activity
20172023
most citedHow to Design a Program Repair Bot? Insights from the Repairnator Project

71 citations · 226 across the 11 of their papers we have counts for

collaborators

11 papers

cs.SE2023

Understanding Solidity Event Logging Practices in the Wild

Lantian Li, Yejian Liang, Zhihao Liu +1

Writing logging messages is a well-established conventional programming practice, and it is of vital importance for a wide variety of software development activities. The logging m…

cs.SE2023

Pre-training Code Representation with Semantic Flow Graph for Effective Bug Localization

Yali Du, Zhongxing Yu

Enlightened by the big success of pre-training in natural language processing, pre-trained models for programming languages have been widely used to promote code intelligence in re…

cs.SE2021★ 5 cited

Megadiff: A Dataset of 600k Java Source Code Changes Categorized by Diff Size

Martin Monperrus, Matias Martinez, He Ye +3

This paper presents Megadiff, a dataset of source code diffs. It focuses on Java, with strict inclusion criteria based on commit message and diff size. Megadiff contains 663 029 Ja…

cs.SE2020★ 16 cited

A Software-Repair Robot based on Continual Learning

Benoit Baudry, Zimin Chen, Khashayar Etemadi +8

Software bugs are common and correcting them accounts for a significant part of costs in the software development and maintenance process. This calls for automatic techniques to de…

cs.SE2019★ 10 cited

Learning the Relation between Code Features and Code Transforms with Structured Prediction

Zhongxing Yu, Matias Martinez, Zimin Chen +2

To effectively guide the exploration of the code transform space for automated code evolution techniques, we present in this paper the first approach for structurally predicting co…

cs.SE2018★ 71 cited

How to Design a Program Repair Bot? Insights from the Repairnator Project

Simon Urli, Zhongxing Yu, Lionel Seinturier +1

Program repair research has made tremendous progress over the last few years, and software development bots are now being invented to help developers gain productivity. In this pap…

cs.SE2018★ 58 cited

Alleviating Patch Overfitting with Automatic Test Generation: A Study of Feasibility and Effectiveness for the Nopol Repair System

Zhongxing Yu, Matias Martinez, Benjamin Danglot +2

Among the many different kinds of program repair techniques, one widely studied family of techniques is called test suite based repair. However, test suites are in essence input-ou…

cs.SE2018★ 35 cited

Characterizing the Usage, Evolution and Impact of Java Annotations in Practice

Zhongxing Yu, Chenggang Bai, Lionel Seinturier +1

Annotations have been formally introduced into Java since Java 5. Since then, annotations have been widely used by the Java community for different purposes, such as compiler guida…

cs.SE2017★ 3 cited

Exhaustive Exploration of the Failure-oblivious Computing Search Space

Thomas Durieux, Youssef Hamadi, Zhongxing Yu +2

High-availability of software systems requires automated handling of crashes in presence of errors. Failure-oblivious computing is one technique that aims to achieve high availabil…

cs.SE2017★ 7 cited

A Snowballing Literature Study on Test Amplification

Benjamin Danglot, Oscar Luis Vera-Pérez, Zhongxing Yu +3

The adoption of agile development approaches has put an increased emphasis on developer testing, resulting in software projects with strong test suites. These suites include a larg…

cs.SE2017★ 21 cited

Test Case Generation for Program Repair: A Study of Feasibility and Effectiveness

Zhongxing Yu, Matias Martinez, Benjamin Danglot +2

Among the many different kinds of program repair techniques, one widely studied family of techniques is called test suite based repair. Test-suites are in essence input-output spec…