Code generation using machine learning: A systematic review
Recently, machine learning (ML) methods have been used to create powerful language
models for a broad range of natural language processing tasks. An important subset of this …
models for a broad range of natural language processing tasks. An important subset of this …
Deep learning-based software engineering: progress, challenges, and opportunities
Researchers have recently achieved significant advances in deep learning techniques,
which in turn has substantially advanced other research disciplines, such as natural …
which in turn has substantially advanced other research disciplines, such as natural …
The programmer's assistant: Conversational interaction with a large language model for software development
Large language models (LLMs) have recently been applied in software engineering to
perform tasks such as translating code between programming languages, generating code …
perform tasks such as translating code between programming languages, generating code …
Is ChatGPT the ultimate programming assistant--how far is it?
Recently, the ChatGPT LLM has received great attention: it can be used as a bot for
discussing source code, prompting it to suggest changes, provide descriptions or even …
discussing source code, prompting it to suggest changes, provide descriptions or even …
Spt-code: Sequence-to-sequence pre-training for learning source code representations
Recent years have seen the successful application of large pre-trained models to code
representation learning, resulting in substantial improvements on many code-related …
representation learning, resulting in substantial improvements on many code-related …
[HTML][HTML] A3test: Assertion-augmented automated test case generation
Context: Test case generation is a critical yet challenging task in software development.
Recently, AthenaTest–a Deep Learning (DL) approach for generating unit test cases has …
Recently, AthenaTest–a Deep Learning (DL) approach for generating unit test cases has …
Retrieval-based neural source code summarization
Source code summarization aims to automatically generate concise summaries of source
code in natural language texts, in order to help developers better understand and maintain …
code in natural language texts, in order to help developers better understand and maintain …
Automatic code documentation generation using gpt-3
Source code documentation is an important artifact for efficient software development. Code
documentation could greatly benefit from automation since manual documentation is often …
documentation could greatly benefit from automation since manual documentation is often …
Multilingual training for software engineering
Well-trained machine-learning models, which leverage large amounts of open-source
software data, have now become an interesting approach to automating many software …
software data, have now become an interesting approach to automating many software …
Learning deep semantics for test completion
Writing tests is a time-consuming yet essential task during software development. We
propose to leverage recent advances in deep learning for text and code generation to assist …
propose to leverage recent advances in deep learning for text and code generation to assist …