Fuzzy-Logic Modeling Approach for System Requirements Management

modeling approach. Based on the concept of multi-dimensional information space presented in [TSM04], we p ropose to consider so-called state space for system requirements (SR) called further as �-space. The dimensions of � should describe a current state of a SR for any application domain in some problem-independent and unified manner. In order to establish such a description for any SR, the following three criteria are introduced, namely: C1-Completeness of Specification, it defines the degree of requirements completeness in some project; C2- Level of Formalization, it indicates the formalizing degree of given SR; C3- Measure of Agreement, it shows to which degree the stakeholders (domain experts, analysts, programmers, etc.) are agreed from their points of view to SR in p roject considered. These criteria C1-C3 are really complex and weakly formalized. Basically, the criteria values C1-C3 are orthogonal logically because some project’s state is possible, when there is the completed functional description of given SR (it means C1=C1max), but the level of it’s formalization is low (C2=C2 min), and in addition to this the measure of coordination is also very poor (i.e., C3 = C3min); in the same way all others logical combinations of criteria values C1-C3 could be constructed, etc. If criteria values of C1-C3 are fuzzy defined, the �-space is the fuzzy set, and it could be defined as subset from Cartesian product of those fuzzy sets, namely: � � D(C1) � D(C2) � D(C3) where: D(C i), i � [1,3]- is a fuzzy set (a values domain) of the appropriate criteria. Furthermore, because of the criteria C3: Measure of Consistency, each point in the �-space represents some alternative estimation (further-an alternative) for a given SR: a value a i. We describe the criteria C1-C3 using linguistic variables (LV), which are defined in fuzzy set �.In this way the new subspace A � C1� C2