Naith, Q. and Ciravegna, F. orcid.org/0000-0001-5817-4810 (2018) Hybrid crowd-powered approach for compatibility testing of mobile devices and applications. In: ICCSE'18. 3rd International Conference on Crowd Science and Engineering, 28-31 Jul 2018, Singapore, Singapore. ACM International Conference Proceeding Series . ACM ISBN 978-1-4503-6587-1
Abstract
Testing mobile applications (apps) to ensure they work seamlessly on all devices can be difficult and expensive, especially for small development teams or companies due to limited available resources. There is a need for methods to outsource testing on all these models and OS versions. In this paper, we propose a crowdsourced testing approach that leverages the power of the crowd to perform mobile device compatibility testing in a novel way. This approach aims to provide support for testing code, features, or hardware characteristics of mobile devices which is hardly investigated. This testing will enable developers to ensure that features and hardware characteristics of any device model or features of a specific OS version will work correctly and will not cause any problems with their apps. It empowers developers to find a solution for issues they may face during the development of an app by asking testers to perform a test or searching a knowledge base provided with the platform. It will offer the ability to add a new issue or add a solution to existing issues. We expect that these capabilities will improve the testing and development of mobile apps by considering variant mobile devices and OS versions on the crowd.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 Association for Computing Machinery. This is an author produced version of a paper subsequently published in ICCSE'18. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Crowdtesting; Compatibility; Knowledge base; Mobile Devices |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 05 Apr 2019 11:05 |
Last Modified: | 08 Apr 2019 11:21 |
Status: | Published |
Publisher: | ACM |
Series Name: | ACM International Conference Proceeding Series |
Refereed: | Yes |
Identification Number: | 10.1145/3265689.3265690 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:142482 |