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.
Highlights
Testing is a very labour intensive task and consumes 40-70% of time and resources of software development process (Khana et al 2019)
The results show that Forest Optimization Algorithm (FOA) with metamorphic relations (MRs) is more efficient in terms of time consumption and number of paths covered
The comparative results using two fitness functions, traditional fitness (BD+AL) and Improved Combined Fitness (ICF) function with FOA are shown in Table 4, Table 5 and Table 6 respectively
Summary
Testing is a very labour intensive task and consumes 40-70% of time and resources of software development process (Khana et al 2019). Test case generation is best fitted to a multi objective problem. FOA proposed by Manizheh Ghaemi and Mohammad-RezaFeizi-Derakhshi (Ghaemi & FeiziDerakhshi, 2014). This algorithm is inspired by the trees which survive for many decades. The objective of the algorithm is to search for a tree (candidate solution) in the forest (set of candidate solutions) which survives for a long time. It simulates the seeding procedure of nature in a forest. Dispersal of seeds far away from the parent tree, incorporates global searching.
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