Image de couverture de livre

Order Matters! An Empirical Study on Large Language Models' Input Order Bias in Software Fault Localization

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Rafi, Md Nakhla, Kim, Dong Jae, Chen, Tse-Hsun, Wang, Shaowei
Format:	Preprint
Publié:	2024
Sujets:	Software Engineering Artificial Intelligence Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

A Multi-Agent Approach to Fault Localization via Graph-Based Retrieval and Reflexion
par: Rafi, Md Nakhla, et autres
Publié: (2024)

Towards Better Graph Neural Network-based Fault Localization Through Enhanced Code Representation
par: Rafi, Md Nakhla, et autres
Publié: (2024)

Crash Report Enhancement with Large Language Models: An Empirical Study
par: Fahim, S M Farah Al, et autres
Publié: (2025)

Back to the Future! Studying Data Cleanness in Defects4J and its Impact on Fault Localization
par: Rafi, Md Nakhla, et autres
Publié: (2023)

SBEST: Spectrum-Based Fault Localization Without Fault-Triggering Tests
par: Rafi, Md Nakhla, et autres
Publié: (2024)

LLMParser: An Exploratory Study on Using Large Language Models for Log Parsing
par: Ma, Zeyang, et autres
Publié: (2024)

Evaluating Software Process Models for Multi-Agent Class-Level Code Generation
par: Shafin, Wasique Islam, et autres
Publié: (2025)

CI-Repair-Bench: A Repository-Aware Benchmark for Automated Patch Validation via CI Workflows
par: Muna, Rabeya Khatun, et autres
Publié: (2026)

LibreLog: Accurate and Efficient Unsupervised Log Parsing Using Open-Source Large Language Models
par: Ma, Zeyang, et autres
Publié: (2024)

Identifying Performance-Sensitive Configurations in Software Systems through Code Analysis with LLM Agents
par: Wang, Zehao, et autres
Publié: (2024)

SOEN-101: Code Generation by Emulating Software Process Models Using Large Language Model Agents
par: Lin, Feng, et autres
Publié: (2024)

Studying the Impact of Early Test Termination Due to Assertion Failure on Code Coverage and Spectrum-based Fault Localization
par: Uddin, Md. Ashraf, et autres
Publié: (2025)

RobuNFR: Evaluating the Robustness of Large Language Models on Non-Functional Requirements Aware Code Generation
par: Lin, Feng, et autres
Publié: (2025)

Towards Structured, State-Aware, and Execution-Grounded Reasoning for Software Engineering Agents
par: Tse-Hsun, et autres
Publié: (2026)

Studying and Benchmarking Large Language Models For Log Level Suggestion
par: Heng, Yi Wen, et autres
Publié: (2024)

Static Program Slicing Using Language Models With Dataflow-Aware Pretraining and Constrained Decoding
par: He, Pengfei, et autres
Publié: (2026)

SLICET5: Static Program Slicing using Language Models with Copy Mechanism and Constrained Decoding
par: He, Pengfei, et autres
Publié: (2025)

A Comprehensive Framework for Evaluating API-oriented Code Generation in Large Language Models
par: Wu, Yixi, et autres
Publié: (2024)

Empowering AIOps: Leveraging Large Language Models for IT Operations Management
par: Vitui, Arthur, et autres
Publié: (2025)

Large Language Models for Fault Localization: An Empirical Study
par: Xiao, YingJian, et autres
Publié: (2025)

CODEPROMPTZIP: Code-specific Prompt Compression for Retrieval-Augmented Generation in Coding Tasks with LMs
par: He, Pengfei, et autres
Publié: (2025)

ZS4C: Zero-Shot Synthesis of Compilable Code for Incomplete Code Snippets using LLMs
par: Kabir, Azmain, et autres
Publié: (2024)

An Empirical Study on the Characteristics of Database Access Bugs in Java Applications
par: Liu, Wei, et autres
Publié: (2024)

Agentic Software Engineering: Foundational Pillars and a Research Roadmap
par: Hassan, Ahmed E., et autres
Publié: (2025)

Evaluating the Effectiveness and Efficiency of Demonstration Retrievers in RAG for Coding Tasks
par: He, Pengfei, et autres
Publié: (2024)

AutoEmpirical: LLM-Based Automated Research for Empirical Software Fault Analysis
par: Yu, Jiongchi, et autres
Publié: (2025)

A Survey of Code Review Benchmarks and Evaluation Practices in Pre-LLM and LLM Era
par: Khan, Taufiqul Islam, et autres
Publié: (2026)

Data Mining-Based Techniques for Software Fault Localization
par: Cellier, Peggy, et autres
Publié: (2025)

Large Language Models for Mobile GUI Text Input Generation: An Empirical Study
par: Cui, Chenhui, et autres
Publié: (2024)

Bugs in Large Language Models Generated Code: An Empirical Study
par: Tambon, Florian, et autres
Publié: (2024)

When LLMs Lag Behind: Knowledge Conflicts from Evolving APIs in Code Generation
par: Ashik, Ahmed Nusayer, et autres
Publié: (2026)

An Empirical Study of Fault Localisation Techniques for Deep Learning
par: Humbatova, Nargiz, et autres
Publié: (2024)

Guidelines for Empirical Studies in Software Engineering involving Large Language Models
par: Baltes, Sebastian, et autres
Publié: (2025)

An Empirical Study on Capability of Large Language Models in Understanding Code Semantics
par: Nguyen, Thu-Trang, et autres
Publié: (2024)

On Rank Aggregating Test Prioritizations
par: Mondal, Shouvick, et autres
Publié: (2024)

An Empirical Study of Fault Localization in Python Programs
par: Rezaalipour, Mohammad, et autres
Publié: (2023)

Beyond Autoregression: An Empirical Study of Diffusion Large Language Models for Code Generation
par: Li, Chengze, et autres
Publié: (2025)

An Empirical Study of the Imbalance Issue in Software Vulnerability Detection
par: Guo, Yuejun, et autres
Publié: (2026)

Discovery of Timeline and Crowd Reaction of Software Vulnerability Disclosures
par: Heng, Yi Wen, et autres
Publié: (2024)

An Empirical Study on Self-correcting Large Language Models for Data Science Code Generation
par: Quoc, Thai Tang, et autres
Publié: (2024)