Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
BINTEST - Binary Search-based Test Case Generation
COMPSAC '03 Proceedings of the 27th Annual International Conference on Computer Software and Applications
Genetic Programming and Evolvable Machines
Test input generation with java PathFinder
ISSTA '04 Proceedings of the 2004 ACM SIGSOFT international symposium on Software testing and analysis
Evolutionary testing of classes
ISSTA '04 Proceedings of the 2004 ACM SIGSOFT international symposium on Software testing and analysis
Using evolutionary algorithms for the unit testing of object-oriented software
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Evolutionary Testing Using an Extended Chaining Approach
Evolutionary Computation
Evolutionary unit testing of object-oriented software using strongly-typed genetic programming
Proceedings of the 8th annual conference on Genetic and evolutionary computation
CUTE and jCUTE: concolic unit testing and explicit path model-checking tools
CAV'06 Proceedings of the 18th international conference on Computer Aided Verification
Symstra: a framework for generating object-oriented unit tests using symbolic execution
TACAS'05 Proceedings of the 11th international conference on Tools and Algorithms for the Construction and Analysis of Systems
Search-based software testing and test data generation for a dynamic programming language
Proceedings of the 13th annual conference on Genetic and evolutionary computation
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Automating the generation of object-oriented unit tests is a challenging task. This is mainly due to the complexity and peculiarities that the principles of object-orientation imply. One of these principles is the encapsulation of class members which prevents non-public methods and attributes of the class under test from being freely accessed. This paper suggests an improvement of our automated search-based test generation approach which particularly addresses the test of non-public methods. We extend our objective functions by an additional component that accounts for encapsulation. Additionally, we propose a modification of the search space which increases the efficiency of the approach. The value of the improvement in terms of achieved code coverage is demonstrated by a case study with 7 real-world test objects. In contrast to other approaches which break encapsulation in order to test non-public methods, the tests generated by our approach inherently guarantee that class invariants are not violated. At the same time, refactorings of the encapsulated class members will not break the generated tests