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UCMs (Use Case Maps) model describes functional requirements and high-leveldesigns with causal paths superimposed on a structure of components. It couldprovide useful resources for software acceptance testing. However until nowstatistical testing technologies for large scale software is not considered yetin UCMs model. Thus if one applies UCMs model to a large scale software usingtraditional coverage based exhaustive tasting, then it requires too much costsfor the quality assurance. Therefore this paper proposes an importance analysisof UCMs model with Markov chains. With this approach not only highly frequentlyused usage scenarios but also important objects such as components,responsibilities, stubs and plugins can also be identified from UCMsspecifications. Therefore careful analysis, design, implementation andefficient testing could be possible with the importance of scenarios andobjects during the full software life cycle. Consequently product reliabilitycan be obtained with low costs. This paper includes an importance analysismethod that identifies important scenarios and objects and a case study toillustrate the applicability of the proposed approach.

The Importance Analysis of Use Case Map with Markov Chains