Evolutionary algorithms for object-oriented test data generation

2014 ◽  
Vol 39 (4) ◽  
pp. 1-6 ◽  
Author(s):  
Yeresime Suresh ◽  
Santanu Ku. Rath
Keyword(s):  
Evolutionary Algorithms ◽  
Test Data ◽  
Object Oriented ◽  
Test Data Generation ◽  
Data Generation

scholarly journals Evolutionary algorithms for path coverage test data generation and optimization: a review

2019 ◽  
Vol 15 (1) ◽  
pp. 504
Author(s):  
Deepti Bala Mishra ◽  
Arup Abhinna Acharya ◽  
Rajashree Mishra
Keyword(s):  
Evolutionary Algorithms ◽  
Test Data ◽  
Automatic Testing ◽  
Test Case ◽  
Test Data Generation ◽  
Data Generation ◽  
Branch Coverage ◽  
Path Testing ◽  
Path Coverage ◽  
Manual Testing

Software testing is very time consuming, labor-intensive and complex process. It is found that 50% of the resources of the software development are consumed for testing. Testing can be done in two different ways such as manual testing and automatic testing. Automatic testing can overcomes the limitations of manual testing by decreasing the cost and time of testing process. Path testing is the strongest coverage criteria among all white box testing techniques as it can detect about 65% of defects present in a SUT. With the help of path testing, the test cases are created and executed for all possible paths which results in 100% statement coverage and 100% branch coverage .This paper presents a systematic review of test data generation and optimization for path testing using Evolutionary Algorithms (EAs). Different EAs like GA, PSO, ACO, and ABCO based methods has been already proposed for automatic test case generation and optimization to achieve maximum path coverage.

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