An Efficient Requirement-based Test Case Prioritization Technique using Optimized TFC-SVM Approach
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2021 by IJETT Journal|
|Year of Publication : 2021|
|Authors : Omdev Dahiya, Kamna Solanki
|DOI : 10.14445/22315381/IJETT-V69I1P202|
MLA Style: Omdev Dahiya, Kamna Solanki "An Efficient Requirement-based Test Case Prioritization Technique using Optimized TFC-SVM Approach" International Journal of Engineering Trends and Technology 69.1(2021):5-16.
APA Style:Omdev Dahiya, Kamna Solanki. An Efficient Requirement-based Test Case Prioritization Technique using Optimized TFC-SVM Approach International Journal of Engineering Trends and Technology, 69(1),5-16.
Software testing is an essential and challenging part of the SDLC (Software Development Life Cycle). Requirement-based TCP (Test case prioritization) is a method to optimize the execution time, cost, and effort as an essential part of the regression testing. It is a technique used to arrange the test cases (TCs), and sorting of the TC’s is based on some criteria. It is established to execute the high priority test cases initially to reduce the execution time, efforts, and cost during the software testing. Thus, conventional TCP (Test Case Prioritization) is motivated to design for testing the software to enhance prioritization efficiency. TCP permits the testers to classify the test cases as the priority for performing the test execution. It helps in enhancing software quality. In the existing research, the authors had developed a method to prioritize the optimal test cases using the firefly approach. They used the firefly algorithm to optimize the ordering of the test cases and fitness value (FV), defined through the same distance model, to have better performance. The firefly’s approach may be more efficient in determining fault proneness problems, which is intensely required in security-critical schemes. Thus, the proposed research deals with the processing of the non-linear approach that provides high classification rates. A TFC-SVM algorithm is a novel approach deal with the CUCKOO optimization in collaboration with SVM, used to achieve higher classification rates in terms of high mean, median, and low minimum value. Afterward, training and testing modules are considered through the classification approach and processed the requirements-based in TCP. The proposed model has resolved the existing issues such as error rates, high priorities, and maximum execution time to prioritize processed requirement-based on test case prioritization. The proposed parameters are evaluated using computation time, APFD, Mean, Standard Deviation, Min, and Max values through which the performance metrics can be achieved for the robust proposed system.
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Requirement-based Test Case Prioritization, TFC-SVM method, FA (Firefly Algorithm), and APFD metric.