Application of Different Metaheuristic Techniques for Finding Optimal Test Order During Integration Testing of Object Oriented Systems and their Comparative Study

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Provided by: Cornell University
Topic: Software
Format: PDF
In recent past, a number of researchers have proposed Genetic Algorithm (GA) based strategies for finding optimal test order while minimizing the stub complexity during integration testing. Even though, metaheuristic algorithms have a wide variety of use in various medium to large size optimization problems, their application to solve the Class Integration Test Order (CITO) problem has not been investigated. In this paper, the authors propose to find a solution to CITO problem by the use of a GA based approach. They have proposed a Class Dependency Graph (CDG) to model dependencies namely, association, aggregation, composition and inheritance between classes of Unified Modeling Language (UML) class diagram.
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