Knowledge based non-functional software distinguishing quality effort estimation using fuzzy use case point approach

Abstract

Knowledge management along with data analytic process provides the collection of information which helps to examine both qualitative and quantitative software information. During the knowledge based data examination process, software effort estimation (SEE) is an organised approach to increase the efficiency of a software development process in various organisations. Software effort estimation based on use case point (UCP) methods provides only fixed estimation value which cannot deal with the uncertain and ambiguous conditions of the particular software. This work attempts to provide a fuzzy effort estimation procedure for use case model based on fuzzy inference rules. This paper also proposes a metric to calculate the enhanced UCPs with the fuzzy membership function for examining the software distinguishing quality. The proposed approach has been validated against the goal-driven UCP model, tree-boost model, Regression model and traditional use-case model. The obtained results show the better performance than those obtained by the existing methods.