Cure: Code-aware neural machine translation for automatic program repair
Automatic program repair (APR) is crucial to improve software reliability. Recently, neural
machine translation (NMT) techniques have been used to automatically fix software bugs …
machine translation (NMT) techniques have been used to automatically fix software bugs …
Machine/deep learning for software engineering: A systematic literature review
Since 2009, the deep learning revolution, which was triggered by the introduction of
ImageNet, has stimulated the synergy between Software Engineering (SE) and Machine …
ImageNet, has stimulated the synergy between Software Engineering (SE) and Machine …
What do they capture? a structural analysis of pre-trained language models for source code
Recently, many pre-trained language models for source code have been proposed to model
the context of code and serve as a basis for downstream code intelligence tasks such as …
the context of code and serve as a basis for downstream code intelligence tasks such as …
Infercode: Self-supervised learning of code representations by predicting subtrees
Learning code representations has found many uses in software engineering, such as code
classification, code search, comment generation, and bug prediction, etc. Although …
classification, code search, comment generation, and bug prediction, etc. Although …
A survey on machine learning techniques for source code analysis
T Sharma, M Kechagia, S Georgiou, R Tiwari… - ar** study of source code representation for deep learning in software engineering
The usage of deep learning (DL) approaches for software engineering has attracted much
attention, particularly in source code modelling and analysis. However, in order to use DL …
attention, particularly in source code modelling and analysis. However, in order to use DL …
Assessing generalizability of codebert
Pre-trained models like BERT have achieved strong improvements on many natural
language processing (NLP) tasks, showing their great generalizability. The success of pre …
language processing (NLP) tasks, showing their great generalizability. The success of pre …
Code smell detection by deep direct-learning and transfer-learning
T Sharma, V Efstathiou, P Louridas… - Journal of Systems and …, 2021 - Elsevier
Context: An excessive number of code smells make a software system hard to evolve and
maintain. Machine learning methods, in addition to metric-based and heuristic-based …
maintain. Machine learning methods, in addition to metric-based and heuristic-based …
Self-supervised contrastive learning for code retrieval and summarization via semantic-preserving transformations
We propose Corder, a self-supervised contrastive learning framework for source code
model. Corder is designed to alleviate the need of labeled data for code retrieval and code …
model. Corder is designed to alleviate the need of labeled data for code retrieval and code …
Evaluating representation learning of code changes for predicting patch correctness in program repair
A large body of the literature of automated program repair develops approaches where
patches are generated to be validated against an oracle (eg, a test suite). Because such an …
patches are generated to be validated against an oracle (eg, a test suite). Because such an …