A survey on deep learning for software engineering
In 2006, Geoffrey Hinton proposed the concept of training “Deep Neural Networks (DNNs)”
and an improved model training method to break the bottleneck of neural network …
and an improved model training method to break the bottleneck of neural network …
A systematic literature review on source code similarity measurement and clone detection: Techniques, applications, and challenges
M Zakeri-Nasrabadi, S Parsa, M Ramezani… - Journal of Systems and …, 2023 - Elsevier
Measuring and evaluating source code similarity is a fundamental software engineering
activity that embraces a broad range of applications, including but not limited to code …
activity that embraces a broad range of applications, including but not limited to code …
An extensive study on pre-trained models for program understanding and generation
Automatic program understanding and generation techniques could significantly advance
the productivity of programmers and have been widely studied by academia and industry …
the productivity of programmers and have been widely studied by academia and industry …
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
The advancements in machine learning techniques have encouraged researchers to apply
these techniques to a myriad of software engineering tasks that use source code analysis …
these techniques to a myriad of software engineering tasks that use source code analysis …
[PDF][PDF] Unifying the perspectives of nlp and software engineering: A survey on language models for code
Z Zhang, C Chen, B Liu, C Liao, Z Gong… - arXiv preprint arXiv …, 2023 - simg.baai.ac.cn
In this work we systematically review the recent advancements in code processing with
language models, covering 50+ models, 30+ evaluation tasks, 170+ datasets, and 700 …
language models, covering 50+ models, 30+ evaluation tasks, 170+ datasets, and 700 …
Code search based on context-aware code translation
Code search is a widely used technique by developers during software development. It
provides semantically similar implementations from a large code corpus to developers …
provides semantically similar implementations from a large code corpus to developers …
Deep learning approaches for bad smell detection: a systematic literature review
Context Bad smells negatively impact software quality metrics such as understandability,
reusability, and maintainability. Reduced costs and enhanced software quality can be …
reusability, and maintainability. Reduced costs and enhanced software quality can be …
Deep learning application on code clone detection: A review of current knowledge
M Lei, H Li, J Li, N Aundhkar, DK Kim - Journal of Systems and Software, 2022 - Elsevier
Bad smells in code are indications of low code quality representing potential threats to the
maintainability and reusability of software. Code clone is a type of bad smells caused by …
maintainability and reusability of software. Code clone is a type of bad smells caused by …
Learning approximate execution semantics from traces for binary function similarity
Detecting semantically similar binary functions–a crucial capability with broad security
usages including vulnerability detection, malware analysis, and forensics–requires …
usages including vulnerability detection, malware analysis, and forensics–requires …