Forest Optimization-Based Test Case Generation for Multiple Paths With Metamorphic Relations

Abstract

In general multiple paths are covered by multiple runs which is a time consuming task. Now a days, metaheuristic techniques are widely used for path coverage. In order to reduce the time, an efficient method is proposed based on Forest Optimization Algorithm (FOA) with Metamorphic Relations (MRs) that cover multiple paths at a time in one run unlike the traditional search based testing. In the proposed approach, initial test case is generated using FOA, the successive test cases are generated using MRs without undergoing several runs. The motive of using FOA is that the searching mechanism of this algorithm having resemblance with the branch / path coverage techniques of testing. To the best of our knowledge, FOA has not been implemented in software testing. The experimental results are compared with three existing work. The efficiency of simply FOA is also shown how it able to cover multiple paths. The results show that FOA with MRs is more efficient in terms of time consumption and number of paths covered.

Object-Oriented Test Case Generation Using Teaching Learning-Based Optimization (TLBO) Algorithm

“…The cuckoo search and bee colony algorithm (CSBCA) achieved a higher fitness function value of 0.7 to 1.0 in 65 percent of test cases/test data than the particular swarm optimization (PSO), cuckoo search algorithm (CS), firefly algorithm (FA), and bee colony algorithm (BCA). Sahoo, (2022) [35] proposed a new approach, the forest optimization algorithm (FOA) with metamorphic relations (MRS), to cover multiple paths at a time in one run. The initial test case was created with FOA, and the subsequent test cases were created with metamorphic relations without going through many runs.…”