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Crowd Intelligence Enhances Automated Mobile Testing

Mao, K; Harman, M; Jia, Y; (2017) Crowd Intelligence Enhances Automated Mobile Testing. In: 2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE). (pp. pp. 16-26). IEEE: New York, NY, USA. Green open access

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Abstract

We show that information extracted from crowd-based testing can enhance automated mobile testing. We introduce Polariz, which generates replicable test scripts from crowd-based testing, extracting cross-app `motif' events: automatically-inferred reusable higher-level event sequences composed of lower-level observed event actions. Our empirical study used 434 crowd workers from Mechanical Turk to perform 1,350 testing tasks on 9 popular Google Play apps, each with at least 1 million user installs. The findings reveal that the crowd was able to achieve 60.5% unique activity coverage and proved to be complementary to automated search-based testing in 5 out of the 9 subjects studied. Our leave-one-out evaluation demonstrates that coverage attainment can be improved (6 out of 9 cases, with no disimprovement on the remaining 3) by combining crowd-based and search-based testing.

Type: Proceedings paper
Title: Crowd Intelligence Enhances Automated Mobile Testing
Event: 32nd IEEE/ACM International Conference on Automated Software Engineering, 30 October - 3 November 2017, Urbana, IL, USA
ISBN-13: 978-1-5386-2684-9/17
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/ASE.2017.8115614
Publisher version: https://doi.org/10.1109/ASE.2017.8115614
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Testing , Mobile communication , Tools , Data mining , Androids , Humanoid robots , Mobile handsets, Crowdsourced Software Engineering , Mobile App Testing , Test Generation
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10037960
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