scholarly journals A System for GUI Testing of Android Apps with Multiple Activities

2021 ◽  
Vol 174 (19) ◽  
pp. 25-35
Author(s):  
Moheb R. Girgis ◽  
Bahgat A. Abdel Latef ◽  
Tahany Akl
Keyword(s):  
Android Apps ◽  
Gui Testing

scholarly journals An Empirical Analysis of Test Input Generation Tools for Android Apps through a Sequence of Events

Symmetry ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 1894
Author(s):  
Husam N. Yasin ◽  
Siti Hafizah Ab Hamid ◽  
Raja Jamilah Raja Yusof ◽  
Muzaffar Hamzah
Keyword(s):  
Computational Cost ◽  
Sequence Length ◽  
Code Coverage ◽  
Android Apps ◽  
Gui Testing ◽  
Test Input ◽  
Testing Tools ◽  
Sequence Of Events ◽  
Current State ◽  
A Minor

Graphical User Interface (GUI) testing of Android apps has gained considerable interest from the industries and research community due to its excellent capability to verify the operational requirements of GUI components. To date, most of the existing GUI testing tools for Android apps are capable of generating test inputs by using different approaches and improve the Android apps’ code coverage and fault detection performance. Many previous studies have evaluated the code coverage and crash detection performances of GUI testing tools in the literature. However, very few studies have investigated the effectiveness of the test input generation tools, especially in the events sequence length of the overall test coverage and crash detection. The event sequence length generally shows the number of steps required by the test input generation tools to detect a crash. It is critical to highlight its effectiveness due to its significant effects on time, testing effort, and computational cost. Thus, this study evaluated the effectiveness of six test input generation tools for Android apps that support the system events generation on 50 Android apps. The generation tools were evaluated and compared based on the activity coverage, method coverage, and capability in detecting crashes. Through a critical analysis of the results, this study identifies the diversity and similarity of test input generation tools for Android apps to provide a clear picture of the current state of the art. The results revealed that a long events sequence performed better than a shorter events sequence. However, a long events sequence led to a minor positive effect on the coverage and crash detection. Moreover, the study showed that the tools achieved less than 40% of the method coverage and 67% of the activity coverage.

scholarly journals Guided GUI testing of android apps with minimal restart and approximate learning

2013 ◽  
Vol 48 (10) ◽  
pp. 623-640 ◽  
Author(s):  
Wontae Choi ◽  
George Necula ◽  
Koushik Sen
Keyword(s):  
Android Apps ◽  
Gui Testing

scholarly journals A GUI TESTING STRATEGY AND TOOL FOR ANDROID APPS

2020 ◽  
pp. 355-364
Author(s):  
Moheb R. Girgis ◽  
Bahgat A. Abdel Latef ◽  
Tahany Akl
Keyword(s):  
Test Cases ◽  
Test Evaluation ◽  
Event Sequence ◽  
Event Sequences ◽  
Android Apps ◽  
Gui Testing ◽  
Test Script ◽  
Evaluation Phase ◽  
Two Phases ◽  
Event Based

The increasing popularity of Android and the GUI-driven nature of its apps have motivated the need for applicable automated GUI testing techniques. This paper presents a proposed strategy and a supporting tool for GUI testing of Android apps. The strategy employs a model-based approach to capture the event-driven nature of Android apps. It includes two phases: Modeling Phase and Test Evaluation Phase. In the modeling phase, an event sequence diagram (ESD) is created for each activity in the app under test (AUT), which depicts its events and possible transitions between them, and used to generate event sequences (test cases). In the test evaluation phase, certain event-based coverage criteria are employed to measure the adequacy of the generated test cases. The proposed tool analyses the AUT, creates an ESD for each activity, and generates event sequences. It handles the event sequences explosion problem and ensures the event sequences feasibility. For each event sequence, the tool generates a test script and a corresponding Robotium test class, adds it to the AUT and executes it. The paper also presents a case study that illustrates the use of the proposed strategy and tool for testing a simple Android app.

Tracing or Tracking? A Preliminary Analysis of COVID-19 Outbreak Tracker Apps on Android and User Privacy (Preprint)

2020 ◽  
Author(s):  
Alex Akinbi ◽  
Ehizojie Ojie
Keyword(s):  
Preliminary Analysis ◽  
Service Providers ◽  
User Participation ◽  
Memory Storage ◽  
Phone Call ◽  
Contact Tracing ◽  
Privacy Rights ◽  
User Privacy ◽  
Android Apps ◽  
User Data

BACKGROUND Technology using digital contact tracing apps has the potential to slow the spread of COVID-19 outbreaks by recording proximity events between individuals and alerting people who have been exposed. However, there are concerns about the abuse of user privacy rights as such apps can be repurposed to collect private user data by service providers and governments who like to gather their citizens’ private data. OBJECTIVE The objective of our study was to conduct a preliminary analysis of 34 COVID-19 trackers Android apps used in 29 individual countries to track COVID-19 symptoms, cases, and provide public health information. METHODS We identified each app’s AndroidManifest.xml resource file and examined the dangerous permissions requested by each app. RESULTS The results in this study show 70.5% of the apps request access to user location data, 47% request access to phone activities including the phone number, cellular network information, and the status of any ongoing calls. 44% of the apps request access to read from external memory storage and 2.9% request permission to download files without notification. 17.6% of the apps initiate a phone call without giving the user option to confirm the call. CONCLUSIONS The contributions of this study include a description of these dangerous permissions requested by each app and its effects on user privacy. We discuss principles that must be adopted in the development of future tracking and contact tracing apps to preserve the privacy of users and show transparency which in turn will encourage user participation.

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