Selecting Software Test Data Using Data Flow Information
IEEE Transactions on Software Engineering
Software testing techniques (2nd ed.)
Software testing techniques (2nd ed.)
Incremental testing of object-oriented class structures
ICSE '92 Proceedings of the 14th international conference on Software engineering
Object-oriented integration testing
Communications of the ACM
Integrated object-oriented testing and development processes
Communications of the ACM
Design for testability in object-oriented systems
Communications of the ACM
On regression testing of object-oriented programs
Journal of Systems and Software
Object-oriented software engineering with Eiffel
Object-oriented software engineering with Eiffel
Self-Testable Components: From Pragmatic Tests to Design-for-Testability Methodology
TOOLS '99 Proceedings of the Technology of Object-Oriented Languages and Systems
Testing levels for object-oriented software
Proceedings of the 22nd international conference on Software engineering
ECOOP '01 Proceedings of the 15th European Conference on Object-Oriented Programming
Building Trust into OO Components Using a Genetic Analogy
ISSRE '00 Proceedings of the 11th International Symposium on Software Reliability Engineering
Design by Contract to Improve Software Vigilance
IEEE Transactions on Software Engineering
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In this paper, we present a model, a strategy and a methodology for planning integration and regression testing from an OO model. We show how to produce a model of structural system test dependencies which evolves with the refinement process of the OO design. The model, that is the test dependency graph, serves as a basis for ordering classes and methods to be tested for regression and integration purposes (minimization of test stubs. The mapping from UML to the defined model is detailed as well as the test methodology. While the complexity of optimal stub minimization is exponential with the size of the model, an algorithm which computes a strategy for integration testing with a quadratic complexity is detailed This algorithm provides an efficient testing order for minimizing the number of stubs. A comparison is given of various integration strategies with the proposed optimized algorithm (a real-world case study illustrates this comparison). The results of the experiments seem to give nearly optimal stubs with a low cost despite the exponential complexity of getting optimal stubs.