Re-opening open-source science through AI assisted development

Fuente: arXiv
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Main Authors: Hung, Ling-Hong, Yeung, Ka Yee
Format: Preprint
Published: 2025
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author Hung, Ling-Hong
Yeung, Ka Yee
author_facet Hung, Ling-Hong
Yeung, Ka Yee
contents Open-source scientific software is effectively closed to modification by its complexity. With recent advances in technology, an agentic AI team led by a single human can now rapidly and robustly modify large codebases and re-open science to the community which can review and vet the AI generated code. We demonstrate this with a case study, STAR-Flex, which is an open source fork of STAR, adding 16,000 lines of C++ code to add the ability to process 10x Flex data, while maintaining full original function. This is the first open-source processing software for Flex data and was written as part of the NIH funded MorPHiC consortium.
format Preprint
id arxiv_https___arxiv_org_abs_2512_11993
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Re-opening open-source science through AI assisted development
Hung, Ling-Hong
Yeung, Ka Yee
Software Engineering
Open-source scientific software is effectively closed to modification by its complexity. With recent advances in technology, an agentic AI team led by a single human can now rapidly and robustly modify large codebases and re-open science to the community which can review and vet the AI generated code. We demonstrate this with a case study, STAR-Flex, which is an open source fork of STAR, adding 16,000 lines of C++ code to add the ability to process 10x Flex data, while maintaining full original function. This is the first open-source processing software for Flex data and was written as part of the NIH funded MorPHiC consortium.
title Re-opening open-source science through AI assisted development
topic Software Engineering
url https://arxiv.org/abs/2512.11993