1 citations · 1 across the 4 of their papers we have counts for
4 papers
CodeReasoner: Enhancing the Code Reasoning Ability with Reinforcement Learning
Lingxiao Tang, He Ye, Zhongxin Liu +2
Code reasoning is a fundamental capability for large language models (LLMs) in the code domain. It involves understanding and predicting a program's execution behavior, such as det…
Towards More Realistic Evaluation for Neural Test Oracle Generation
Zhongxin Liu, Kui Liu, Xin Xia +1
Effective unit tests can help guard and improve software quality but require a substantial amount of time and effort to write and maintain. A unit test consists of a test prefix an…
CCT5: A Code-Change-Oriented Pre-Trained Model
Bo Lin, Shangwen Wang, Zhongxin Liu +3
Software is constantly changing, requiring developers to perform several derived tasks in a timely manner, such as writing a description for the intention of the code change, or id…
CCRep: Learning Code Change Representations via Pre-Trained Code Model and Query Back
Zhongxin Liu, Zhijie Tang, Xin Xia +1
Representing code changes as numeric feature vectors, i.e., code change representations, is usually an essential step to automate many software engineering tasks related to code ch…