Fsoft-AIC/SWE-EVO
SWE-EVO: A Frontier Benchmark for Coding Agents in Autonomous Software Evolution Overview SWE-EVO is a benchmark designed to evaluate AI coding agents in autonomous software evolution tasks. Unlike benchmarks that focus on isolated coding problems, SWE-EVO simulates realistic scenarios in which agents must iteratively evolve complex codebases according to high-level software requirement specifications (SRS). Using versioned histories from real Python… See the full description on the dataset page: https://huggingface.co/datasets/Fsoft-AIC/SWE-EVO.
| Author / organization | Fsoft-AIC |
|---|---|
| License (as declared) | apache-2.0 |
| Downloads | 2.5K (as reported by Hugging Face) |
| Likes | 2 |
| Created | 22 December 2025 |
| Last updated at source | 24 December 2025 |
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- 16 Oct 2026 Description: SWE-EVO: A Frontier Benchmark for Coding Agents in Autonomous Software Evolution Overview SWE-EVO is a benchmark designed to evaluate AI coding agents in autonomous software evolution tasks. Unlike benchmarks that focus on isolated coding p → SWE-EVO: A Frontier Benchmark for Coding Agents in Autonomous Software Evolution Overview SWE-EVO is a benchmark designed to evaluate AI coding agents in autonomous software evolution tasks. Unlike benchmarks that focus on isolated coding p
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