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EvoCreeper: Automated Black-Box Model Generation for Smart TV Applications
Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap (from 2013). (SERG, Software engineering)ORCID-id: 0000-0001-9051-7609
Czech Technical University, Czech Republic.
2019 (engelsk)Inngår i: IEEE transactions on consumer electronics, ISSN 0098-3063, E-ISSN 1558-4127, Vol. 65, nr 2, s. 160-169Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Abstract—Smart TVs are coming to dominate the televisionmarket. This accompanied by an increase in the use of the smartTV applications (apps). Due to the increasing demand, developersneed modeling techniques to analyze these apps and assess theircomprehensiveness, completeness, and quality. In this paper, wepresent an automated strategy for generating models of smartTV apps based on a black-box reverse engineering. The strategycan be used to cumulatively construct a model for a given app byexploring the user interface in a manner consistent with the use ofa remote control device and extracting the runtime information.The strategy is based on capturing the states of the user interfaceto create a model during runtime without any knowledge ofthe internal structure of the app. We have implemented ourstrategy in a tool called EvoCreeper. The evaluation results showthat our strategy can automatically generate unique states anda comprehensive model that represents the real user interactionswith an app using a remote control device. The models thusgenerated can be used to assess the quality and completeness ofsmart TV apps in various contexts, such as the control of otherconsumer electronics in smart houses.

sted, utgiver, år, opplag, sider
2019. Vol. 65, nr 2, s. 160-169
Emneord [en]
Model generation, Smart TV application, Application reverse engineering, Model-based testing
HSV kategori
Forskningsprogram
Datavetenskap
Identifikatorer
URN: urn:nbn:se:kau:diva-71606DOI: 10.1109/TCE.2019.2907017ISI: 000466181000005OAI: oai:DiVA.org:kau-71606DiVA, id: diva2:1298752
Tilgjengelig fra: 2019-03-25 Laget: 2019-03-25 Sist oppdatert: 2019-08-07bibliografisk kontrollert

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