By Stefan Bärisch
ISBN-10: 3834809314
ISBN-13: 9783834809315
Software program reuse and software program caliber are more and more very important issues in brand new software program engineering either for researchers and for practitioners. The layout and implementation of checks is principally demanding while assessments are conceptualized for various variations and types of an program. Stefan Baerisch applies a mix of function modeling and code new release, for which he makes use of a model-driven technique, that allows you to facilitate the layout of assessments by way of non-programmers. hence, the reuse of exams, represented through summary try out versions, for various structures below assessments is made attainable. The technique makes use of code new release to permit try out execution on heterogeneous and altering implementations. this mix of modeling and code new release enables a extra built-in and extra effective trying out technique.
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Additional info for Domain-Specific Model-Driven Testing
Sample text
Since MTCC takes an external, responsibility-based view of testing, details regarding the theory and implementation of the retrieval model used by the testee are neither available to MTCC nor of interest to acceptance tests. We therefore limit our discussion to the differences between the Boolean retrieval model and retrieval models that support the ranking of results by relevance. The subjects of retrieval models are not an information need and documents but rather queries and document surrogates.
Feature models facilitate the representation ble parameterization of of the supported features and combinations of features of the members of a system family in an formal, hierarchical way. Feature models define operations that allow derivations of a feature model that represents a more constrained variability. Specialization operations perform local transformations on the feature model that result in a more specific feature model. A fully specialized feature model is a configuration [CHE05b, CHE05c].
Structural heterogeneity is a relevant problem outside the domain of Digital Libraries [Has97, Has02, PH04]. Rahm and Bernstein [RB01] give an overview of the challenges imposed by structural heterogeneity and outline some approaches to their solution. Semantic heterogeneity is caused by the use of different Knowledge Organization Systems (KOS) like thesauri, classifications and subject lists for the different databases. Since a user of a Digital Library cannot be expected to be familiar with multiple KOSs, it is important to make the different KOSs used in a Digital Library interoperable [ZC04].
Domain-Specific Model-Driven Testing by Stefan Bärisch
by Paul
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