7 papers
Bug Report Specification Refinement with Trajectory Guidance for Automated Program Repair
S M Farah Al Fahim, Md Nakhla Rafi, Md Ahasanuzzaman +5
Bug reports serve as task specifications for repository-level automated program repair (APR) agents, but they often describe only the observed failure and omit repair-relevant info…
Order Matters! An Empirical Study on Large Language Models' Input Order Bias in Software Fault Localization
Md Nakhla Rafi, Dong Jae Kim, Tse-Hsun Chen +1
Large Language Models (LLMs) show great promise in software engineering tasks like Fault Localization (FL) and Automatic Program Repair (APR). This study investigates the impact of…
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…
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…
A Multi-Agent Approach to Fault Localization via Graph-Based Retrieval and Reflexion
Md Nakhla Rafi, Dong Jae Kim, Tse-Hsun Chen +1
Identifying and resolving software faults remains a challenging and resource-intensive process. Traditional fault localization techniques, such as Spectrum-Based Fault Localization…
SOEN-101: Code Generation by Emulating Software Process Models Using Large Language Model Agents
Feng Lin, Dong Jae Kim, Tse-Husn +1
Software process models are essential to facilitate collaboration and communication among software teams to solve complex development tasks. Inspired by these software engineering…