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Comparison of GUI Testing Tools for Android Applications
Comparison of GUI testing tools for Android applications University of Oulu Department of Information Processing Science Master’s Thesis Tomi Lämsä Date 22.5.2017 2 Abstract Test automation is an intriguing area of software engineering, especially in Android development. This is since Android applications must be able to run in many different permutations of operating system versions and hardware choices. Comparison of different tools for automated UI testing of Android applications is done in this thesis. In a literature review several different tools available and their popularity is researched and the structure of the most popular tools is looked at. The two tools identified to be the most popular are Appium and Espresso. In an empirical study the two tools along with Robotium, UiAutomator and Tau are compared against each other in test execution speed, maintainability of the test code, reliability of the test tools and in general issues. An empirical study was carried out by selecting three Android applications for which an identical suite of tests was developed with each tool. The test suites were then run and the execution speed and reliability was analysed based on these results. The test code written is also analysed for maintainability by calculating the lines of code and the number of method calls needed to handle asynchrony related to UI updates. The issues faced by the test developer with the different tools are also analysed. This thesis aims to help industry users of these kinds of applications in two ways. First, it could be used as a source on what tools are over all available for UI testing of Android applications. -
Predicting Student's Attributes from Their Physiological Response to An
ISSN 2007-9737 Predicción de atributos de estudiantes a partir de su respuesta fisiológica a cursos en línea Marco A. Hernández Pérez1, Emmanuel Rosado Martínez2, Rolando Menchaca Méndez1, Ricardo Menchaca Méndez1, Mario E. Rivero Ángeles1, Víctor M. González3 1 Centro de Investigación en Computación, Instituto Politécnico Nacional, México 2 Escuela Superior de Cómputo, Instituto Politécnico Nacional, México [email protected], [email protected], {rmen, ric, erivero}@cic.ipn.mx, [email protected] Resumen. En este trabajo se presentan los resultados Predicting Student’s Attributes from de un estudio donde se monitorizó la respuesta fisiológica de un conjunto de cincuenta estudiantes de their Physiological Response to an nivel medio superior, durante su participación en un Online Course curso en línea. Por cada uno de los sujetos de prueba, se recolectaron series de tiempo obtenidas por medio de Abstract. In this work, we present the results of a study sensores de señales fisiológicas como actividad where we monitored the physiological response of a set eléctrica cerebral, ritmo cardiaco, respuesta galvánica of fifty high-school students during their participation in de la piel, temperatura corporal, entre otros. A partir de an online course. For each of the subjects, we los primeros cuatro momentos estadísticos (media, recollected time-series obtained from sensors of varianza, asimetría y curtosis) de dichas series de physiological signals such as electrical cerebral activity, tiempo, se entrenaron modelos de redes neuronales y heart rate, galvanic skin response, body temperature, máquinas de vector de soporte que demostraron ser among others. From the first four moments (mean, efectivas para determinar el sexo del sujeto de prueba, variance, skewness and kurtosis) of the time-series we el tipo de actividad que se encuentra realizando, su trained Artificial Neural Network and Support Vector estilo de aprendizaje, así como si contaban o no con Machine models that showed to be effective for conocimientos previos acerca del contenido del curso. -
Mobile Developer's Guide to the Galaxy
