抽象的

Functional Testing Technique Using ODC to Identify And Predict Faults

K.Sivaprakash, Prof. Preethi harris

The type of faults in software testing techniques may differ and are more prone to detect. Based upon the features of the application under test, their performance varies. The current methodology like Novel Fault Classification Scheme, used to identify and classify faults based on least square software vector machine in software application. The Novel Classification Scheme based on least square SVM may requires more time and also with less accurateness. The Genetic algorithms are used to generate the test cases and fitness of each test case has been determined individually. The Orthogonal Defect Classification (ODC) mechanism identifies the faults and classifies based on the fault types for the given set of generated test cases through the genetic algorithm. The testing techniques such as functional testing, statistical testing, robustness testing and stress testing are utilized to classify the faults based on their types. Besides, the difficulty of switching among the techniques has been resolved using the Markov Decision Process (MDP) that maximizes the number of faults. The classification of the faults may be varied based upon the testing technique that has been utilized. The performance of the ODC fault classification mechanism and classification system is analyzed through the percentage of faults identified and classified based on the ODC mechanism.