A Novel Approach for Efficient Selection of Test Case Prioritization Techniques
Pages : 582-586
Download PDF
Abstract
Test case prioritization techniques schedule test cases to lessen the cost of regression checking out and to maximize a few objective function. Test cases are prioritized such that those check cases which are more important under some standards are executed in advance in regression checking out procedure. Test case prioritization allows to improve the effectiveness of Regression Testing. However, running all the take a look at cases in the test suite is prohibitive in most instances. Optimization of test case execution time to maximize the early fault detection rate of the original test suite will assist to decrease the rate of regression testing. Because of the resource and time constraint, it turns into necessary to broaden some strategies which help to minimize existing take a look at suites by disposing of redundant test instances and prioritizing them. We make the preparation and test information via robotized change of User interface segments taken from the page wireframes. In light of the plan rules and the test varieties, we present potential defects in direct connection to the structure input. In light of the preparation information and the multifaceted nature of our situations, various models, for example, Reinforcement Learning and ANN can be picked. When the model is concluded, we can prepare our model to catch UI absconds. Along these lines, we can accomplish more prominent gauges as far as upgraded Test advancement inclusion of UI segments. The main purpose in the back of is the absence of hints for the selection of TCP strategies. Hence, this piece of research introduces a novel technique for class of Test case prioritization strategies the usage of fuzzy common sense to assist the efficient selection of test case prioritization strategies. This work is an expansion of as of now proposed determination outline for experiment prioritization procedures.
Keywords: Test case prioritization (TCP), User Interface, Regression testing, fuzzy method, Optimization.