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Authors
Affiliations
1 Department of Information Technology, Pondicherry Engineering College, Puducherry, IN
Source
AIRCC's International Journal of Computer Science and Information Technology, Vol 3, No 1 (2011), Pagination: 213-223
Abstract
Search-based Software Engineering has been utilized for a number of software engineering activities. One area where Search-Based Software Engineering has seen much application is test data generation.
Evolutionary testing designates the use of metaheuristic search methods for test case generation. The search space is the input domain of the test object, with each individual or potential solution, being an encoded set of inputs to that test object. The fitness function is tailored to find test data for the type of test that is being undertaken.
Evolutionary Testing (ET) uses optimizing search techniques such as evolutionary algorithms to generate test data. The effectiveness of GA-based testing system is compared with a Random testing system. For simple programs both testing systems work fine, but as the complexity of the program or the complexity of input domain grows, GA-based testing system significantly outperforms Random testing.
Keywords
Search-Based Software Engineering, Evolutionary Algorithms, Optimization Problem, Evolutionary Testing, Meta-Heuristic Search Techniques.
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