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Deep learning for code intelligence: Survey, benchmark and toolkit
Code intelligence leverages machine learning techniques to extract knowledge from
extensive code corpora, with the aim of develo** intelligent tools to improve the quality …
extensive code corpora, with the aim of develo** intelligent tools to improve the quality …
Graph neural networks: foundation, frontiers and applications
The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …
recent years. Graph neural networks, also known as deep learning on graphs, graph …
Large language models are few-shot summarizers: Multi-intent comment generation via in-context learning
Code comment generation aims at generating natural language descriptions for a code
snippet to facilitate developers' program comprehension activities. Despite being studied for …
snippet to facilitate developers' program comprehension activities. Despite being studied for …
Semantic similarity metrics for evaluating source code summarization
Source code summarization involves creating brief descriptions of source code in natural
language. These descriptions are a key component of software documentation such as …
language. These descriptions are a key component of software documentation such as …
Studying the usage of text-to-text transfer transformer to support code-related tasks
Deep learning (DL) techniques are gaining more and more attention in the software
engineering community. They have been used to support several code-related tasks, such …
engineering community. They have been used to support several code-related tasks, such …
An empirical comparison of pre-trained models of source code
While a large number of pre-trained models of source code have been successfully
developed and applied to a variety of software engineering (SE) tasks in recent years, our …
developed and applied to a variety of software engineering (SE) tasks in recent years, our …
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, H Yu… - 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 …
Cocomic: Code completion by jointly modeling in-file and cross-file context
While pre-trained language models (LM) for code have achieved great success in code
completion, they generate code conditioned only on the contents within the file, ie, in-file …
completion, they generate code conditioned only on the contents within the file, ie, in-file …