.png){kind=icon}
返回
Program Repair With Repeated Learning
.png){kind=icon}
PRE
AI
DOI：10.1109/TSE.2022.3164662.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
A key challenge in generate-and-validate automated program repair is directing the search for fixes so that it can efficiently find those that are more likely to be correct. To this end, several techniques use machine learning to capture the features of programmer-written fixes. In existing approaches, fitting the model typically takes place before fix generation and is independent of it: the fix generation process uses the learned model as one of its inputs. However, the intermediate outcomes of an ongoing fix generation process often provide valuable information about which candidate fixes were better; this information could profitably be used to retrain the model, so that each new iteration of the fixing process would also learn from the outcome of previous ones. In this paper, we propose the LIANA technique for automated program repair, which is based on this idea of repeatedly learning the features of generated fixes. To this end, LIANA uses a fine-grained model that combines information about fix characteristics, their relations to the fixing context, and the results of test execution. The model is initially trained offline, and then repeatedly updated online as the fix generation process unravels; at any step, the most up-to-date model is used to guide the search for fixes-prioritizing those that are more likely to include the right ingredients. In an experimental evaluation on 732 real-world Java bugs from 3 popular benchmarks, LIANA built correct fixes for 134 faults ( 83 ranked as first in its output)- improving over several other generate-and-validate program repair tools according to various measures.
Keyword:
Automated program repair (APR)
generate-and-validate APR
learning-to-rank
repeated learning
期刊
IF:
5.6
论文数:
2.9K
被引数:
1.1W
机构
引用论文
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Three-dimensional computed tomographic angiography of a horseshoe kidney with ureteropelvic junction obstruction.png)
Urology
UrologyIF0
PREAI
分享收藏
查看更多内容