Edit, But Verify: An Empirical Audit of Instructed Code-Editing Benchmarks

1. 1Identify existing code-editing benchmarks
2. 2Evaluate the relevance of these benchmarks to instructed code editing
3. 3Compare and contrast the two relevant benchmarks, CanItEdit and EDIT-Bench
4. 4Analyze the results to inform future improvements to instructed code-editing models and benchmarks

AI engineers and researchers benefit from this study as it provides insights into the current state of instructed code-editing benchmarks, helping them improve their models and evaluation methods. This information is also useful for software engineers who work with coding assistants and LLMs

💡 There is a lack of benchmarks for instructed code editing, and the existing ones have limitations, highlighting the need for further research and development in this area

💡 Only 2 benchmarks, CanItEdit & EDIT-Bench, evaluate instructed code editing. Researchers audit & compare them to improve coding assistants #AI #LLMs