Integrating Speci cations A Similarity Reasoning Approach

Requirements analysis usually results in a set of di erent speci cations for the same system which must be integrated Integration involves the detection and elimination of discrepancies between them Discrepancies may be due to di erences in representation models modeling perspectives or practices As instances of the semantic heterogeneity problem D Gangopadhyay and T Barsalou discrepancies are broader than logical inconsistencies and therefore not always detectable using theorem proving This paper proposes an approach to their detection using meta modeling and similarity analysis Speci cation components are classi ed under a meta model of domain independent semantic modeling abstrac tions and thereby compared according to a newly developedmodel of similarity Similarity analysis results in an isomorphic mapping between them which can be used as a basis for reconciling and merging them The approach is extensible in the sense that it accommodates di erent models for representing speci cations and analysis scales up to manage large complex speci cations because the complexity of similarity analysis is polynomial