Code search: A survey of techniques for finding code
L Di Grazia, M Pradel - ACM Computing Surveys, 2023 - dl.acm.org
The immense amounts of source code provide ample challenges and opportunities during
software development. To handle the size of code bases, developers commonly search for …
software development. To handle the size of code bases, developers commonly search for …
Opportunities and challenges in code search tools
Code search is a core software engineering task. Effective code search tools can help
developers substantially improve their software development efficiency and effectiveness. In …
developers substantially improve their software development efficiency and effectiveness. In …
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 …
When deep learning met code search
There have been multiple recent proposals on using deep neural networks for code search
using natural language. Common across these proposals is the idea of embedding code …
using natural language. Common across these proposals is the idea of embedding code …
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 …
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 …
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 …
Aroma: Code recommendation via structural code search
Programmers often write code that has similarity to existing code written somewhere. A tool
that could help programmers to search such similar code would be immensely useful. Such …
that could help programmers to search such similar code would be immensely useful. Such …
Improving code search with co-attentive representation learning
Searching and reusing existing code from a large-scale codebase, eg, GitHub, can help
developers complete a programming task efficiently. Recently, Gu et al. proposed a deep …
developers complete a programming task efficiently. Recently, Gu et al. proposed a deep …