Grammatical Evolution for the Multi-Objective Integration and Test Order Problem

Abstract

Search techniques have been successfully applied for solving different software testing problems. However, choosing, implementing and configuring a search technique can be hard tasks. To reduce efforts spent in such tasks, this paper presents an offline hyper-heuristic named GEMOITO, based on Grammatical Evolution (GE). The goal is to automatically generate a Multi-Objective Evolutionary Algorithm (MOEA) to solve the Integration and Test Order (ITO) problem. The MOEAs are distinguished by components and parameters values, described by a grammar. The proposed hyper-heuristic is compared to conventional MOEAs and to a selection hyper-heuristic used in related work. Results show that GEMOITO can generate MOEAs that are statistically better or equivalent to the compared algorithms.

DOI: 10.1145/2908812.2908816

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Cite this paper

@inproceedings{Mariani2016GrammaticalEF, title={Grammatical Evolution for the Multi-Objective Integration and Test Order Problem}, author={Thain{\'a} Mariani and Giovani Guizzo and Silvia Regina Vergilio and Aurora Trinidad Ramirez Pozo}, booktitle={GECCO}, year={2016} }