A Hyper-heuristic for Multi-objective Integration and Test Ordering in Google Guava
Integration testing seeks to find communication problems between different units of a software system. As the order in which units are considered can impact the overall effort required to perform integration testing, deciding an appropriate sequence to integrate and test units is vital. Here we apply a multi-objective hyper-heuristic set within an NSGA-II framework to the Integration and Test Order Problem (ITO) for Google Guava, a set of open-source common libraries for Java. Our results show that an NSGA-II based hyper-heuristic employing a simplified version of Choice Function heuristic selection, outperforms standard NSGA-II for this problem.
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