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https://doi.org/10.32657/10220...
Doctoral thesis . 2019 . Peer-reviewed
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Testing mobile applications via automated exploration of graphical user interface and textual user input generation

Authors: Arnatovich, Yauhen Leanidavich;

Testing mobile applications via automated exploration of graphical user interface and textual user input generation

Abstract

A Graphical User Interface (GUI) is acknowledged as a crucial component of an event-driven software (e.g., mobile apps). In the event-driven software, the GUI usually contains hundreds or even thousands of elements. As such, a large part of app functionality, and thus its code, is usually dedicated to a user interface, so its testing becomes an essential part of the software development life-cycle significantly improving quality of software. During a testing phase, the GUI can be tested by executing each event individually and observing its behaviour. However, it is not a trivial task since the behaviour of an event handler may depend on a GUI internal state, state of other entities (objects, event handlers) and an external environment. Furthermore, an outcome of the event handler execution may vary depending on a particular sequence of preceding events. As a result, each GUI event needs to be tested in a context of different states via generating and executing various sequences of the GUI events. Modern mobile apps have a highly interactive nature and complex GUI structure. As such, an automated GUI testing of mobile apps is a daunting task for developers and testers. Often the GUI testing is done manually where all possible combinations of the GUI elements for a given app screen are manually tested for functional correctness and aesthetic quality. The manual GUI-testing is no doubt an effective approach, however, it is inefficient, i.e., time-consuming, error-prone, and usually not complete, especially for a large software with complex GUIs. So, to facilitate manual testing, various automated testing approaches have been introduced such as model-based testing, concolic testing, search-based testing, evolutionary testing, and combinatorial testing. However, for automated testing, there is a challenge to generate tests with high coverage, as well as to maintain a reasonable execution time. These are hindered by the non-trivial structure, and highly interactive nature of mobile apps GUIs so that an achieved code coverage is generally low while execution time is high. Doctor of Philosophy

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Keywords

:Engineering::Computer science and engineering::Software::Software engineering [DRNTU], DRNTU::Engineering::Computer science and engineering::Software::Software engineering, 004

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
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