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Data Flow Testing of UML State Machine Using Ant Colony Algorithm (ACO)


Abdul Rauf


Vol. 17  No. 10  pp. 40-44


Automatic data flow testing refers to analysis of flow of data within models by using data flow analysis rules. To ensure correct data flow within states we have to consider these data values. The data flow analysis (DFA) forms a source of testing data flow (DFT) by considering defines and uses of the variables. State-based testing examines state changes and its behavior without focusing on the internal details, thus data faults remain uncovered. Empirical studies have shown that existing state- based approaches are not efficient in detecting state based faults. In this paper, an approach is presented to enhance fault detection capability state based approaches. All definition-use paths are used as coverage criterion. We implemented this approach in a tool named data flow generator (DFG). Tool enhances fault detection capability of state based approaches by efficiently detects data flow errors and generates optimal number of feasible test cases are automatically to provide complete def-use paths coverage.


State-Based approaches, Data Flow Testing, Coverage Criteria, Data flow testing