Fuzzy Case-Based Reasoning Models for Software Cost Estimation

Providing a timely estimation of the likely software development effort has been the focus of intensive research investigations in the field of software engineering, especially software project management. As a result, various cost estimation techniques have been proposed and validated. Due to the nature of the software-engineering domain, software project attributes are often measured in terms of linguistic values, such as very low, low, high and very high. The imprecise nature of such attributes constitutes uncertainty and vagueness in their subsequent interpretation. We feel that software cost estimation models should be able to deal with imprecision and uncertainty associated with such values. However, there are no cost estimation models that can directly tolerate such imprecision and uncertainty when describing software projects, without taking the classical intervals and numeric-values approaches. This chapter presents a new technique based on fuzzy logic, linguistic quantifiers, and analogy-based reasoning to estimate the cost or effort of software projects when they are described by either numerical data or linguistic values. We refer to this approach as Fuzzy Analogy. In addition to presenting the proposed technique, this chapter also illustrates an empirical validation based on the historical COCOMO’81 software projects data set.