Evolution of Test case Prioritization Approach in Software Testing and Role of Genetic Algorithm-Research in Progress

Numerous outgrowths can be noted such as effort, schedule as well as estimation of the testing. Hence, diversified approaches as well as methodologies have been anticipated for acquiring awareness of these outgrowths. Application of genetic algorithms for automatic test development has been a domain of attentiveness for many researchers. Genetic Algorithm (GA) is one analogous aspect of evolutionary algorithms. In this research paper, we evince contemplate of GA approach for approaching the diverse outgrowths dealt with during software testing. There is a confirmed curtailment between academic as well as practitioner convictions on software testing. This paper benchmarks to secure the gap by benchmarking both convictions regarding the merits and boundaries of test case Prioritization. The academic convictions are examined with a consistent literature review while the practitioner’s convictions are approximated with a survey, where we accumulated acknowledgments from plural software experts. The consequences of the balanced literature review materialize that the conception of apotheosis regarding merits and boundaries is quite superficial as only 30 papers ascribe the apotheosis. The survey emerged that merits of test case prioritization were accompanied to test case reusability, repeatability, test case coverage as well as effort reserved in test case executions. The boundaries were high alpha invests in Prioritization setup, tool preference along with educating. Comprehensively, 51% of the respondents accepted that feasible tools in the market assist a poor fit for expects and GA can be an alpha grade towards test case prioritization.