Multiobjective evolutionary algorithm test suites
Proceedings of the 1999 ACM symposium on Applied computing
Using genetic algorithms and coupling measures to devise optimal integration test orders
SEKE '02 Proceedings of the 14th international conference on Software engineering and knowledge engineering
Test Order for Inter-Class Integration Testing of Object-Oriented Software
COMPSAC '97 Proceedings of the 21st International Computer Software and Applications Conference
An Investigation of Graph-Based Class Integration Test Order Strategies
IEEE Transactions on Software Engineering
Data-Flow-Based Unit Testing of Aspect-Oriented Programs
COMPSAC '03 Proceedings of the 27th Annual International Conference on Computer Software and Applications
Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy
Evolutionary Computation
Coupling-based class integration and test order
Proceedings of the 2006 international workshop on Automation of software test
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Minimizing stub creation during integration test of aspect-oriented programs
Proceedings of the 3rd workshop on Testing aspect-oriented programs
Control and data flow structural testing criteria for aspect-oriented programs
Journal of Systems and Software
The Current State and Future of Search Based Software Engineering
FOSE '07 2007 Future of Software Engineering
An empirical study of cycles among classes in Java
Empirical Software Engineering
IEEE Transactions on Software Engineering
A Pareto ant colony algorithm applied to the class integration and test order problem
ICTSS'10 Proceedings of the 22nd IFIP WG 6.1 international conference on Testing software and systems
Establishing integration test orders of classes with several coupling measures
Proceedings of the 13th annual conference on Genetic and evolutionary computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Performance assessment of multiobjective optimizers: an analysis and review
IEEE Transactions on Evolutionary Computation
Search based design of software product lines architectures
Proceedings of the 34th International Conference on Software Engineering
Controversy Corner: Search Based Software Engineering: Review and analysis of the field in Brazil
Journal of Systems and Software
An orchestrated survey of methodologies for automated software test case generation
Journal of Systems and Software
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The integration test of aspect-oriented systems involves the determination of an order to integrate and test classes and aspects, which should be associated to a minimal possible stubbing cost. To determine such order is not trivial because different factors influence on the stubbing process. Many times these factors are in conflict and diverse good solutions are possible. Due to this, promising results have been obtained with multi-objective and evolutionary algorithms that generally optimize two coupling measures: number of attributes and methods. However, the problem can be more effectively addressed considering as many as coupling measures could be associated to the stubbing process. Therefore, this paper introduces MECBA, a Multi-Evolutionary and Coupling-Based Approach to the test and integration order problem, which includes the definition of models to represent the dependency between modules and to quantify the stubbing costs. The approach is instantiated and evaluated considering four AspectJ programs and four coupling measures. The results represent a good trade-off between the objectives and an example of use of the obtained results shows how they can be used to reduce test effort and costs.