5 citations · 8 across the 4 of their papers we have counts for
6 papers
Demystifying Deep Learning Compiler Frontend Bugs: An LLM-Aided Empirical Study
Xinyi Yuan, Wei Chen, Jinyi Liu +5
Deep learning compilers (DLCs) are designed to translate deep learning programs into optimized, hardware-specific code. Typically, DLC frontends translate programs into graph-based…
PATCH: Empowering Large Language Model with Programmer-Intent Guidance and Collaborative-Behavior Simulation for Automatic Bug Fixing
Yuwei Zhang, Zhi Jin, Ying Xing +5
Bug fixing holds significant importance in software development and maintenance. Recent research has made substantial strides in exploring the potential of large language models (L…
CITYWALK: Enhancing LLM-Based C++ Unit Test Generation via Project-Dependency Awareness and Language-Specific Knowledge
Yuwei Zhang, Qingyuan Lu, Kai Liu +6
Unit testing plays a pivotal role in the software development lifecycle, as it ensures code quality. However, writing high-quality unit tests remains a time-consuming task for deve…
STEAM: Simulating the InTeractive BEhavior of ProgrAMmers for Automatic Bug Fixing
Yuwei Zhang, Zhi Jin, Ying Xing +1
Bug fixing holds significant importance in software development and maintenance. Recent research has made notable progress in exploring the potential of large language models (LLMs…
When the Open Source Community Meets COVID-19: Characterizing COVID-19 themed GitHub Repositories
Liu Wang, Ruiqing Li, Jiaxin Zhu +2
Ever since the beginning of the outbreak of the COVID-19 pandemic, researchers from interdisciplinary domains have worked together to fight against the crisis. The open source comm…
Feedback-based, Automated Failure Testing of Microservice-based Applications
Chengxu Cui, Guoquan Wu, Wei Chen +2
Modern distributed applications are moving toward a microservice architecture, in which each service is developed and managed independently, and new features and updates are delive…