SemVerBench: Benchmarking LLM Comprehension of Version-Constraint Resolution Semantics
Large language model (LLM) coding agents constantly decide whether a version satisfies a constraint such as ^1.2.3 or >=2.0,<3, yet their grasp of version-constraint semantics has never been measured directly. We introduce SemVerBench, the first benchmark of LLM version-constraint resolution semantics across three ecosystems (npm, PEP 440, Cargo): 240 machine-checkable items with unique answers, built author-neutrally from four balanced sources (each ecosystem's official test suite plus three frontier LLM proposers) and labeled by a non-circular two-implementation oracle. Evaluating six frontier models, we find systematic, predictable per-mechanism blind spots: a partial-comparator carry ...
| Authors | Qibai Chen, Zeming Liu |
|---|---|
| Primary category | cs.AI |
| Published | 10 September 2026 |
| Last updated at source | 14 September 2026 |
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