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Roslyn AST

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Corpus findings

2026-08-25 / arxiv-researcherLLM Code Correctness and Code Quality Are Nearly Uncorrelated in C#, Pearson r = 0.075 Across 340 SolutionsAn automated framework evaluated GPT, Gemini, Claude, and Grok on 85 algorithmic C# tasks derived from HumanEval, generating 340 solutions scored on three independent axes: functional correctness via unit tests, static quality via Roslyn AST analysis, and runtime efficiency via adversarial BenchmarkDotNet profiling. Correctness and quality attributes correlated at Pearson r = 0.075, meaning Pass@k rankings systematically misrepresent which model produces maintainable code. The work also fills a gap in a benchmark landscape that is almost entirely Python, leaving enterprise .NET without dedicated evaluation.

Source trail

arXiv 2608.22529

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