Model-based test adaptation for smart TVs

Fırat, Atıl; Azimi, Mohammad Yusaf; Elgün, Celal Çağın; Erata, Ferhat; Yılmaz, Cemal

doi:10.1145/3524481.3527237

Cited by 3 publications

(3 citation statements)

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“…In our previous work (an industrial abstract) [12], we briefly introduced the idea and the rationale behind our model-based adaptation approach without providing any further details and without reporting any empirical results. In this work, however, we provide all the details regarding the proposed approach and empirically evaluate it by using real as well as randomly generated test cases.…”

Section: Introductionmentioning

confidence: 99%

AdapTV: A Model-Based Test Adaptation Approach for End-to-End User Interface Testing of Smart TVs

Azimi

Elgun²,

Firat³

et al. 2023

IEEE Access

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We introduce a model-based feedback-driven test adaptation approach for end-to-end user interface testing of smart TVs. From the perspective of the TV software, the proposed approach is a nonintrusive and completely black-box approach, which operates by interpreting the screen images. Given a test suite, which is known to work in an older version of the TV, and a new version of the TV, to which the test suite should be adapted, the proposed approach first automatically discovers user interface models for both the older and the new version of TV by opportunistically crawling the TVs. Then, each test case in the test suite is executed on the old version, and the path traversed by the test case in the respective UI model is found. Finally, a semantically equivalent path in the UI model discovered for the new version of the TV is determined and dynamically executed on the new version in a feedback-driven manner. We empirically evaluate the proposed approach in a setup that closely mimics the industrial setup used by a large consumer electronics company. While the proposed approach successfully adapted all the test cases, the alternative approaches used in the experiments could not adapt any of them. INDEX TERMSConsumer electronics testing, model-based testing, smart TV testing, test adaptation

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Section: Introductionmentioning

confidence: 99%

AdapTV: A Model-Based Test Adaptation Approach for End-to-End User Interface Testing of Smart TVs

Azimi

Elgun²,

Firat³

et al. 2023

IEEE Access

Self Cite

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“…Our final aim with this VUI context‐of‐use conceptual structure based on our matrix is to have a reference framework for automatic evaluation of VUIs. We could apply mechanisms such as early testing for this validation, but the reference model is essential 15 . To answer our RQs and create our matrix, we interviewed persons who regularly utilize VUIs in private and professional settings.…”

Section: Introductionmentioning

confidence: 99%

“…We could apply mechanisms such as early testing for this validation, but the reference model is essential. 15 To answer our RQs and create our matrix, we interviewed persons who regularly utilize VUIs in private and professional settings. We asked them about which ones they use, how they use them in daily life, the environments in which they use them, and the conditions under which they use them.…”

mentioning

confidence: 99%

Exploring the context of use for voice user interfaces: Toward context‐dependent user experience quality testing

Klein,

Deutschländer,

Kölln

et al. 2023

J Software Evolu Process

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Voice user interface (VUI) systems, such as Alexa, Siri, and Google Assistant, are popular and widely available. Still, challenges such as privacy and the ability to have a dialog remain. In the latter example, the user expects a human‐like conversation, that is, that the VUI understands the dialog and its context. However, this VUI feature of context‐aware interaction is rather error prone. For this reason, we intend to explore the VUI context of use and its impact on interaction, that is, relevant user experience (UX). We see a demand for context‐dependent UX measurement because analyzing the context of use and UX assessment are both critical human‐centered design (HCD) methods. Therefore, we examine the VUI context of use by asking users about how, where, and for what they use VUIs, as well as their UX and improvement proposals. We interviewed people with disabilities who rely on VUIs and people without disabilities who use VUIs for convenience or fun. We identified VUI context‐of‐use categories and factors and explored their impacts on relevant UX qualities. Our result is a matrix containing these elements; thus, it provides an overview of the contextual UX of our target group's VUI interaction. We intend to develop a VUI context‐of‐use conceptual structure in the future based on this matrix, which is needed to create an automated context‐dependent UX measurement recommendation tool for VUIs. This conceptual structure could also be useful for automated UX testing in the context of VUI.

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AdapTV+: Enhancing Model-Based Test Adaptation for Smart TVs through Icon Recognition

Azimi,

Yilmaz

2023

2023 IEEE 28th Pacific Rim International Symposium on Dependable Computing (PRDC)

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Model-based test adaptation for smart TVs

Cited by 3 publications

References 1 publication

AdapTV: A Model-Based Test Adaptation Approach for End-to-End User Interface Testing of Smart TVs

AdapTV: A Model-Based Test Adaptation Approach for End-to-End User Interface Testing of Smart TVs

Exploring the context of use for voice user interfaces: Toward context‐dependent user experience quality testing

AdapTV+: Enhancing Model-Based Test Adaptation for Smart TVs through Icon Recognition

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