Generalizable Characterization of LLM Behavior
Characterize which properties of large language model behavior in software engineering are generalizable across model generations rather than transient capability gaps.
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Whether newer and more capable LLMs exhibit similar sensitivity to requirement smells remains an open empirical question.
Separating generalizable characteristics of LLM behavior from transient capability gaps remains an open methodological challenge.
How violation profiles differ across builders is a further question.
Our results might however not generalize to stronger models (that might have stronger capabilities to detect faults). However, we believe that our results are a fundamental consequence of the design of LLM-generated regression testing and the stronger capabilities of larger models to follow instructions might amplify our results. We leave this evaluation open for future research.