activity
20162025
most citedIdentifying Patch Correctness in Test-Based Program Repair

164 citations · 404 across the 23 of their papers we have counts for

collaborators

24 papers

cs.SE2025★ 2 cited

Trae Agent: An LLM-based Agent for Software Engineering with Test-time Scaling

Trae Research Team, Pengfei Gao, Zhao Tian +12

Software issue resolution is a critical challenge in software engineering and has garnered increasing attention in recent years. With the rapid advancement of large language models…

cs.SE2025

SmartFL: Semantics Based Probabilistic Fault Localization

Yiqian Wu, Yujie Liu, Yi Yin +5

Testing-based fault localization has been a research focus in software engineering in the past decades. It localizes faulty program elements based on a set of passing and failing t…

cs.PL2025

Grammar-Based Code Representation: Is It a Worthy Pursuit for LLMs?

Qingyuan Liang, Zhao Zhang, Zeyu Sun +9

Grammar serves as a cornerstone in programming languages and software engineering, providing frameworks to define the syntactic space and program structure. Existing research demon…

cs.SE2024★ 118 cited

DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Daya Guo, Qihao Zhu, Dejian Yang +10

The rapid development of large language models has revolutionized code intelligence in software development. However, the predominance of closed-source models has restricted extens…

cs.SE2023

OrdinalFix: Fixing Compilation Errors via Shortest-Path CFL Reachability

Wenjie Zhang, Guancheng Wang, Junjie Chen +3

The development of correct and efficient software can be hindered by compilation errors, which must be fixed to ensure the code's syntactic correctness and program language constra…

cs.SE2023★ 14 cited

Accelerating Patch Validation for Program Repair with Interception-Based Execution Scheduling

Yuan-An Xiao, Chenyang Yang, Bo Wang +1

Long patch validation time is a limiting factor for automated program repair (APR). Though the duality between patch validation and mutation testing is recognized, so far there exi…

cs.SE2023

Reliability Assurance for Deep Neural Network Architectures Against Numerical Defects

Linyi Li, Yuhao Zhang, Luyao Ren +2

With the widespread deployment of deep neural networks (DNNs), ensuring the reliability of DNN-based systems is of great importance. Serious reliability issues such as system failu…

cs.SE2023★ 3 cited

Effective Random Test Generation for Deep Learning Compilers

Luyao Ren, ZiHeng Wang, Yingfei Xiong +3

Deep learning compilers help address the difficulties of deploying deep learning models on diverse types of hardware. Testing deep learning compilers is highly crucial, because the…

cs.PL2022

Decomposition-Based Synthesis for Applying Divide-and-Conquer-Like Algorithmic Paradigms

Ruyi Ji, Yuwei Zhao, Yingfei Xiong +3

Algorithmic paradigms such as divide-and-conquer (D&C) are proposed to guide developers in designing efficient algorithms, but it can still be difficult to apply algorithmic paradi…

cs.SE2021★ 6 cited

Lyra: A Benchmark for Turducken-Style Code Generation

Qingyuan Liang, Zeyu Sun, Qihao Zhu +4

Recently, neural techniques have been used to generate source code automatically. While promising for declarative languages, these approaches achieve much poorer performance on dat…

cs.PL2021

Occam Learning Meets Synthesis Through Unification

Ruyi Ji, Jingtao Xia, Yingfei Xiong +1

The generalizability of PBE solvers is the key to the empirical synthesis performance. Despite the importance of generalizability, related studies on PBE solvers are still limited.…

cs.LG2021

Generalized Equivariance and Preferential Labeling for GNN Node Classification

Zeyu Sun, Wenjie Zhang, Lili Mou +3

Existing graph neural networks (GNNs) largely rely on node embeddings, which represent a node as a vector by its identity, type, or content. However, graphs with unattributed nodes…

cs.CL2020★ 9 cited

OCoR: An Overlapping-Aware Code Retriever

Qihao Zhu, Zeyu Sun, Xiran Liang +2

Code retrieval helps developers reuse the code snippet in the open-source projects. Given a natural language description, code retrieval aims to search for the most relevant code a…

cs.SE2020★ 2 cited

Interactive Patch Filtering as Debugging Aid

Jingjing Liang, Ruyi Ji, Jiajun Jiang +3

It is widely recognized that program repair tools need to have a high precision to be useful, i.e., the generated patches need to have a high probability to be correct. However, it…

cs.AI2020★ 32 cited

NLocalSAT: Boosting Local Search with Solution Prediction

Wenjie Zhang, Zeyu Sun, Qihao Zhu +4

The Boolean satisfiability problem (SAT) is a famous NP-complete problem in computer science. An effective way for solving a satisfiable SAT problem is the stochastic local search…

cs.LG2019★ 18 cited

TreeGen: A Tree-Based Transformer Architecture for Code Generation

Zeyu Sun, Qihao Zhu, Yingfei Xiong +3

A code generation system generates programming language code based on an input natural language description. State-of-the-art approaches rely on neural networks for code generation…

cs.LG2018★ 17 cited

A Grammar-Based Structural CNN Decoder for Code Generation

Zeyu Sun, Qihao Zhu, Lili Mou +3

Code generation maps a program description to executable source code in a programming language. Existing approaches mainly rely on a recurrent neural network (RNN) as the decoder.…

cs.SE2018★ 1 cited

Automatic Clone Recommendation for Refactoring Based on the Present and the Past

Ruru Yue, Zhe Gao, Na Meng +3

When many clones are detected in software programs, not all clones are equally important to developers. To help developers refactor code and improve software quality, various tools…

cs.SE2018★ 15 cited

An Empirical Study of Fault Localization Families and Their Combinations

Daming Zou, Jingjing Liang, Yingfei Xiong +2

The performance of fault localization techniques is critical to their adoption in practice. This paper reports on an empirical study of a wide range of fault localization technique…

cs.SE2018

Learning to Synthesize

Yingfei Xiong, Bo Wang, Guirong Fu +1

In many scenarios we need to find the most likely program under a local context, where the local context can be an incomplete program, a partial specification, natural language des…

cs.SE2017★ 164 cited

Identifying Patch Correctness in Test-Based Program Repair

Yingfei Xiong, Xinyuan Liu, Muhan Zeng +2

Test-based automatic program repair has attracted a lot of attention in recent years. However, the test suites in practice are often too weak to guarantee correctness and existing…

cs.SE2017★ 1 cited

Can defects be fixed with weak test suites? An analysis of 50 defects from Defects4J

Jiajun Jiang, Yingfei Xiong

Automated program repair techniques, which target to generating correct patches for real world defects automatically, have gained a lot of attention in the last decade. Many differ…

cs.SE2017

Faster Mutation Analysis via Equivalence Modulo States

Bo Wang, Yingfei Xiong, Yangqingwei Shi +2

Mutation analysis has many applications, such as asserting the quality of test suites and localizing faults. One important bottleneck of mutation analysis is scalability. The lates…

cs.SE2016★ 2 cited

Precise Condition Synthesis for Program Repair

Yingfei Xiong, Jie Wang, Runfa Yan +4

Due to the difficulty of repairing defect, many research efforts have been devoted into automatic defect repair. Given a buggy program that fails some test cases, a typical automat…