LocSeq: Automated Localization for Compiler Optimization Sequence Bugs of LLVM

Author:

Zhou Zhide1ORCID,Jiang He2ORCID,Ren Zhilei1,Chen Yuting3,Qiao Lei4

Affiliation:

1. Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province and the School of Software, Dalian University of Technology, Dalian, China

2. Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, the School of Software, and DUT Artificial Intelligence, Dalian University of Technology, Dalian, China

3. Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China

4. Beijing Institute of Control Engineering, Beijing, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Safety, Risk, Reliability and Quality

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1. Isolating Compiler Bugs by Generating Effective Witness Programs With Large Language Models;IEEE Transactions on Software Engineering;2024-07

2. A Testing Program and Pragma Combination Selection Based Framework for High-Level Synthesis Tool Pragma-Related Bug Detection;IEEE Transactions on Software Engineering;2024-04

3. Software bug localization based on optimized and ensembled deep learning models;Journal of Software: Evolution and Process;2024-02-26

4. An interval construction belief rule base with interpretability for complex systems;Expert Systems with Applications;2023-11

5. Automatically Localizing Dynamic Code Generation Bugs in JIT Compiler Back-End;Proceedings of the 32nd ACM SIGPLAN International Conference on Compiler Construction;2023-02-17

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