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Community detection in model-based testing to address scalability

Boekbijdrage - Boekabstract Conferentiebijdrage

Ondertitel:study design
Model-based GUI testing has achieved widespread recognition in academy thanks to its advantages compared to code-based testing due to its potentials to automate testing and the ability to cover bigger parts more efficiently. In this study design paper, we address the scalability part of the model-based GUI testing by using community detection algorithms. A case study is presented as an example of possible improvements to make a model-based testing approach more efficient. We demonstrate layered ESG models as an example of our approach to consider the scalability problem. We present rough calculations with expected results, which show 9 times smaller time and space units for 100 events in the ESG model when a community detection algorithm is applied.
Boek: 15th Conference on Computer Science and Information Systems (FedCSIS), 6-9 September, 2020, Sofia, Bulgaria
Pagina's: 657 - 660
ISBN:978-83-955416-7-4
Jaar van publicatie:2020
Trefwoorden:P3 Proceeding
Toegankelijkheid:Closed