantitative Symbolic Patch Impact Analysis
Quantitative partial equivalence analysis quantifies behavioral differences between original and patched programs via symbolic analysis and a range-based heuristic for numerical domains.
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ConCovUp: Effective Agent-Based Test Driver Generation for Concurrency Testing
ConCovUp uses static analysis to ground LLM test generation and backward tracing to produce concurrent test drivers that raise average shared-memory access pair coverage from 36.6% to 68.1% on nine real-world libraries.
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An Eye for Trust: An Exploration of Developers' Trust Perceptions Through Urgency and Reputation
A controlled eye-tracking study finds that code priority affects review time, cognitive load, and perceived quality but not reuse decisions, while author reputation changes visual attention patterns without altering performance or reuse choices.