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Research paper | Open Access

Mobile devices compatibility testing strategy via crowdsourcing

University of Sheffield, Sheffield, UK
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Abstract

Purpose

This paper aims to support small mobile application development teams or companies performing testing on a large variety of operating systems versions and mobile devices to ensure their seamless working.

Design/methodology/approach

This paper proposes a “hybrid crowdsourcing” method that leverages the power of public crowd testers. This leads to generating a novel crowdtesting workflow Developer/Tester- Crowdtesting (DT-CT) that focuses on developers and crowd testers as key elements in the testing process without the need for intermediate as managers or leaders. This workflow has been used in a novel crowdtesting platform (AskCrowd2Test). This platform enables testing the compatibility of mobile devices and applications at two different levels, high-level (device characteristics) or low-level (code). Additionally, a “crowd-powered knowledge base” has been developed that stores testing results, relevant issues and their solutions.

Findings

The comparison of the presented DT-CT workflow with the common and most recent crowdtesting workflows showed that DT-CT may positively impact the testing process by reducing time-consuming and budget spend because of the direct interaction of developers and crowd testers.

Originality/value

To authors’ knowledge, this paper is the first to propose crowdtesting workflow based on developers and public crowd testers without crowd managers or leaders, which light the beacon for the future research in this field. Additionally, this work is the first that authorizes crowd testers with a limited level of experience to participate in the testing process, which helps in studying the behaviors and interaction of end-users with apps and obtains more concrete results.

References

 

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International Journal of Crowd Science
Pages 225-246
Cite this article:
Naith Q, Ciravegna F. Mobile devices compatibility testing strategy via crowdsourcing. International Journal of Crowd Science, 2018, 2(3): 225-246. https://doi.org/10.1108/IJCS-09-2018-0024

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Received: 15 September 2018
Revised: 15 October 2018
Accepted: 15 October 2018
Published: 13 November 2018
© The author(s)

Qamar Naith and Fabio Ciravegna. Published in International Journal of Crowd Science. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

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