C. Siebra, A. Freitas, P. Costa, R. Freitas, F. Silva, and A. Santos (Brazil)
Test Automation, AI planning, handset network simulation.
More thorough testing prior to deployment and a reduced time to market are competing objectives that handset manufacturers must try to optimize. Thus, the evolution of test methodologies, with the use of a test automation approach, is an essential requirement to accelerate the product realization process. One important issue of test automation is to identify appropriate test cases, which can be applied to different scenarios. However, the very dynamic variety of new scenarios hampers the use of fixed sets of test cases, which are commonly used in a record and playback mode. This work investigates the use of Artificial Intelligence (AI) planning to generate appropriate and adaptive collections of test cases, which are used together with a network simulator to validate several handsets operations. The analytical results of our investigation shows that planning algorithms can create a more autonomous and general test process. Furthermore, such a process could be independent of changes in any of the scenarios parameters.
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