A Comparative Study of Two Fuzzy Logic Models for Software Development Effort Estimation

Software development effort estimation (SDEE) has been the focus of research in recent years. No single software development estimation technique is best for all situations and linear regression (LR) has frequently been used for both small and industrial software projects. Fuzzy logic (FL) has been applied as an alternative technique to SDEE using a Mamdani Model. In order to compare the estimation accuracy of the Mamdani and Takagi-Sugeno fuzzy systems with that of an LR model, a sample of small projects was used to generate two FL models and an LR equation. Then the FL models and the LR equation were validated by estimating the effort of projects elaborated by other developers. This latter group of projects was subdivided into projects with Effort<100 and Effort ≥100 (as it has been demonstrated that the estimation accuracy depends on the effort, which is an amount of time in human-hours). The results showed that the Takagi-Sugeno fuzzy system was more accurate than the Mamdani system and the LR model for SDEE of projects with Effort 100. It can be concluded that a Takagi-Sugeno fuzzy system can be useful for estimating the effort of projects with Effort≥100 when they have been individually developed on a disciplined process.