Measuring the Performance of Computer Software — A Dual Role for Statisticians

Ivor Francis
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Ivor Francis: Cornell University

A chapter in Computer Science and Statistics: Proceedings of the 13th Symposium on the Interface, 1981, pp 199-204 from Springer

Abstract: Abstract In describing and modelling the properties of any system, science traditionally uses quantitative measures. The emerging science of software is no exception. Statisticians, traditionally the arbiters of evidential inference in science, can play an important role in defining quantitative measures — metrics — of software performance and the equally important quantitative measures of the computational difficulty of problems to be solved. Computer Science, in embracing empirical research in software, must now consult the discipline of experimental design. When the software is statistical in application, statisticians are also in the role of beneficiaries of this scientific study of software. As users they should insist that evaluations of performance measure not only the usual completion times of workloads on certain machines, but also the accuracy of computed solution and the usefulness of the output. This paper describes a classification system for statistical software which is based on quantitative measures drawn from the “life-cycle” of a complete statistical analysis: file building, editing, data display, exploration, model building.

Keywords: software performance; quantitative measures; classification; software science; evaluation; experimental design; statistical software (search for similar items in EconPapers)
Date: 1981
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4613-9464-8_29

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DOI: 10.1007/978-1-4613-9464-8_29

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