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Samuel A.Ajila

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#artificial intelligence Review Sep 2026

Complexity-Aware Evaluation of LLM Comprehension

A complexity-aware framework for evaluating LLM code comprehension using cyclomatic complexity, nesting depth, branching factor, and Halstead volume demonstrates that complexity-aware evaluation provides a more diagnostic assessment of LLM code-comprehension reliability than aggregate accuracy alone.

Ali Mohammadi Esfahani, Nafiseh Kahani, Samuel A.Ajila · 0 citations

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