PSO Based Pseudo Dynamic Method for Automated Test Case Generation Using Interpreter

Singh, Surender; Chhabra, Jitender Kumar; Kumar, Surendra

doi:10.1007/978-3-642-21515-5_18

Cited by 7 publications

(4 citation statements)

References 16 publications

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“…The results showed that APSO had better performance than basic PSO. Dahiya et al [8] proposed PSO based hybrid testing technique and solved many of the structural testing problems such as dynamic variables, input dependent array index, abstract function calls, infeasible paths and loop handling. Singla et al [10] presented a technique that based on a combination of genetic algorithm and particle swarm algorithm.…”

Section: Related Workmentioning

confidence: 99%

“…If the individual fitness f i is less than the first average fitness f avg , we think that the particles performance of this part is poorer in the population. We can adjust w_i according to the particle aggregationn degree in formula (8). So when f g ¼f 0 avg , w_i takes the maximum, w_i¼c-0.5 and the range of w_i is [w min , c-0.5].…”

Section: Adaptive Adjustment Scheme Based On Inertia Weightmentioning

confidence: 99%

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Automatic test data generation based on reduced adaptive particle swarm optimization algorithm

et al. 2015

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Section: Related Workmentioning

confidence: 99%

Section: Adaptive Adjustment Scheme Based On Inertia Weightmentioning

confidence: 99%

Automatic test data generation based on reduced adaptive particle swarm optimization algorithm

et al. 2015

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“…Search-based technology is used to search for data automatically. For example, Particle Swarm Optimization (PSO) [7,8], Difference Evolutionary algorithm (DE) [9][10][11], Artificial Bee Colony algorithm (ABC) [12,13], Firework Algorithm (FA) [14] are applied by scholars. They convert test data generation problems into combinatorial optimization problems and evolve to generate test data that meet the requirements.…”

Section: Introductionmentioning

confidence: 99%

An Evolutionary Generation Method of Test Data for Multiple Paths Based on Coverage Balance

et al. 2021

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Test data generation is one of the main tasks of software testing. The goal of test data generation based on search algorithms is to automate the task and find test data that meet test criteria. In this study, an evolutionary generation method for test data that cover multiple paths is proposed. Firstly, the method obtains the coverage balance for each target path based on the number of individuals traversing the true and false branches of branch nodes, and calculates the individual's influence on coverage balance before and after an individual joining based on our previous work. Then, according to the number of branch nodes on each target path, the weights of different target paths are designed to obtain the individual fitness to adjust the evolution process and quickly generate test data covering multiple target paths. Finally, the proposed method is compared with existing techniques. Experimental results of benchmark programs and industrial use cases show that the proposed method can effectively improve the efficiency of test data generation for multiple paths.

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“…Dahiya et al [18] proposed a PSObasedhybrid testing technique and solved many of the structural testingproblems such as dynamic variables, input dependent array index,abstract function calls, infeasible paths and loop handling.…”

Section: Related Workmentioning

confidence: 99%

Generating Test Data for Software Structural Testing using Particle Swarm Optimization

Thi

2017

JCSCE

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Search-based test data generation is a very popular domain in the field of automatic test data generation. However, existing search-based test data generators suffer fromsome problems. By combining static program analysis and search-based testing, our proposed approach overcomesone of these problems. Considering the automatic ability and the path coverage as the test adequacycriterion, this paper proposes using Particle Swarm Optimization, an alternative search technique, for automating the generation of test data for evolutionary structural testing. Experimental results demonstrate that our test data generator can generate suitable test data with higher path coverage than the previous one.

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PSO Based Pseudo Dynamic Method for Automated Test Case Generation Using Interpreter

Cited by 7 publications

References 16 publications

Automatic test data generation based on reduced adaptive particle swarm optimization algorithm

Automatic test data generation based on reduced adaptive particle swarm optimization algorithm

An Evolutionary Generation Method of Test Data for Multiple Paths Based on Coverage Balance

Generating Test Data for Software Structural Testing using Particle Swarm Optimization

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