EvoCreeper: Automated Black-Box Model Generation for Smart TV Applications
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00331593" target="_blank" >RIV/68407700:21230/19:00331593 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/TCE.2019.2907017" target="_blank" >https://doi.org/10.1109/TCE.2019.2907017</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TCE.2019.2907017" target="_blank" >10.1109/TCE.2019.2907017</a>
Alternative languages
Result language
angličtina
Original language name
EvoCreeper: Automated Black-Box Model Generation for Smart TV Applications
Original language description
Smart TVs are coming to dominate the television market. This accompanied by an increase in the use of the smart TV applications (apps). Due to the increasing demand, developers need modeling techniques to analyze these apps and assess their comprehensiveness, completeness, and quality. In this paper, we present an automated strategy for generating models of smart TV apps based on a black-box reverse engineering. The strategy can be used to cumulatively construct a model for a given app by exploring the user interface in a manner consistent with the use of a remote control device and extracting the runtime information. The strategy is based on capturing the states of the user interface to create a model during runtime without any knowledge of the internal structure of the app. We have implemented our strategy in a tool called EvoCreeper. The evaluation results show that our strategy can automatically generate unique states and a comprehensive model that represents the real user interactions with an app using a remote control device. The models thus generated can be used to assess the quality and completeness of smart TV apps in various contexts, such as the control of other consumer electronics in smart houses.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE Transactions on Consumer Electronics
ISSN
0098-3063
e-ISSN
1558-4127
Volume of the periodical
65
Issue of the periodical within the volume
2
Country of publishing house
US - UNITED STATES
Number of pages
10
Pages from-to
160-169
UT code for WoS article
000466181000005
EID of the result in the Scopus database
2-s2.0-85063393778