Software Engineering for Computational Science: Past, Present, Future

JohansonArne, HasselbringWilhelm
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引用次数: 21

Abstract

Despite the increasing importance of in silico experiments to the scientific discovery process, state-of-the-art software engineering practices are rarely adopted in computational science. To understand the underlying causes for this situation and to identify ways to improve it, we conducted a literature survey on software engineering practices in computational science. We identified 13 recurring key characteristics of scientific software development that are the result of the nature of scientific challenges, the limitations of computers, and the cultural environment of scientific software development. Our findings allow us to point out shortcomings of existing approaches for bridging the gap between software engineering and computational science and to provide an outlook on promising research directions that could contribute to improving the current situation.
计算科学的软件工程:过去,现在,未来
尽管计算机实验在科学发现过程中越来越重要,但在计算科学中很少采用最先进的软件工程实践。为了理解这种情况的潜在原因,并确定改进它的方法,我们对计算科学中的软件工程实践进行了文献调查。我们确定了科学软件开发的13个反复出现的关键特征,这些特征是科学挑战的本质、计算机的局限性和科学软件开发的文化环境的结果。我们的发现使我们能够指出现有方法在弥合软件工程和计算科学之间的差距方面的缺点,并对有前途的研究方向提供了一个前景,这可能有助于改善当前的情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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