Quantitative partial equivalence analysis quantifies behavioral differences between original and patched programs via symbolic analysis and a range-based heuristic for numerical domains.
Meyer, Thomas Fritz, Gail C
6 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 6representative citing papers
EditFlow reconstructs temporal developer editing flows from code changes to benchmark and optimize AI code edit recommenders so they align with natural incremental reasoning rather than static snapshots.
SSA harness matches frontier model pass@1 scores on agent benchmarks and 138k trajectory analysis in code state-spaces shows model-specific differences in edit frequency, testing activity, and phase transitions.
Mixed-methods study adapting UTAUT2 shows individual-level perceptions predict continued GenAI use in Italian SME developers (R²=0.647) while social and organisational factors do not.
Longitudinal surveys show AI coding assistants reduce time on code writing but increase supervisory verification tasks, with stable productivity perceptions yet rising reports of worsened developer experience.
MultiMend augments buggy function context via retrieval and generates multi-hunk patches, fixing 2,227 of 5,501 bugs across six benchmarks in four languages.
citing papers explorer
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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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EditFlow: Benchmarking and Optimizing Code Edit Recommendation Systems via Reconstruction of Developer Flows
EditFlow reconstructs temporal developer editing flows from code changes to benchmark and optimize AI code edit recommenders so they align with natural incremental reasoning rather than static snapshots.
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Dissecting model behavior through agent trajectories
SSA harness matches frontier model pass@1 scores on agent benchmarks and 138k trajectory analysis in code state-spaces shows model-specific differences in edit frequency, testing activity, and phase transitions.
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From Early Adoption to Sustained Use: Understanding GenAI Usage Among Software Developers in Italian SMEs
Mixed-methods study adapting UTAUT2 shows individual-level perceptions predict continued GenAI use in Italian SME developers (R²=0.647) while social and organisational factors do not.
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The Impact of AI Coding Assistants on Software Engineering: A Longitudinal Study
Longitudinal surveys show AI coding assistants reduce time on code writing but increase supervisory verification tasks, with stable productivity perceptions yet rising reports of worsened developer experience.
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MultiMend: Multilingual Program Repair with Context Augmentation and Multi-Hunk Patch Generation
MultiMend augments buggy function context via retrieval and generates multi-hunk patches, fixing 2,227 of 5,501 bugs across six benchmarks in four languages.