Cover Image

FLIMs: Fault Localization Interference Mutants, Definition, Recognition and Mitigation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liu, Hengyuan, Li, Zheng, Wang, Donghua, Wu, Yankai, Chen, Xiang, Liu, Yong
Format:	Preprint
Published:	2025
Subjects:	Software Engineering
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

MBFL-DKMR: Improving Mutation-based Fault Localization through Denoising-based Kill Matrix Refinement
by: Liu, Hengyuan, et al.
Published: (2025)

Exploring the Potential and Limitations of Large Language Models for Novice Program Fault Localization
by: Xu, Hexiang, et al.
Published: (2025)

Explainable Fault Localization for Programming Assignments via LLM-Guided Annotation
by: Liu, Fang, et al.
Published: (2025)

SmartFL: Semantics Based Probabilistic Fault Localization
by: Wu, Yiqian, et al.
Published: (2025)

Definition and Detection of Centralization Defects in Smart Contracts
by: Lin, Zewei, et al.
Published: (2024)

SBEST: Spectrum-Based Fault Localization Without Fault-Triggering Tests
by: Rafi, Md Nakhla, et al.
Published: (2024)

Fault Localization from the Semantic Code Search Perspective
by: Qin, Yihao, et al.
Published: (2024)

Large Language Models for Equivalent Mutant Detection: How Far Are We?
by: Tian, Zhao, et al.
Published: (2024)

Enhancing LLM-based Fault Localization with a Functionality-Aware Retrieval-Augmented Generation Framework
by: Shi, Xinyu, et al.
Published: (2025)

AgentFL: Scaling LLM-based Fault Localization to Project-Level Context
by: Qin, Yihao, et al.
Published: (2024)

Back to the Future! Studying Data Cleanness in Defects4J and its Impact on Fault Localization
by: Rafi, Md Nakhla, et al.
Published: (2023)

Large Language Models for Fault Localization: An Empirical Study
by: Xiao, YingJian, et al.
Published: (2025)

An Empirical Study of the Realism of Mutants in Deep Learning
by: Ahmed, Zaheed, et al.
Published: (2025)

An Empirical Evaluation of Manually Created Equivalent Mutants
by: Straubinger, Philipp, et al.
Published: (2024)

Quantum Circuit Mutants: Empirical Analysis and Recommendations
by: Usandizaga, Eñaut Mendiluze, et al.
Published: (2023)

FlexFL: Flexible and Effective Fault Localization with Open-Source Large Language Models
by: Xu, Chuyang, et al.
Published: (2024)

RESTORE: Retrospective Fault Localization Enhancing Automated Program Repair
by: Xu, Tongtong, et al.
Published: (2019)

Towards Better Graph Neural Network-based Fault Localization Through Enhanced Code Representation
by: Rafi, Md Nakhla, et al.
Published: (2024)

A Multi-Agent Approach to Fault Localization via Graph-Based Retrieval and Reflexion
by: Rafi, Md Nakhla, et al.
Published: (2024)

Diversity Drives Fairness: Ensemble of Higher Order Mutants for Intersectional Fairness of Machine Learning Software
by: Chen, Zhenpeng, et al.
Published: (2024)

Simple Fault Localization using Execution Traces
by: Prenner, Julian Aron, et al.
Published: (2025)

An Empirical Study of Fault Localization in Python Programs
by: Rezaalipour, Mohammad, et al.
Published: (2023)

On Applying Bandit Algorithm to Fault Localization Techniques
by: Nakao, Masato, et al.
Published: (2024)

QCRMut: Quantum Circuit Random Mutant generator tool
by: Gil, Sinhué García, et al.
Published: (2024)

Test vs Mutant: Adversarial LLM Agents for Robust Unit Test Generation
by: Chang, Pengyu, et al.
Published: (2026)

FGIT: Fault-Guided Fine-Tuning for Code Generation
by: Fan, Lishui, et al.
Published: (2025)

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

Evaluating Mutation-based Fault Localization for Quantum Programs
by: Ishimoto, Yuta, et al.
Published: (2025)

On the Integration of Spectrum-Based Fault Localization Tools into IDEs
by: Szatmári, Attila, et al.
Published: (2024)

FauxPy: A Fault Localization Tool for Python
by: Rezaalipour, Mohammad, et al.
Published: (2024)

Effective Fault Localization using Probabilistic and Grouping Approach
by: Srivastava, Saksham Sahai, et al.
Published: (2024)

Impact of Large Language Models of Code on Fault Localization
by: Ji, Suhwan, et al.
Published: (2024)

Software Fault Localization Based on Multi-objective Feature Fusion and Deep Learning
by: Hu, Xiaolei, et al.
Published: (2024)

A Systematic Literature Review of Code Hallucinations in LLMs: Characterization, Mitigation Methods, Challenges, and Future Directions for Reliable AI
by: Gao, Cuiyun, et al.
Published: (2025)

Debug Like a Human: Scaling LLM-based Fault Localization to Processor Design via Block-Level Instruction-Oriented Slicing
by: Liu, Zizhen, et al.
Published: (2026)

Enhancing The Open Network: Definition and Automated Detection of Smart Contract Defects
by: Song, Hao, et al.
Published: (2025)

Extending Delta Debugging Minimization for Spectrum-Based Fault Localization
by: Kapugama, Charaka Geethal
Published: (2026)

Using Fourier Analysis and Mutant Clustering to Accelerate DNN Mutation Testing
by: Ghanbari, Ali, et al.
Published: (2025)

Exploring the Potential of Large Language Models in Simulink-Stateflow Mutant Generation
by: Valle, Pablo, et al.
Published: (2026)

Principal Context-aware Diffusion Guided Data Augmentation for Fault Localization
by: Fu, Shihao, et al.
Published: (2025)