Search- Based Test Data Generation for Object Oriented Programming

Test-data generation for object-oriented programming (OOP) is challenging due to the features of OOP, e.g., abstraction, encapsulation, and visibility that prevent direct access to some parts of the source code. To address this problem we present a new automated search-based software test-data generation approach that achieves high code coverage for the source code and reduces the search space. For that we first describe the test-data generation problem for object oriented testing to generate relevant sequences of method calls. In this paper, proposed technique uses means-of-instantiation, diversification strategy and seeding strategy for object oriented generation and sequence caller for search space reduction. Finally, we show that our technique is more efficient than the randomized technique as it reduces the search space better than the randomized one. It also uses a seeding strategy and a diversification strategy to increase the likelihood to reach a test target.