New Tool Generates Contamination-Resistant, Labeled Code Datasets for LLMs
Summary
Spaghetti Architect is a new open-source tool that generates controlled, multi-language code datasets, addressing issues of contamination and lack of semantic control in existing code corpora. It creates correct-by-construction programs with adjustable "messiness" and difficulty labels, making it ideal for training and evaluating code-generating LLMs.
Why it matters
This tool provides a critical resource for AI researchers and engineers to develop and rigorously test code-generating LLMs with clean, controlled, and diverse datasets, overcoming limitations of existing public corpora.
How to implement this in your domain
- 1Download and experiment with Spaghetti Architect to generate custom code datasets for specific LLM training needs.
- 2Integrate generated datasets into existing LLM evaluation pipelines to benchmark model performance on controlled tasks.
- 3Utilize the tool's "messiness" and difficulty controls to create targeted challenges for code generation and refactoring models.
- 4Contribute to the open-source project to expand language support or add new anti-pattern profiles.
Who benefits
Key takeaways
- Spaghetti Architect generates controlled, multi-language code datasets for LLM training and evaluation.
- It addresses data contamination and provides precise semantic and difficulty labels.
- The tool creates correct-by-construction programs with adjustable "messiness" and complexity.
- It is an open-source, dependency-free resource for improving code-generating AI.
Original post by Yuxiang Ji
"arXiv:2607.18642v1 Announce Type: new Abstract: Mined code corpora are abundant but uncontrolled: a snippet's semantics, surface "messiness," and difficulty are whatever the wild contained; there is no known-optimal reference to grade against; and any public sample may already si…"
View on XOriginally posted by Yuxiang Ji on X · view source
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