Don’t Panic MOBILE DEVELOPER’S GUIDE TO THE GALAXY U PD A TE D & EX TE ND 12th ED EDITION published by: Services and Tools for All Mobile Platforms Enough Software GmbH + Co. KG Sögestrasse 70 28195 Bremen Germany www.enough.de Please send your feedback, questions or sponsorship requests to: [email protected] Follow us on Twitter: @enoughsoftware 12th Edition February 2013 This Developer Guide is licensed under the Creative Commons Some Rights Reserved License. Editors: Marco Tabor (Enough Software) Julian Harty Izabella Balce Art Direction and Design by Andrej Balaz (Enough Software) Mobile Developer’s Guide Contents I Prologue 1 The Galaxy of Mobile: An Introduction 1 Topology: Form Factors and Usage Patterns 2 Star Formation: Creating a Mobile Service 6 The Universe of Mobile Operating Systems 12 About Time and Space 12 Lost in Space 14 Conceptional Design For Mobile 14 Capturing The Idea 16 Designing User Experience 22 Android 22 The Ecosystem 24 Prerequisites 25 Implementation 28 Testing 30 Building 30 Signing 31 Distribution 32 Monetization 34 BlackBerry Java Apps 34 The Ecosystem 35 Prerequisites 36 Implementation 38 Testing 39 Signing 39 Distribution 40 Learn More 42 BlackBerry 10 42 The Ecosystem 43 Development 51 Testing 51 Signing 52 Distribution 54 iOS 54 The Ecosystem 55 Technology Overview 57 Testing & Debugging 59 Learn More 62 Java ME (J2ME) 62 The Ecosystem 63 Prerequisites 64 Implementation 67 Testing 68 Porting 70 Signing 71 Distribution 72 Learn More 4 75 Windows Phone 75 The Ecosystem 76 Implementation 82 Testing -
Measuring Heart Rate Variability in Free-Living Conditions Using Consumer-Grade Photoplethysmography: Validation Study
JMIR BIOMEDICAL ENGINEERING Lam et al Original Paper Measuring Heart Rate Variability in Free-Living Conditions Using Consumer-Grade Photoplethysmography: Validation Study Emily Lam1*, BEng; Shahrose Aratia2*, BSc; Julian Wang3, MD; James Tung4, PhD 1Possibility Engineering and Research Laboratory, Bloorview Research Institute, Toronto, ON, Canada 2Department of Occupational Science and Occupational Therapy, University of Toronto, Toronto, ON, Canada 3Michael G Degroote School of Medicine, McMaster University, Hamilton, ON, Canada 4Department of Mechanical & Mechatronics Engineering, University of Waterloo, Waterloo, ON, Canada *these authors contributed equally Corresponding Author: James Tung, PhD Department of Mechanical & Mechatronics Engineering University of Waterloo 200 University Ave W Waterloo, ON, N2L 3G1 Canada Phone: 1 519 888 4567 ext 43445 Email: [email protected] Abstract Background: Heart rate variability (HRV) is used to assess cardiac health and autonomic nervous system capabilities. With the growing popularity of commercially available wearable technologies, the opportunity to unobtrusively measure HRV via photoplethysmography (PPG) is an attractive alternative to electrocardiogram (ECG), which serves as the gold standard. PPG measures blood flow within the vasculature using color intensity. However, PPG does not directly measure HRV; it measures pulse rate variability (PRV). Previous studies comparing consumer-grade PRV with HRV have demonstrated mixed results in short durations of activity under controlled conditions. Further research is required to determine the efficacy of PRV to estimate HRV under free-living conditions. Objective: This study aims to compare PRV estimates obtained from a consumer-grade PPG sensor with HRV measurements from a portable ECG during unsupervised free-living conditions, including sleep, and examine factors influencing estimation, including measurement conditions and simple editing methods to limit motion artifacts. -
Behavioral Analysis of Android Applications Using Automated Instrumentation
2013 Seventh International Conference on Software Security and Reliability Companion Behavioral Analysis of Android Applications Using Automated Instrumentation Mohammad Karami, Mohamed Elsabagh, Parnian Najafiborazjani, and Angelos Stavrou Computer Science Department, George Mason University, Fairfax, VA 22030 { mkarami, melsabag, pnajafib, astavrou}@gmu.edu Abstract—Google’s Android operating system has become one application is not a straight forward task due to variety of the most popular operating system for hand-held devices. Due inputs and heterogeneity of the technologies [12]. to its ubiquitous use, open source nature and wide-spread Two primary methods are being employed for mobile appli- popularity, it has become the target of recent mobile malware. In this paper, we present our efforts on effective security cation analysis: white-box approach and black-box approach. inspection mechanisms for identification of malicious applications In black-box testing only the inputs and outputs of the appli- for Android mobile applications. To achieve that, we devel- cation are being exercised. On the other hand, for white box oped a comprehensive software inspection framework. Moreover, approach the source code need to be analyzed. Since the source to identify potential software reliability flaws and to trigger code of the malicious applications that we get from Google malware, we develop a transparent instrumentation system for automating user interactions with an Android application that Play is not available we cannot analyze the internal structure does not require source code. Additionally, for run-time behavior of the malicious applications to figure out what they exactly analysis of an application, we monitor the I/O system calls gener- do, but we can utilize the black-box testing to define their ated the by application under monitoring to the underlying Linux functionality. -
