Martin, W;
Sarro, F;
Harman, M;
Jia, Y;
Zhang, Y;
(2016)
A survey of app store analysis for software engineering.
Transactions on Software Engineering
, 43
(9)
pp. 817-847.
10.1109/TSE.2016.2630689.
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Abstract
App Store Analysis studies information about applications obtained from app stores. App stores provide a wealth of information derived from users that would not exist had the applications been distributed via previous software deployment methods. App Store Analysis combines this non-technical information with technical information to learn trends and behaviours within these forms of software repositories. Findings from App Store Analysis have a direct and actionable impact on the software teams that develop software for app stores, and have led to techniques for requirements engineering, release planning, software design, security and testing. This survey describes and compares the areas of research that have been explored thus far, drawing out common aspects, trends and directions future research should take to address open problems and challenges.
| Type: | Article |
|---|---|
| Title: | A survey of app store analysis for software engineering |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/TSE.2016.2630689 |
| Publisher version: | http://dx.doi.org/10.1109/TSE.2016.2630689 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/. |
| Keywords: | Software, Security, Software engineering, Market research, Ecosystems, Mobile communication, Google, ecosystem, App Store, analysis, mining, API, feature, release planning, requirements engineering, reviews, security |
| UCL classification: | UCL 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/1538191 |
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