Genetic Algorithm-Based Test Data Generation for Multiple Paths via Individual Sharing

Joint Authors

Yao, Xiangjuan
Gong, Dunwei

Source

Computational Intelligence and Neuroscience

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-12, 12 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-10-16

Country of Publication

Egypt

No. of Pages

12

Main Subjects

Biology

Abstract EN

The application of genetic algorithms in automatically generating test data has aroused broad concerns and obtained delightful achievements in recent years.

However, the efficiency of genetic algorithm-based test data generation for path testing needs to be further improved.

In this paper, we establish a mathematical model of generating test data for multiple paths coverage.

Then, a multipopulation genetic algorithm with individual sharing is presented to solve the established model.

We not only analyzed the performance of the proposed method theoretically, but also applied it to various programs under test.

The experimental results show that the proposed method can improve the efficiency of generating test data for many paths’ coverage significantly.

American Psychological Association (APA)

Yao, Xiangjuan& Gong, Dunwei. 2014. Genetic Algorithm-Based Test Data Generation for Multiple Paths via Individual Sharing. Computational Intelligence and Neuroscience،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1016738

Modern Language Association (MLA)

Yao, Xiangjuan& Gong, Dunwei. Genetic Algorithm-Based Test Data Generation for Multiple Paths via Individual Sharing. Computational Intelligence and Neuroscience No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-1016738

American Medical Association (AMA)

Yao, Xiangjuan& Gong, Dunwei. Genetic Algorithm-Based Test Data Generation for Multiple Paths via Individual Sharing. Computational Intelligence and Neuroscience. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1016738

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1016738