Výsledky vyhledávání - "Java program repair"

CodeTranFix: A Neural Machine Translation Approach for Context-Aware Java Program Repair with CodeBERT

Autoři: Yiwei Lu Shuxia Ye Liang Qi

Zdroj: Applied Sciences, Vol 15, Iss 7, p 3632 (2025)

Témata: Technology, Chemistry, QH301-705.5, Physics, QC1-999, context-aware patch generation, automated program repair (APR), TA1-2040, Biology (General), Engineering (General). Civil engineering (General), neural machine translation (NMT), QD1-999

Přístupová URL adresa: https://doaj.org/article/16b1494334b748a0b2e0208d5ddee76e

Empirical review of Java program repair tools: a large-scale experiment on 2,141 bugs and 23,551 repair attempts

Autoři: Matias Martinez Thomas Durieux Fernanda Madeiral a další

Zdroj: Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering. :302-313

Témata: Software Engineering (cs.SE), FOS: Computer and information sciences, Computer Science - Software Engineering, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: http://arxiv.org/pdf/1905.11973
http://arxiv.org/abs/1905.11973
https://dl.acm.org/doi/pdf/10.1145/3338906.3338911
https://dblp.uni-trier.de/db/journals/corr/corr1905.html#abs-1905-11973
https://dl.acm.org/citation.cfm?id=3338911

Empirical Review of Java Program Repair Tools: A Large-Scale Experiment on 2,141 Bugs and 23,551 Repair Attempts

Autoři: Durieux, Thomas Madeiral, Fernanda Martinez, Matias a další

Témata: Computer Science - Software Engineering, text

URL: http://arxiv.org/abs/1905.11973

CodeTranFix: A Neural Machine Translation Approach for Context-Aware Java Program Repair with CodeBERT.

Autoři: Lu, Yiwei Ye, Shuxia Qi, Liang

Zdroj: Applied Sciences (2076-3417); Apr2025, Vol. 15 Issue 7, p3632, 14p

Témata: LANGUAGE models, COMPUTER software quality control, CONTEXTUAL learning, BOTTLENECKS (Manufacturing), GENERALIZATION

Java Syntax Error Repair Using RoBERTa

Autoři: Xiang, Ziyi

Témata: Java program repair, RoBERTa, Neural machine translation architecture, Reparation av Java­program, Neural maskinöversättningsarkitektu, Computer Sciences, Datavetenskap (datalogi)

Popis souboru: application/pdf

Relation: TRITA-EECS-EX ; 2022:64

Dostupnost: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-311988

ContrastRepair: Enhancing Conversation-Based Automated Program Repair via Contrastive Test Case Pairs.

Autoři: Kong, Jiaolong Xie, Xiaofei Cheng, Mingfei a další

Zdroj: ACM Transactions on Software Engineering & Methodology; Nov2025, Vol. 34 Issue 8, p1-31, 31p

Témata: CHATGPT, LANGUAGE models, SOFTWARE failures, SOFTWARE maintenance, PROBLEM solving

Benchmarking and Categorizing the Performance of Neural Program Repair Systems for Java.

Autoři: Zhong, Wenkang Li, Chuanyi Liu, Kui a další

Zdroj: ACM Transactions on Software Engineering & Methodology; Jan2025, Vol. 34 Issue 1, p1-35, 35p

Témata: DEEP learning, SYSTEMS software, RESEARCH personnel, EMPIRICAL research

RESTORE: Retrospective Fault Localization Enhancing Automated Program Repair

Autoři: Xu, Tongtong Chen, Liushan Pei, Yu a další

Témata: Computer Science - Software Engineering, text

URL: http://arxiv.org/abs/1906.01778

On the acceptance by code reviewers of candidate security patches suggested by Automated Program Repair tools.

Autoři: Papotti, Aurora Paramitha, Ranindya Massacci, Fabio

Zdroj: Empirical Software Engineering; Sep2024, Vol. 29 Issue 5, p1-35, 35p

Test-based patch clustering for automatically-generated patches assessment.