A Mobile Application for Data Acquisition from Wearable Devices in Affective Computing Experiments∗
BandReader – A Mobile Application for Data Acquisition from Wearable Devices in Affective Computing Experiments∗ Krzysztof Kutt AGH University of Science and Technology [email protected] Grzegorz J. Nalepa AGH University of Science and Technology [email protected] Barbara Gizycka˙ AGH University of Science and Technology [email protected] Paweł Jemio{o AGH University of Science and Technology [email protected] Marcin Adamczyk AGH University of Science and Technology Abstract As technology becomes more ubiquitous and pervasive, special attention should be given to human-computer interaction, especially to the aspect related to the emotional states of the user. However, this approach assumes very specific mode of data collection and storage. This data is used in the affective computing experiments for human emotion recognition. In the paper we describe a new software solution for mobile devices that allows for data acquisition from wristbands. The application reads physiological signals from wristbands and supports multiple recent devices. In our work we focus on the Heart Rate (HR) and Galvanic Skin Response (GSR) readings. The recorded data is conveniently stored in CSV files, ready for further interpretation. We provide the evaluation of our application with several experiments. The results indicate that the BandReader is a reliable software for data acquisition in affective computing scenarios. I. IntroductionDRAFTeach user, mobile systems offer various meth- ods of personalization and customization of eople nowadays are getting more and these devices. However, as they become more more accustomed to technology that is and more miniature, they can be fit to pieces Ppervasive and ubiquitous. Besides using of hardware of a size of an accessory. -
Unit Testing, Integration Testing and Continuous Builds for Android
Unit Testing, Integration Testing and Continuous Builds Manfred Moser simpligility technologies inc. http://www.simpligility.com @simpligility Agenda Get an overview about testing and continuous integration for Android app development Why testing? What can we test? How can we do it? 2 Manfred Moser simpligility.com Apache Maven See previous presentation Maven used to control build and more Good library reuse and dependency use – makes testing easier out of the box Strong tool support But its all possible without Maven too... Why (automated) testing? Find problem early and you ● Can fix it quickly ● Safe money on QA testing ● Do not get negative customer feedback ● Deal with feature requests instead of bugs ● Avoid production problems ● Can refactor (and change) without breaking old stuff 4 Manfred Moser simpligility.com What are we testing? Plain java code Android dependent code Configuration User interface Look and feel 5 Manfred Moser simpligility.com JVM vs Dalvik/Android stack JVM based: ● Faster ● More tools available ● More mature tooling Dalvik based: ● Necessary for integration tests ● Reproduce actual behaviour ● Full stack testing (beyond VM, to native..) 6 Manfred Moser simpligility.com JVM testing tools ● JUnit ● TestNG ● EasyMock ● Unitils ● Cobertura ● Emma ● and many more 7 Android SDK Test Tools ● Integrated Junit ● use on emulator/device though ● Instrumentation Test Tools ● rich set of classes for testing ● now well documented ● MonkeyRunner ● control device/emulator running tests ● take screenshots ● jython 8 Dalvik/Android -
Large-Scale Android Dynamic Analysis
