Object-oriented methods define a considerable number of rules, which are generally expressed using two-valued logic. Far example, an entity in a requirement specification is either accepted or rejected as a class. There are two major problems how rules are defined and applied in current methods. Firstly, two-valued logic cannot effectively express the approximate and inexact nature of a typical software development process. Secondly, the influence of contextual factors on rules is generally not modeled explicitly. This paper terms these problems as quantization error and contextual bias problems, respectively. To reduce these problems, we adopt fuzzy logic-based methodological rules. This approach is method independent and is useful for evaluating and enhancing current methods. In addition, the use of fuzzy-logic increases the adaptability and reusability of design models.
Reducing quantization error and contextual bias problems in software development processes by applying fuzzy logic
MARCELLONI, FRANCESCO;
1999-01-01
Abstract
Object-oriented methods define a considerable number of rules, which are generally expressed using two-valued logic. Far example, an entity in a requirement specification is either accepted or rejected as a class. There are two major problems how rules are defined and applied in current methods. Firstly, two-valued logic cannot effectively express the approximate and inexact nature of a typical software development process. Secondly, the influence of contextual factors on rules is generally not modeled explicitly. This paper terms these problems as quantization error and contextual bias problems, respectively. To reduce these problems, we adopt fuzzy logic-based methodological rules. This approach is method independent and is useful for evaluating and enhancing current methods. In addition, the use of fuzzy-logic increases the adaptability and reusability of design models.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
