Indian Journal of Science and Technology

Open Access Open Access  Restricted Access Subscription Access

A Review of Random Test Case Generation using Genetic Algorithm


Affiliations
1 School of Computer Engineering, KIIT University, Bhubaneswar – 751024, Odisha, India
2 School of Applied Sciences, KIIT University, Bhubaneswar – 751024, Odisha, India
 

Background/Objectives: This research paper presents how Genetic algorithm is efficiently used in random test case generation during functional software testing. Methods/Statistical Analysis: Different hybridized Genetic Algorithms are used to generate test data automatically and optimized those test cases to solve many complex problem related to software testing. Findings: Genetic Algorithms are successfully used in software testing with increasing number of test case generation and provides a means of an automatic test case generator. Applications/Improvements: This study gives us a brief idea to implement Genetic Algorithms in software testing for optimum results and also it can be used with the neural networks and fuzzy systems for different types of testing to improve the performance.

Keywords

Black-Box Testing, Fitness Function, Genetic Algorithm (GA), Neural Network, Software Testing, Test case Generation
User

Abstract Views: 120

PDF Views: 0




  • A Review of Random Test Case Generation using Genetic Algorithm

Abstract Views: 120  |  PDF Views: 0

Authors

Deepti Bala Mishra
School of Computer Engineering, KIIT University, Bhubaneswar – 751024, Odisha, India
Saurabh Bilgaiyan
School of Computer Engineering, KIIT University, Bhubaneswar – 751024, Odisha, India
Rajashree Mishra
School of Applied Sciences, KIIT University, Bhubaneswar – 751024, Odisha, India
Arup Abhinna Acharya
School of Computer Engineering, KIIT University, Bhubaneswar – 751024, Odisha, India
Samaresh Mishra
School of Computer Engineering, KIIT University, Bhubaneswar – 751024, Odisha, India

Abstract


Background/Objectives: This research paper presents how Genetic algorithm is efficiently used in random test case generation during functional software testing. Methods/Statistical Analysis: Different hybridized Genetic Algorithms are used to generate test data automatically and optimized those test cases to solve many complex problem related to software testing. Findings: Genetic Algorithms are successfully used in software testing with increasing number of test case generation and provides a means of an automatic test case generator. Applications/Improvements: This study gives us a brief idea to implement Genetic Algorithms in software testing for optimum results and also it can be used with the neural networks and fuzzy systems for different types of testing to improve the performance.

Keywords


Black-Box Testing, Fitness Function, Genetic Algorithm (GA), Neural Network, Software Testing, Test case Generation



DOI: https://doi.org/10.17485/ijst%2F2017%2Fv10i30%2F158521