.png){kind=icon}
返回
Automatic Software Repair: A Survey
.png){kind=icon}
OA
AI
DOI：10.1109/TSE.2017.2755013.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Despite their growing complexity and increasing size, modern software applications must satisfy strict release requirements that impose short bug fixing and maintenance cycles, putting significant pressure on developers who are responsible for timely producing high-quality software. To reduce developers workload, repairing and healing techniques have been extensively investigated as solutions for efficiently repairing and maintaining software in the last few years. In particular, repairing solutions have been able to automatically produce useful fixes for several classes of bugs that might be present in software programs. A range of algorithms, techniques, and heuristics have been integrated, experimented, and studied, producing a heterogeneous and articulated research framework where automatic repair techniques are proliferating. This paper organizes the knowledge in the area by surveying a body of 108 papers about automatic software repair techniques, illustrating the algorithms and the approaches, comparing them on representative examples, and discussing the open challenges and the empirical evidence reported so far.
Keyword:
Automatic program repair
generate and validate
search-based
semantics-driven repair
correct by construction
program synthesis
self-repairing
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
5.6
论文数:
2.9K
被引数:
1.1W
机构
引用论文
.png){kind=icon}
Polysialylated Neural Cell Adhesion Molecule Is Involved in Induction of Long-Term Potentiation and Memory Acquisition and Consolidation in a Fear-Conditioning Paradigm聚唾液酸化的神经细胞粘附分子在恐惧调节范式中参与诱导长期增强和记忆获取和巩固OAAI
OAAI分享收藏分享收藏分享收藏
查看更多内容