An Optimized Test Case Minimization Technique Using Genetic Algorithm for Regression Testing

Regression testing is a widely used approach to confirm the correct functionality of the software in incremental development.The use of test cases makes it easier to test the ripple effect of changed requirements.Rigorous testingmay help in meeting the quality criteria that is based on the conformance to the requirements as given by the intended stakeholders.However,a minimized and prioritized set of test cases may reduce the efforts and time required for testingwhile focusing on the timely delivery of the software application.In this research,a technique named Test Reduce has been presented to get a minimal set of test cases based on high priority to ensure that the web applicationmeets the required quality criteria.A new technique TestReduce is proposed with a blend of genetic algorithm to find an optimized and minimal set of test cases.The ultimate objective associated with this study is to provide a technique that may solve the minimization problem of regression test cases in the case of linked requirements.In this research,the 100-Dollar prioritization approach is used to define the priority of the new requirements.

QoS Aware Multicast Routing Protocol for Video Transmission in Smart Cities

In recent years,Software Defined Networking(SDN)has become an important candidate for communication infrastructure in smart cities.It produces a drastic increase in the need for delivery of video services that are of high resolution,multiview,and large-scale in nature.However,this entity gets easily influenced by heterogeneous behaviour of the user’s wireless link features that might reduce the quality of video stream for few or all clients.The development of SDN allows the emergence of new possibilities for complicated controlling of video conferences.Besides,multicast routing protocol with multiple constraints in terms of Quality of Service(QoS)is a Nondeterministic Polynomial time(NP)hard problem which can be solved only with the help of metaheuristic optimization algorithms.With this motivation,the current research paper presents a new Improved BlackWidow Optimization with Levy Distribution model(IBWO-LD)-based multicast routing protocol for smart cities.The presented IBWO-LD model aims at minimizing the energy consumption and bandwidth utilization while at the same time accomplish improved quality of video streams that the clients receive.Besides,a priority-based scheduling and classifier model is designed to allocate multicast request based on the type of applications and deadline constraints.A detailed experimental analysis was carried out to ensure the outcomes improved under different aspects.The results from comprehensive comparative analysis highlighted the superiority of the proposed IBWO-LD model over other compared methods.