code-gen/cscg

Code Generation as a Dual Task of Code Summarization.

35
/ 100
Emerging

This tool helps AI/ML researchers explore a novel approach to code generation and summarization. It takes in structured code and its corresponding natural language annotations, then processes them to build language models. The output is a set of trained language models and computed probabilities for both code and annotations, useful for advancing research in AI for software engineering.

No commits in the last 6 months.

Use this if you are an AI/ML researcher or practitioner studying the relationship between code and its natural language descriptions, particularly for tasks like code generation or summarization.

Not ideal if you are looking for an out-of-the-box solution to generate code or summaries for your daily development work, as this is a research-oriented implementation.

AI-research natural-language-processing software-engineering-AI code-analysis machine-learning-models
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 12 / 25

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Stars

30

Forks

4

Language

Jupyter Notebook

License

MIT

Last pushed

Jun 28, 2021

Commits (30d)

0

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