Regression Test Case Prioritization Technique Using Genetic Algorithm
Regression testing is a maintenance action in which it ensures validity of changed software. Regression testing takes much time to execute the entire test suite and this activity is very costly. In this paper we present a technique which is based on Genetic algorithms (GA) for test case prioritization. Genetic algorithm is a generative algorithm based on natural evolution which generate solutions to optimization problem. In this paper, a new Genetic algorithm is used for regression testing that will prioritize test cases using statement coverage technique. The Algorithm finds fitness function using statement coverage. The results shows the efficiency of algorithms with the help of Average Percentage of Statement Coverage (APSC) metric. This prioritization technique shows optimum results to prioritize the test case. Genetic Algorithm is used to produce the population and it finds the optimal sequence order of test case in regression testing.
Large-scale construction projects frequently appear which make people pay more attention to the performance evaluation.This paper established the large-scale construction projects'performance evaluation index system and carried out comprehensive evaluation of the performance with a combined model of fuzzy theory and the matter-element theory.The analytic hierarchy process and the membership function were used to determine the weights of indicator elements and the membership matter-element.Finally,the study used the performance indicator system in construction phase for a large-scale project as an example to verify the fuzzy matter-element correctness,rationality and feasibility.