Unverified50% confidenceFactExact time
SWE-type benchmarks are used to evaluate a model's ability to solve real software engineering problems, with problems usually drawn from real issues and PRs in open-source repositories, testing cross-file understanding and multi-step reasoning ability.
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50%
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Long-term
Relevance
10/14/2026
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Related Claims
UnverifiedThe Deep SWE test simulates a real software engineering environment, requiring AI to understand architecture, locate problems, iteratively modify code, and verify results through automated tests within an existing codebase.75% similarUnverifiedSWE-bench involves high-level capabilities such as cross-file dependency analysis, version compatibility judgment, and regression test passing, making it more reflective of real engineering scenarios than function-writing benchmarks such as HumanEval75% similarUnverifiedLong-horizon coding benchmarks (such as SWE-bench) evaluate a model's ability to handle repository-level tasks, including reading codebases, locating bugs, making cross-file modifications, and passing tests.74% similarUnverifiedSWE-bench相比HumanEval、MBPP等传统基准更贴近实际开发场景，考验模型对大型代码库的理解、跨文件依赖追踪和缺陷定位能力72% similar
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