Usability Prediction: A Fuzzy Approach

M.K. Donyaee, J. Rilling, and A. Seffah (Canada)


Software Metrics, Prediction, Fuzzy Modelling and Usability. Table 1. Usability prediction models


For software products to succeed they have to satisfy customer expectations, including usability aspects of the software. Early during the development cycle important design decisions are made for projects that are typically on restricted schedules and budgets. There is a need to support this decision-making process, by empowering the decision makers with better tools and techniques. In this research we present a prediction approach that allows potential stakeholders to examine and choose among different user interfaces based on our usability prediction model. The research tries to establish correlations between predictive usability metrics and the results of usability tests performed by users on 8 COTS systems. The correlations are expressed in the form of fuzzy models. Fuzzy models have been proven to be convenient in decision-making processes. The remaining paper is organized as follows. Section 2 will discuss related work with respect to usability predication. Section 3 will present the methodology on which our usability prediction models are based. Section 4 presents the process of building fuzzy models and we present the results and discussion in section 5. Section 6 describes the limitations of predictive models. And finally Conclusions and future work are presented in section 7. 2. Related Work In this section we introduce a classification of current usability prediction methods and analyze their impacts, their advantages and challenges during system development. Table 1 shows the categories of existing prediction models and their respective methods. We would like to note that the list of methods is not exhaustive and it just presents examples in each category.

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