As Search in testing is a most time consuming task which takes approximately 60% work load of the total software development time. If the testing is performed using automated testing then it will lead to reduce in software development cost by a significant margin. Metaheuristic search based testing techniques have been extensively used to automate the process of generating test cases and thus providing solutions for a more cost-effective testing process. Mobile Testing as a Service (known as Mobile TaaS a.k.a MTAAS) provides on-demand testing services for mobile applications and/or SaaS to support software validation and quality engineering processes by leveraging a cloud-based scalable mobile testing environment to assure pre-defined given QoS requirements and service-level-agreements (SLAs)”. Most“MTAAS are managed in an ad-hoc way with very limited mobile test automation tools. This approach offers the benefits of in-the-wild testing without the need to invest in a lab or purchase or rent devices, but at the risk of low testing quality and an uncertain validation schedule. In this paper a methodology is discussed based on Clonal Selection Based Optimization Approach that utilizes Crowed Sourcing.

Software testing , Search based testing ,Crowed Sourcing, Swarm Optimization

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