15 citations · 34 across the 5 of their papers we have counts for
5 papers
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…
Poison Attack and Defense on Deep Source Code Processing Models
Jia Li, Zhuo Li, Huangzhao Zhang +4
In the software engineering community, deep learning (DL) has recently been applied to many source code processing tasks. Due to the poor interpretability of DL models, their secur…
Is this Change the Answer to that Problem? Correlating Descriptions of Bug and Code Changes for Evaluating Patch Correctness
Haoye Tian, Xunzhu Tang, Andrew Habib +5
In this work, we propose a novel perspective to the problem of patch correctness assessment: a correct patch implements changes that "answer" to a problem posed by buggy behaviour.…
Are We Building on the Rock? On the Importance of Data Preprocessing for Code Summarization
Lin Shi, Fangwen Mu, Xiao Chen +6
Code summarization, the task of generating useful comments given the code, has long been of interest. Most of the existing code summarization models are trained and validated on wi…