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Exploring the integration of user feedback in automated testing of Android applications

Type of publication Peer-reviewed
Publikationsform Proceedings (peer-reviewed)
Author Grano Giovanni, Ciurumelea Adelina, Panichella Sebastiano, Palomba Fabio, Gall Harald C.,
Project SURF-MobileAppsData
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Proceedings (peer-reviewed)

Editor , Penta Massimiliano Di; , Oliveto Rocco; , Shepherd David C.
Page(s) 72 - 83
Title of proceedings 25th Int Conf on Software Analysis, Evolution and Reengineering, SANER 2018
DOI 10.1109/saner.2018.8330198

Open Access

URL https://www.zora.uzh.ch/id/eprint/150360/
Type of Open Access Repository (Green Open Access)

Abstract

The intense competition characterizing mobile application's marketplaces forces developers to create and maintain high-quality mobile apps in order to ensure their commercial success and acquire new users. This motivated the research community to propose solutions that automate the testing process of mobile apps. However, the main problem of current testing tools is that they generate redundant and random inputs that are insufficient to properly simulate the human behavior, thus leaving feature and crash bugs undetected until they are encountered by users. To cope with this problem, we conjecture that information available in user reviews---that previous work showed as effective for maintenance and evolution problems---can be successfully exploited to identify the main issues users experience while using mobile applications, e.g., GUI problems and crashes. In this paper we provide initial insights into this direction, investigating (i) what type of user feedback can be actually exploited for testing purposes, (ii) how complementary user feedback and automated testing tools are, when detecting crash bugs or errors and (iii) whether an automated system able to monitor crash-related information reported in user feedback is sufficiently accurate. Results of our study, involving 11,296 reviews of 8 mobile applications, show that user feedback can be exploited to provide contextual details about errors or exceptions detected by automated testing tools. Moreover, they also help detecting bugs that would remain uncovered when rely on testing tools only. Finally, the accuracy of the proposed automated monitoring system demonstrates the feasibility of our vision, i.e., integrate user feedback into testing process.
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