LitterBox+: An Extensible Framework for LLM-enhanced Scratch Static Code Analysis

Fuente: arXiv
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Auteurs principaux: Fein, Benedikt, Obermüller, Florian, Fraser, Gordon
Format: Preprint
Publié: 2025
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author Fein, Benedikt
Obermüller, Florian
Fraser, Gordon
author_facet Fein, Benedikt
Obermüller, Florian
Fraser, Gordon
contents Large language models (LLMs) have become an essential tool to support developers using traditional text-based programming languages, but the graphical notation of the block-based Scratch programming environment inhibits the use of LLMs. To overcome this limitation, we propose the LitterBox+ framework that extends the Scratch static code analysis tool LitterBox with the generative abilities of LLMs. By converting block-based code to a textual representation suitable for LLMs, LitterBox+ allows users to query LLMs about their programs, about quality issues reported by LitterBox, and it allows generating code fixes. Besides offering a programmatic API for these functionalities, LitterBox+ also extends the Scratch user interface to make these functionalities available directly in the environment familiar to learners. The framework is designed to be easily extensible with other prompts, LLM providers, and new features combining the program analysis capabilities of LitterBox with the generative features of LLMs. We provide a screencast demonstrating the tool at https://youtu.be/RZ6E0xgrIgQ.
format Preprint
id arxiv_https___arxiv_org_abs_2509_12021
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle LitterBox+: An Extensible Framework for LLM-enhanced Scratch Static Code Analysis
Fein, Benedikt
Obermüller, Florian
Fraser, Gordon
Software Engineering
Large language models (LLMs) have become an essential tool to support developers using traditional text-based programming languages, but the graphical notation of the block-based Scratch programming environment inhibits the use of LLMs. To overcome this limitation, we propose the LitterBox+ framework that extends the Scratch static code analysis tool LitterBox with the generative abilities of LLMs. By converting block-based code to a textual representation suitable for LLMs, LitterBox+ allows users to query LLMs about their programs, about quality issues reported by LitterBox, and it allows generating code fixes. Besides offering a programmatic API for these functionalities, LitterBox+ also extends the Scratch user interface to make these functionalities available directly in the environment familiar to learners. The framework is designed to be easily extensible with other prompts, LLM providers, and new features combining the program analysis capabilities of LitterBox with the generative features of LLMs. We provide a screencast demonstrating the tool at https://youtu.be/RZ6E0xgrIgQ.
title LitterBox+: An Extensible Framework for LLM-enhanced Scratch Static Code Analysis
topic Software Engineering
url https://arxiv.org/abs/2509.12021