AbstractSoftware testing is a very important technique to design the faultless software and takes approximately 60% of resources for the software development. It is the process of executing a program or application to detect the software bugs. In software development life cycle, the testing phase takes around 60% of cost and time. Test case generation is a method to identify the test data and satisfy the software testing criteria. Test case generation is a vital concept used in software testing, that can be derived from the user requirements specification. An automatic test case technique determines automatically where the test cases or test data generates utilizing search based optimization method. In this paper, Cuckoo Search and Bee Colony Algorithm (CSBCA) method is used for optimization of test cases and generation of path convergence within minimal execution time. The performance of the proposed CSBCA was compared with the performance of existing methods such as Particle Swarm Optimization (PSO), Cuckoo Search (CS), Bee Colony Algorithm (BCA), and Firefly Algorithm (FA).

Network operators heavily depend on security services to secure their information technology infrastructures. On the other hand, due to the complexity of security policies, it is not appropriate to straightforwardly use previous pathwise enforcement approaches. In this paper, the enforcement problem of the security policy on middleboxes is formulated as a weighted K set covering problem that requires a policy space analysis tool. This tool is intended to be supported on range-represented hyperrectangles, which are tagged using a prioritized R-tree. This methodological work initially evaluates the topological features of diverse types of policies. Hybrid firefly bat algorithm-supported heuristic information shows the inherent difficulties of security policies and provides direction for the design of the enforcement algorithm. At the same time, a scopewise policy enforcement procedure is proposed, which requires a moderate number of enforcement network nodes for organizing the various policy subsets in a greedy manner. Our results demonstrate that the proposed hybrid firefly bat algorithm with policy space analysis offer greatly improved outcomes in terms of the rule overhead, network security, packet delivery ratio, packet loss ratio, and time efficiency above the set operations of the security policy. KEYWORDScomputer network, fuzzy rule, hybrid firefly bat algorithm, policy space analysis, security | INTRODUCTIONThe work performed by a network involves concepts such as security examination to protect their information technology environment. Diverse types of network security strategies are found worldwide and are dispersed among numerous security middleboxes organized in networks. Nevertheless, accomplishing high performance and implementing the security advantages of middleboxes are extremely difficult tasks. This difficulty thus demands a careful sketch of the network topology, which physically implements rules to direct the traffic in the preferred series of middleboxes and performs the exact procedure when malfunctions and overloads occur. 1 Software-defined networking (SDN) presents a promising choice for policy enforcement through sensibly centralized management, decoupling of information and control planes, and the capability to programmatically organize the forwarding rules. 2

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