Future paths for integer programming and links to artificial intelligence
Computers and Operations Research - Special issue: Applications of integer programming
Incremental testing of object-oriented class structures
ICSE '92 Proceedings of the 14th international conference on Software engineering
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
A Test Strategy for Object-Oriented Programs
COMPSAC '95 Proceedings of the 19th International Computer Software and Applications Conference
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 Computation in Dynamic and Uncertain Environments (Studies in Computational Intelligence)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
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
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Survey: A survey on search-based software design
Computer Science Review
Integration test of classes and aspects with a multi-evolutionary and coupling-based approach
SSBSE'11 Proceedings of the Third international conference on Search based software engineering
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
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During the inter-class test, a common problem, named Class Integration and Test Order (CITO) problem, involves the determination of a test class order that minimizes stub creation effort, and consequently test costs. The approach based on Multi-Objective Evolutionary Algorithms (MOEAs) has achieved promising results because it allows the use of different factors and measures that can affect the stubbing process. Many times these factors are in conflict and usually there is no a single solution for the problem. Existing works on MOEAs present some limitations. The approach was evaluated with only two coupling measures, based on the number of attributes and methods of the stubs to be created. Other MOEAs can be explored and also other coupling measures. Considering this fact, this paper investigates the performance of two evolutionary algorithms: NSGA-II and SPEA2, for the CITO problem with four coupling measures (objectives) related to: attributes, methods, number of distinct return types and distinct parameter types. An experimental study was performed with four real systems developed in Java. The obtained results point out that the MOEAs can be efficiently used to solve this problem with several objectives, achieving solutions with balanced compromise between the measures, and of minimal effort to test.