Investigating soft computing in case-based reasoning for software cost estimation

Software cost estimation has been the subject of intensive investigations in the field of software engineering. As a result, numerous software cost estimation techniques have been proposed and investigated. To our knowledge, currently there are no cost estimation techniques that can incorporate and/or tolerate the aspects of imprecision, vagueness, and uncertainty into their predictions. However, software projects are often described by vague information. Furthermore, an estimate is only a probabilistic assessment of a future condition. Consequently, cost estimation models must be able to deal with imprecision and uncertainty, the two principal components of soft computing. To estimate the cost of software projects when they are described by vague and imprecise attributes, in an earlier study we have proposed an innovative approach referred to as Fuzzy Analogy. In this paper, we investigate the uncertainty of cost estimates generated by the Fuzzy Analogy approach. The primary aim is to generate a set of possible values for the actual software development cost. This set can then be used to deduce, for practical purposes, a point estimate for the cost, and for analyzing the risks associated with all possible estimates.