Abstract
Quality optimisation methods offer a structured way of improving software development as early as in the product design phase. This work introduces the Taguchi method in software design optimisation. The basics of the method are reviewed along with a proposed methodology for design of experiments (DOE). A case study is drawn from a real software development project in the area of industrial simulations. One critical quality characteristic in simulations software is the software performance. A key performance metric, the code total execution time, is selected to monitor experimentally performance variation. Taguchi's DOE is employed to provide a practical relationship between code structure factors and factor interactions and the performance metric. The run-time performance evaluation of two alternate versions of multiple loop-nesting are analysed by Taguchi's signal-to-noise ratio (SNR) concept. The purpose of the paper was to insinuate the usefulness of these statistical tools in assessing software quality metrics based on a scientific approach. It is demonstrated that performance optimisation enhances execution time by a factor of three with respect to the expected value.
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