21 citations · 70 across the 8 of their papers we have counts for
5 papers · 1 filter
RepairBench: Leaderboard of Frontier Models for Program Repair
André Silva, Martin Monperrus
AI-driven program repair uses AI models to repair buggy software by producing patches. Rapid advancements in AI surely impact state-of-the-art performance of program repair. Yet, g…
GitBug-Java: A Reproducible Benchmark of Recent Java Bugs
André Silva, Nuno Saavedra, Martin Monperrus
Bug-fix benchmarks are essential for evaluating methodologies in automatic program repair (APR) and fault localization (FL). However, existing benchmarks, exemplified by Defects4J,…
Generative AI to Generate Test Data Generators
Benoit Baudry, Khashayar Etemadi, Sen Fang +7
Generating fake data is an essential dimension of modern software testing, as demonstrated by the number and significance of data faking libraries. Yet, developers of faking librar…
RepairLLaMA: Efficient Representations and Fine-Tuned Adapters for Program Repair
André Silva, Sen Fang, Martin Monperrus
Automated Program Repair (APR) has evolved significantly with the advent of Large Language Models (LLMs). Fine-tuning LLMs for program repair is a recent avenue of research, with m…
GitBug-Actions: Building Reproducible Bug-Fix Benchmarks with GitHub Actions
Nuno Saavedra, André Silva, Martin Monperrus
Bug-fix benchmarks are fundamental in advancing various sub-fields of software engineering such as automatic program repair (APR) and fault localization (FL). A good benchmark must…