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Computational Idealizations in Software Intensive Science: a Comment on Symons' and Horner's paper

机译:软件密集型科学中的计算理想化:Symons和Horner论文的评述

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This commentary on John Symons' and Jack Homer's paper, besides sharing its main argument, challenges the authors' statement that there is no effective method to evaluate software-intensive systems as a distinguishing feature of software intensive science. It is underlined here how analogous methodological limitations characterise the evaluations of empirical systems in non-software intensive sciences. The authors' claim that formal methods establish the correctness of computational models rather than of the represented programme is here compared with the empirical adequacy problem typifying the model-based reasoning approach in physics, and the remark that testing all the paths of a software-intensive system is unfeasible is related to the enumerative induction problem in the justification of empirical law-like hypotheses in non-software intensive sciences.
机译:对约翰·西蒙斯(John Symons)和杰克·霍默(Jack Homer)的论文的评论,除了分享其主要论点外,还挑战了作者的说法,即没有有效的方法来评估软件密集型系统,这是软件密集型科学的显着特征。这里要强调的是,类似的方法学局限性是如何表征非软件密集型科学中的经验系统评估的。作者声称,形式方法确定了计算模型的正确性,而不是所代表程序的正确性,在此与物理上基于模型的推理方法的经验充足性问题进行了比较,并指出了测试软件密集型的所有路径的说法。在非软件密集型科学中,系统不可行与枚举归纳问题有关,该枚举归纳问题是基于经验法则的假设的证明。

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