Princeton NLP group

Dataset

SWE-bench_Verified

Princeton NLP group

SWE-bench Verified is a subset of 500 samples from the SWE-bench test set, which have been human-validated for quality. SWE-bench is a dataset that tests systems’ ability to solve GitHub issues automatically. See this post for more details on the human-validation process. The dataset collects 500 test Issue-Pull Request pairs from popular Python repositories. Evaluation is performed by unit test verification using post-PR behavior as the reference solution. The original SWE-bench dataset was released as part of SWE-bench: Can Language Models Resolve Real-World GitHub Issues? Want to run inference now? This dataset only contains the problemstatement (i.e. issue text) and the basecommit which…

Dataset

SWE-bench_Lite

Princeton NLP group

SWE-bench Lite is subset of SWE-bench, a dataset that tests systems’ ability to solve GitHub issues automatically. The dataset collects 300 test Issue-Pull Request pairs from 11 popular Python. Evaluation is performed by unit test verification using post-PR behavior as the reference solution. The dataset was released as part of SWE-bench: Can Language Models Resolve Real-World GitHub Issues? This dataset only contains the problemstatement (i.e. issue text) and the basecommit which can represents the state of the codebase before the issue has been resolved. If you want to run inference using the "Oracle" or BM25 retrieval settings mentioned in the paper, consider the following datasets.…