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cs.SE2025
Crash Report Enhancement with Large Language Models: An Empirical Study
S M Farah Al Fahim, Md Nakhla Rafi, Zeyang Ma +3
Crash reports are central to software maintenance, yet many lack the diagnostic detail developers need to debug efficiently. We examine whether large language models can enhance cr…
cs.SE2025
RobuNFR: Evaluating the Robustness of Large Language Models on Non-Functional Requirements Aware Code Generation
Feng Lin, Dong Jae Kim, Zhenhao Li +3
When using LLMs to address Non-Functional Requirements (NFRs), developers may behave differently (e.g., expressing the same NFR in different words). Robust LLMs should output consi…