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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

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • 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