6 papers · 1 filter
Retrieval-Oriented Code Representations in Agentic Bug Localization
Genevieve Caumartin, Tse-Hsun, Chen +1
LLM-based agents are increasingly being used to support software development, yet their performance in repository-level tasks depends on retrieving the right code context. Existing…
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…
Rethinking Code Performance Benchmarks for LLMs
Nhat Minh Le, Yisen Xu, Zhijie Wang +2
Many function-level performance benchmarks have been proposed to evaluate whether large language models (LLMs) can generate efficient programs. However, results on these benchmarks…
LogSemFuse: Semantic Evidence Fusion for Explainable Log Anomaly Detection
Hassan Jabri, Zeyang Ma, Zhijie Wang +1
Log anomaly detection is critical for reliability monitoring and failure diagnosis in modern software systems. Existing model-based detectors provide useful anomaly signals, but th…
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…
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…