Evaluating different strategies for integration testing of aspect-oriented programs

Background: The determination of an order for integration and testing of aspects and classes is a difficult optimization problem. This order should be associated to a minimal possible stubbing cost. To determine such order, different approaches exist. For example, traditional approaches are based on Tarjan’s algorithm; search-based approaches are based on metaheuristics, usually genetic algorithms (GA). In addition to such approaches, in the literature, there are different strategies to integrate aspect-oriented software. Some works suggest the integration of aspects and classes in a combined way. Other ones adopt an incremental strategy. Studies evaluating the approaches show that the multi-objective one presents better solutions. However, these studies were conducted applying only the combined strategy. Methods: In this paper, we present experimental results comparing both strategies with three different approaches: the traditional one, a simple GA-based, and a multi-objective one. Results: The results show better performance of the multi-objective approach independently of the strategy adopted. A comparison of both strategies points out that the incremental strategy reaches a lower cost in most cases, considering a number of attributes and operations to be emulated in the stub. Conclusion: It seems that with Incremental+, the best choice is the multi-objective approach. If the system is very complex, PAES seems to be the best MOEA. © 2014, Assunção et al.; licensee Springer.