There is a growing body of evidence to suggest that significant benefits may be gained from augmenting current approaches to software development effort estimation, and indeed other project management activities, with models developed using fuzzy logic and other soft computing methods. The tasks undertaken by project managers early in a development process would appear to be particularly amenable to such a strategy, particularly if fuzzy logic models are used in a complementary manner with other algorithmic approaches, thus providing a range of predictions as opposed to a single point value. As well as providing a more intuitively acceptable set of estimates, this would help to reduce or remove the unwarranted level of certainty associated with a point estimate. Furthermore, such an approach would enable organizations to "store" their project management knowledge, making them less susceptible to employee resignations and the like. If fuzzy logic modeling is to be implemented in industry, however, managers must first believe it to be a realistic and workable option. This issue is addressed here by considering two related questions: one, what expectations do project managers have in relation to effort estimation? And two, what is their opinion of the methods that might be useful in this regard? This is followed by a discussion of the results of two surveys of project managers aimed at deriving membership functions using polling methods, the first using an interval declaration approach and the second using votes on fixed points. It is concluded that there is indeed support in the software engineering practitioner community for the use of methods based on the principles of fuzzy logic modeling.
A Comparative Study of Two Fuzzy Logic Models for Software Development Effort Estimation