Andlantis: Large-scale Android Dynamic Analysis Michael Biermayz, Eric Gustafsonz, Jeremy Ericksony, David Fritzy, Yung Ryn Choey ∗ySandia National Laboratories fmbierma, jericks, djfritz, [email protected] zUniversity of California, Davis fmhbierma, [email protected] Abstract— In this paper, we present Andlantis: a highly scalable Analyzing Android applications for malicious behavior is an dynamic analysis framework for analyzing applications on important area of research, and is made difficult, in part, by the Android operating system. Andlantis runs the Android the increasingly large number of applications available for the operating system in a virtualized environment and is able platform. While techniques exist to perform static analysis on a to provide the virtual device with artificial network data in large number of applications, dynamic analysis techniques are order to provide an environment which closely replicates that relatively limited in scale due to the computational resources of a physical device. Andlantis is able to schedule and run required to emulate the full Android system to achieve accurate thousands of Android instances in parallel, enabling us to execution. We present Andlantis, a scalable dynamic analysis investigate the behavior of mobile malware at scale. system capable of processing over 3000 Android applications per hour. During this processing, the system is able to collect Andlantis employs a scalable high-performance emulytics valuable forensic data, which helps reverse-engineers and mal- framework, minimega, to parallelize this expensive task as ware researchers identify and understand anomalous application much as possible and achieve a level of throughput un- behavior. We discuss the results of running 1261 malware samples precedented in Android dynamic analysis. -
Use of Mobile Health Apps and Wearable Technology to Assess Changes and Predict Pain During Treatment of Acute Pain in Sickle Cell Disease: Feasibility Study
JMIR MHEALTH AND UHEALTH Johnson et al Original Paper Use of Mobile Health Apps and Wearable Technology to Assess Changes and Predict Pain During Treatment of Acute Pain in Sickle Cell Disease: Feasibility Study Amanda Johnson1*, MD, BA; Fan Yang2*; Siddharth Gollarahalli3; Tanvi Banerjee2, PhD; Daniel Abrams4, PhD; Jude Jonassaint5, RN; Charles Jonassaint5, PhD, MHS; Nirmish Shah6, MD 1Department of Pediatrics, Duke University, Durham, NC, United States 2Department of Computer Science & Engineering, Wright State University, Dayton, OH, United States 3North Carolina State University, Raleigh, NC, United States 4Engineering Sciences and Applied Mathematics, Northwestern University, Chicago, IL, United States 5Social Work and Clinical and Translational Science, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States 6Division of Hematology, Department of Medicine, Duke University, Durham, NC, United States *these authors contributed equally Corresponding Author: Amanda Johnson, MD, BA Department of Pediatrics Duke University 2301 Erwin Road Durham, NC, 27710 United States Phone: 1 651 207 3255 Email: [email protected] Abstract Background: Sickle cell disease (SCD) is an inherited red blood cell disorder affecting millions worldwide, and it results in many potential medical complications throughout the life course. The hallmark of SCD is pain. Many patients experience daily chronic pain as well as intermittent, unpredictable acute vaso-occlusive painful episodes called pain crises. These pain crises often require acute medical care through the day hospital or emergency department. Following presentation, a number of these patients are subsequently admitted with continued efforts of treatment focused on palliative pain control and hydration for management. Mitigating pain crises is challenging for both the patients and their providers, given the perceived unpredictability and subjective nature of pain. -
Guide to Test Automation Tools 2017 - 2018
Guide to Test Automation Tools 2017 - 2018 WHITEPAPER QATestlab 2017 Copyright 2017 ©QATestLab. All Rights Reserved Table of Contents Summary 3 Introduction 3 1. Test Automation Tools. Market review 1.1. Selenium WebDriver Framework 4 1.2. Appium Framework 5 1.3. Robotium Framework 7 1.4. Serenity Framework 9 1.5. Robot Framework 10 1.6. Galen Framework 12 1.7. HP Unified Functional Testing (UFT) 14 1.8. Ranorex Studio 16 1.9. TestComplete 19 1.10. Telerik Test Studio 20 1.11. Applitools Eyes 22 1.12. Test Automation Tools and Frameworks: Comparison of 23 Technical Aspects 2. Test Automation Tools Approved by QATestLab 2.1. Selenium WebDriver 26 2.2. Appium 28 2.3. TestComplete 29 2.4. Ranorex Studio 31 3. Summary 32 Contact Information 33 2 Copyright 2017 ©QATestLab. All Rights Reserved Summary Table of Contents Click the section to jump This whitepaper aims at providing the comprehensive data on the most ahead popular test automation tools in 2017 - 2018 including the description of Summary their parameters which can be considered when selecting a tool / framework for test automation. The document also provides the Introduction comparison of the leading test automation tools highlighting both 1. Test Automation advantages and disadvantages, and also main objectives, technical Tools. Market review characteristics and the information about a provider. 