Autoři: Martinez, Matias Kechagia, Maria Perera, Anjana a další

Zdroj: Empirical Software Engineering; Sep2024, Vol. 29 Issue 5, p1-31, 31p

The Impact of Input Types on Smart Contract Vulnerability Detection Performance Based on Deep Learning: A Preliminary Study.

Autoři: Aldyaflah, Izdehar M. Zhao, Wenbing Yang, Shunkun a další

Zdroj: Information; Jun2024, Vol. 15 Issue 6, p302, 22p

Témata: DEEP learning, CONVOLUTIONAL neural networks, CONTRACTS

Smart Contract Code Repair Recommendation based on Reinforcement Learning and Multi-metric Optimization.

Autoři: Guo, Hanyang Chen, Yingye Chen, Xiangping a další

Zdroj: ACM Transactions on Software Engineering & Methodology; May2024, Vol. 33 Issue 4, p1-31, 31p

Témata: HEURISTIC algorithms, SEARCH algorithms, CONTRACTS, PROGRAMMING languages, HEURISTIC, REINFORCEMENT learning, BLOCKCHAINS

RobustNPR: Evaluating the robustness of neural program repair models.

Autoři: Ge, Hongliang Zhong, Wenkang Li, Chuanyi a další

Zdroj: Journal of Software: Evolution & Process; Apr2024, Vol. 36 Issue 4, p1-16, 16p

Témata: SUCCESS

APR4Vul: an empirical study of automatic program repair techniques on real-world Java vulnerabilities.

Autoři: Bui, Quang-Cuong Paramitha, Ranindya Vu, Duc-Ly a další

Zdroj: Empirical Software Engineering; Feb2024, Vol. 29 Issue 1, p1-40, 40p

A Survey of Learning-based Automated Program Repair.

Autoři: Zhang, Quanjun Fang, Chunrong Ma, Yuxiang a další

Zdroj: ACM Transactions on Software Engineering & Methodology; Feb2024, Vol. 33 Issue 2, p1-69, 69p

Témata: MACHINE translating, SOFTWARE maintenance, COMPUTER software development, OPEN scholarship, REPAIRING, SOFTWARE engineering, QUALITY function deployment, DEEP learning

Reliable Fix Patterns Inferred from Static Checkers for Automated Program Repair.

Autoři: KUI LIU JINGTANG ZHANG LI LI a další

Zdroj: ACM Transactions on Software Engineering & Methodology; Jul2023, Vol. 32 Issue 4, p1-38, 38p

The Best of Both Worlds: Combining Learned Embeddings with Engineered Features for Accurate Prediction of Correct Patches.

Autoři: HAOYE TIAN KUI LIU YINGHUA LI a další

Zdroj: ACM Transactions on Software Engineering & Methodology; Jul2023, Vol. 32 Issue 4, p1-51, 51p

Seeing the Whole Elephant: Systematically Understanding and Uncovering Evaluation Biases in Automated Program Repair.

Autoři: DEHENG YANG YAN LEI XIAOGUANG MAO a další

Zdroj: ACM Transactions on Software Engineering & Methodology; May2023, Vol. 32 Issue 3, p1-37, 37p

Restore: Retrospective Fault Localization Enhancing Automated Program Repair

Autoři: Tongtong Xu Liushan Chen Yu Pei a další

Přispěvatelé: Tongtong Xu Liushan Chen Yu Pei a další

Zdroj: IEEE Transactions on Software Engineering. 48:309-326

Témata: Software Engineering (cs.SE), FOS: Computer and information sciences, Computer Science - Software Engineering, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: http://arxiv.org/pdf/1906.01778
http://arxiv.org/abs/1906.01778
https://ieeexplore.ieee.org/document/9068412/
https://dblp.uni-trier.de/db/journals/corr/corr1906.html#abs-1906-01778

A comprehensive study of code-removal patches in automated program repair.

Autoři: Ginelli, Davide Martinez, Matias Mariani, Leonardo a další

Zdroj: Empirical Software Engineering; Jul2022, Vol. 27 Issue 4, p1-43, 43p