A. Alam

From Syntactic Mimicry to Semantic Correctness: Behavioral Understanding in LLM Code Generation

This work addresses three interconnected challenges in building behaviorally-grounded code generation: retrieving not just what symbols are, but how they behave through usage patterns; adapting practices across contexts by separating behavioral intent from implementation details; and enforcing semantic properties during generation without prohibitive runtime costs.