1.1. Selenium WebDriver Framework The whitepaper is aimed to assist in selecting a proper test automation 1.2 Appium Framework tool avoiding time and money losses. Besides, it includes the 1.3 Robotium recommendations on the most effective test automation tools, Framework 1.4 Serenity Framework information about their effectiveness and maintainability, which were 1.5 Robot Framework prepared by QATestLab on the ground of successful execution of 50 test 1.6 Galen Framework automation projects. -
Profiling the Responsiveness of Android Applications Via Automated
Profiling the Responsiveness of Android Applications via Automated Resource Amplification Yan Wang Atanas Rountev Ohio State University Ohio State University ABSTRACT Android run-time|the user may decide to uninstall the ap- The responsiveness of the GUI in an Android application is plication and/or rate it negatively in the app market. an important component of the user experience. Android Android guidelines [9, 6] are very clear on the importance guidelines recommend that potentially-expensive operations of designing responsive applications. The general rule is the should not be performed in the GUI thread, but rather in following: \In any situation in which your app performs a separate threads. The responsiveness of existing code can potentially lengthy operation, you should not perform the be improved by introducing such asynchronous processing, work on the UI thread, but instead create a worker thread either manually or automatically. and do most of the work there." [9]. One simple view is that all potentially-expensive opera- There are various mechanisms for achieving this goal. Typ- tions should be removed from the GUI thread. We demon- ical examples include user-managed threads, AsynchTask, strate that this view is too simplistic, because run-time cost and IntentService. The responsiveness of existing code under reasonable conditions may often be below the thresh- can be improved by introducing these mechanisms either old for poor responsiveness. We propose a profiling ap- through manual refactoring or by using automated transfor- proach to characterize response times as a function of the mations (e.g., [12, 11]). A natural question that arises in size of a potentially-expensive resource (e.g., shared prefer- this context is the following: which operations should be re- ences store, bitmap, or SQLite database). -
Automation for Mobile Apps
automation for mobile apps SeConf 13 Workshop http://appium.io/seconf.pdf Jonathan Lipps | @jlipps | Sauce Labs @TheDanCuellar | @maudineormsby appium is the cross-platform solution for native and hybrid mobile automation appium introduction 1 2 3 4 5 6 iOS Android calabash-ios calabash-android Frank MonkeyTalk UIAutomation Robotium ios-driver UiAutomator KeepItFunctional selendroid Philosophy R1. Test the same app you submit to the marketplace R2. Write your tests in any language, using any framework R3. Use a standard automation specification and API R4. Build a large and thriving open-source community effort Platforms • Real devices (iOS, Android) • Simulators (iOS, Android, FirefoxOS) • Hybrid apps (iOS, Android, FirefoxOS) • Safari on iOS • Chrome on Android • Robot-controlled devices Architecture • Apple Instruments & UIAutomation for iOS • Google UiAutomator for Android (4.2.1 up) • Selendroid for older Android & hybrid • Selenium WebDriver interface Selenium WebDriver? • this is SeConf, isn’t it? appium.app 1 2 3 4 5 6 Appium.app • GUI for launching Appium server • Monitor status • Set preferences Appium.app • Inspector for probing your app • Create hooks for UI elements in app • Try out actions • Record / playback actions • Convert UIAutomation JS to Appium code Appium.app • Mac: stable • Windows: under development Monitor Preferences Inspector Recorder Robot support • Bitbeambot Delta-2 • http://www.bitbeam.org • Tapster • https://www.tindie.com/products/hugs/robot-that- plays-angry-birds/ Robot support • Redirects touch actions