Tootfinder

Report of the 2025 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science
L. C. McInnes, D. Arnold, P. Balaprakash, M. Bernhardt, B. Cerny, A. Dubey, R. Giles, D. W. Hood, M. A. Leung, V. Lopez-Marrero, P. Messina, O. B. Newton, C. Oehmen, S. M. Wild, J. Willenbring, L. Woodley, T. Baylis, D. E. Bernholdt, C. Camano, J. Cohoon, C. Ferenbaugh, S. M. Fiore, S. Gesing, D. Gomez-Zara, J. Howison, T. Islam,…

Report of the 2025 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science
This report summarizes insights from the 2025 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science, which convened more than 40 experts from national laboratories, academia, industry, and community organizations to chart a path toward more powerful, sustainable, and collaborative scientific software ecosystems. To address urgent challenges at the intersection of high-performance computing (HPC), AI, and scien…

FreshBrew: A Benchmark for Evaluating AI Agents on Java Code Migration
Victor May, Diganta Misra, Yanqi Luo, Anjali Sridhar, Justine Gehring, Silvio Soares Ribeiro Junior
https://arxiv.org/abs/2510.04852

FreshBrew: A Benchmark for Evaluating AI Agents on Java Code Migration
AI coding assistants are rapidly becoming integral to modern software development. A key challenge in this space is the continual need to migrate and modernize codebases in response to evolving software ecosystems. Traditionally, such migrations have relied on rule-based systems and human intervention. With the advent of powerful large language models (LLMs), AI-driven agentic frameworks offer a promising alternative-but their effectiveness has not been systematically evaluated. In this paper, …

ChemGen: Code Generation for Multispecies Chemical Kinetics in Computational Physics Simulations
Ryan F. Johnson, Eric J. Ching, Ethan S. Genter, Joshua E. Lipman, Andrew D. Kercher, Jay Arcities, Hai Wang
https://arxiv.org/abs/2510.10005

ChemGen: Code Generation for Multispecies Chemical Kinetics in Computational Physics Simulations
This paper introduces ChemGen, a software package that uses code generation to integrate multispecies thermodynamics and chemical kinetics into C+-based computational physics codes. ChemGen aims to make chemical kinetics more accessible in existing simulation frameworks and help bridge the gap between combustion modeling and computational physics. The package employs the concept of decorators which enable flexible C++ code generation to target established software ecosystems. ChemGen generates …

Crosslisted article(s) found for cs.MS. https://arxiv.org/list/cs.MS/new
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- Report of the 2025 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Co...
L. C. McInnes, et al.