1 Analogy-Based Software Effort Estimation Using Fuzzy Numbers

Context: Software effort estimation at early stage is a crucial task for project bedding and feasibility study. Since collected data at early stage of software development lifecycle is always imprecise and uncertain, it is very hard to deliver accurate estimate. Analogy-based estimation, which is one of the popular estimation methods, is rarely used at early stage because of uncertainty associated with attribute measurement and data availability. Objective: in order to improve performance of analogy-based estimation at early stage, using all available early data, we integrated it with Fuzzy numbers. Particularly, this paper proposes a new software project similarity measure and a new adaptation technique based on Fuzzy numbers in order to support analogy-based estimation at early stage of software development lifecycle. Method: Empirical evaluation with Jack-knifing procedure carried out, using five benchmark data sets of software projects, namely, ISBSG, Desharnais, Kemerer, Albrecht and COCOMO, are reported. The results are compared to those obtained by methods employed in the literature using case-based reasoning and stepwise regression. Results: In all data sets the empirical evaluations have shown that the proposed similarity measure and adaptation techniques method were able to remarkably improve the performance of analogy-based estimation at early stage of software development. The results have also shown the proposed method outperforms some well know estimation techniques such as case-based reasoning and stepwise regression. Conclusions: It is concluded that the proposed estimation model could form a useful approach for early stage estimation especially when data is almost uncertain