Using App Attributes to Improve Mobile Device Selection for Compatibility Testing

Villanes, Isabel K.; Endo, André Takeshi; Dias-Neto, Arilo Cláudio

doi:10.1145/3425174.3425215

Cited by 4 publications

(6 citation statements)

References 24 publications

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“…With the substantial rise of the type of mobile devices and platforms, some researchers tried to reduce the search space for devices to solve compatibility problems. Selecting the optimal device set [17][18][19][20] becomes an important research topic. Vilkomir 17 first evaluated the fault detection effectiveness of the random selection approach of 30 different devices on 15 apps and concluded that random selection is a useful way of testing.…”

Section: Related Workmentioning

confidence: 99%

“…Some work in the literature has investigated the optimal device selection 17–20 . Vilkomir 17 evaluated the fault detection effectiveness of the random selection approach of 30 different devices on 15 apps.…”

Section: Introductionmentioning

confidence: 99%

“…Cheng et al 19 conducted a multi‐objective genetic algorithm for selection based on the attributes of devices. Villanes et al 20 proposed DeSeCT, which first used a multi‐objective algorithm to select devices based on the attributes of the app. However, it only analyzed the manifest files of apps that only contain limited information for selection.…”

Section: Introductionmentioning

confidence: 99%

“…16 Some work in the literature has investigated the optimal device selection. [17][18][19][20] Vilkomir 17 evaluated the fault detection effectiveness of the random selection approach of 30 different devices on 15 apps. Zhang et al 18 conducted the K-Means algorithm to cluster the attributes of existing mobile devices, SDK platforms, and other features.…”

mentioning

confidence: 99%

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APP constraint analysis approach to select mobile devices for compatibility crowdtesting

Hui¹,

Zheng

2022

J Software Evolu Process

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The compatibility issues caused by Android fragmentation have become a vital task in the development of Android applications. To locate those issues, thousand of crowd testers run apps on different devices with different configurations to achieve the largest coverage, which might be costly and time‐consuming. Since existing approaches to selecting optimal devices are device‐side analysis without the information of the internal structures of apps, app‐side analysis that flags the essential devices for testers has remained elusive. To mitigate this gap of compatibility crowdtesting, this paper proposes an app constraint analysis approach named CompatDroid to generate the optimal device set to guide crowd testers. By evaluating 46 benchmark apps on 14 SDK versions, the optimal device sets are successfully generated, and CompatDroid only needs no more than 7 Android versions to achieve almost the same code coverage (i.e., 33.13%) testing on all 14 android versions (i.e., 34.65%) in 36 of 46 apps, which indicates that it can drastically reduce the consumption of test resources while losing little test coverage. On a larger dataset, CompatDroid successfully analyzes 98.3% of 645 apps, in which the median number of the optimal SDK versions set is 2.5 versions, and 68.92% of those apps contain the constraints of SDK version (i.e., SDK version) while 84.86% of them do not have the constraints of hardware information (i.e., model name and manufacture name).

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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APP constraint analysis approach to select mobile devices for compatibility crowdtesting

Hui¹,

Zheng

2022

J Software Evolu Process

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“…We also study the work of Villanes et al (Villanes et al, 2020) devoted to test cases exploration and in particular, the ways to decide which use cases could be useful in terms of compatibility testing scenarios. This is somehow what we try to experience in our paper by providing our testing verdicts.…”

Section: Related Workmentioning

confidence: 99%

An Automated Parallel Compatibility Testing Framework for Web-Based Systems

2021

Proceedings of the International Conferences on WWW/Internet 2021 and Applied Computing 2021

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With the growth and wide use of web-based applications in many domains, it is crucial to check their conformance with regards to their requirements. Among the important set of testing types, compatibility testing is of high importance. Indeed, ubiquity is required and the way of interacting with these applications can be performed in many manners. Compatibility testing aims at determining if the web application is proficient enough to run in different browsers, database, hardware, operating system, mobile devices, networks, etc. In this context, one challenge for compatibility testing is how to execute multiple tests cases, in a correct and efficient way, that may cover several environments and functionalities of the tested applications, while reducing the consumed resources and time. In our work, we propose a methodology to efficiently perform compatibility tests through several environments with different versions of operating systems (OS) and browsers. We emphasize on resource consumption improvement by using parallel testing and containerization.

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Cross-Device Difference Detector for Mobile Application GUI Compatibility Testing

Ren

et al. 2022

2022 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)

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Using App Attributes to Improve Mobile Device Selection for Compatibility Testing

Cited by 4 publications

References 24 publications

APP constraint analysis approach to select mobile devices for compatibility crowdtesting

APP constraint analysis approach to select mobile devices for compatibility crowdtesting

An Automated Parallel Compatibility Testing Framework for Web-Based Systems

Cross-Device Difference Detector for Mobile Application GUI Compatibility Testing

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