scholarly journals DroidbotX: Test Case Generation Tool for Android Applications Using Q-Learning

Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 310
Author(s):  
Husam N. Yasin ◽  
Siti Hafizah Ab Hamid ◽  
Raja Jamilah Raja Yusof
Keyword(s):  
User Interface ◽  
Test Generation ◽  
State Of The Art ◽  
Time Budget ◽  
Sequence Length ◽  
Interface Element ◽  
Test Coverage ◽  
Q Learning ◽  
Code Coverage ◽  
Android Applications

Android applications provide benefits to mobile phone users by offering operative functionalities and interactive user interfaces. However, application crashes give users an unsatisfactory experience, and negatively impact the application’s overall rating. Android application crashes can be avoided through intensive and extensive testing. In the related literature, the graphical user interface (GUI) test generation tools focus on generating tests and exploring application functions using different approaches. Such tools must choose not only which user interface element to interact with, but also which type of action to be performed, in order to increase the percentage of code coverage and to detect faults with a limited time budget. However, a common limitation in the tools is the low code coverage because of their inability to find the right combination of actions that can drive the application into new and important states. A Q-Learning-based test coverage approach developed in DroidbotX was proposed to generate GUI test cases for Android applications to maximize instruction coverage, method coverage, and activity coverage. The overall performance of the proposed solution was compared to five state-of-the-art test generation tools on 30 Android applications. The DroidbotX test coverage approach achieved 51.5% accuracy for instruction coverage, 57% for method coverage, and 86.5% for activity coverage. It triggered 18 crashes within the time limit and shortest event sequence length compared to the other tools. The results demonstrated that the adaptation of Q-Learning with upper confidence bound (UCB) exploration outperforms other existing state-of-the-art solutions.

Random GUI Testing of Android Application Using Behavioral Model

2017 ◽  
Vol 27 (09n10) ◽  
pp. 1603-1612 ◽  
Author(s):  
Woramet Muangsiri ◽  
Shingo Takada
Keyword(s):  
Static Analysis ◽  
State Of The Art ◽  
Evaluation Criteria ◽  
Behavioral Model ◽  
Code Coverage ◽  
Gui Testing ◽  
Testing Tools ◽  
Current State ◽  
Android Applications ◽  
Manual Testing

Automated GUI testing based on behavioral model is one of the most efficient testing approaches. By mining user usage, test scenarios can be generated based on statistical models such as Markov chain. However, these works require static analysis before starting the exploration which requires too much prerequisites and time. To address these challenges, we propose a behavioral-based GUI testing approach for mobile applications that achieves faster and higher coverage. The proposed approach does not conduct static analysis. It creates a behavioral model from usage logs by applying a statistical model. The events within the behavioral model are mapped to GUI components in a GUI tree. Finally, it updates the model dynamically to increase the probability of an event that rarely or never occurs when users use the application. The proposed approach was evaluated on four open-source Android applications, and compared with the state-of-the-art tools and manual testing. The main evaluation criteria are code coverage and ability to find errors. The proposed approach performed better than the current state-of-the-art automated testing tools in most aspects.

scholarly journals CONFUZZIUS: A Data Dependency-Aware Hybrid Fuzzer for Smart Contracts

2021 ◽  
Author(s):  
Christof Ferreira Torres ◽  
Antonio Ken Iannillo ◽  
Arthur Gervais ◽  
Radu State
Keyword(s):  
State Of The Art ◽  
Symbolic Execution ◽  
Hybrid Approach ◽  
Data Dependency ◽  
Smart Contracts ◽  
Dependency Analysis ◽  
Bug Detection ◽  
Code Coverage ◽  
Traditional Programs ◽  
Turing Complete

<div> <div> <p>Smart contracts are Turing-complete programs that are executed across a blockchain. Unlike traditional programs, once deployed, they cannot be modified. As smart contracts carry more value, they become more of an exciting target for attackers. Over the last years, they suffered from exploits costing millions of dollars due to simple programming mistakes. As a result, a variety of tools for detecting bugs have been proposed. Most of these tools rely on symbolic execution, which may yield false positives due to over-approximation. Recently, many fuzzers have been proposed to detect bugs in smart contracts. However, these tend to be more effective in finding shallow bugs and less effective in finding bugs that lie deep in the execution, therefore achieving low code coverage and many false negatives. An alternative that has proven to achieve good results in traditional programs is hybrid fuzzing, a combination of symbolic execution and fuzzing. In this work, we study hybrid fuzzing on smart contracts and present ConFuzzius, the first hybrid fuzzer for smart contracts. ConFuzzius uses evolutionary fuzzing to exercise shallow parts of a smart contract and constraint solving to generate inputs that satisfy complex conditions that prevent evolutionary fuzzing from exploring deeper parts. Moreover, ConFuzzius leverages dynamic data dependency analysis to efficiently generate sequences of transactions that are more likely to result in contract states in which bugs may be hidden. We evaluate the effectiveness of ConFuzzius by comparing it with state-of-the-art symbolic execution tools and fuzzers for smart contracts. Our evaluation on a curated dataset of 128 contracts and a dataset of 21K real-world contracts shows that our hybrid approach detects more bugs than state-of-the-art tools (up to 23%) and that it outperforms existing tools in terms of code coverage (up to 69%). We also demonstrate that data dependency analysis can boost bug detection up to 18%.</p> </div> </div>

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.

User Interface Consistency in the DECwindows Program

1988 ◽  
Vol 32 (5) ◽  
pp. 259-263
Author(s):  
Michael Good
Keyword(s):  
User Interface ◽  
User Interfaces ◽  
Interface Design ◽  
State Of The Art ◽  
Major Goal ◽  
Interface Consistency ◽  
Electronic Conferencing ◽  
Different Types ◽  
Innovative Techniques ◽  
Application Programs

A major goal of the DECwindows program is to provide a consistent, state-of-the-art user interface for workstation software.1 This interface extends across operating systems and many different types of application programs. Within the DECwindows program we have addressed both the technical and organizational aspects of developing consistent user interfaces across applications. Traditional methods for developing user interface consistency, such as the use of an interface style guide and toolkit, were supplemented with more innovative techniques. An exhibition and catalog of DECwindows application designs helped to develop a DECwindows school of interface design. Electronic conferencing software played an important role in facilitating communication among DECwindows contributors throughout the company. Preliminary user interviews suggest that the DECwindows interface style gives a consistent, usable feel to Digital's workstation applications.

scholarly journals Visual Tracking Using Wang–Landau Reinforcement Sampler

2020 ◽  
Vol 10 (21) ◽  
pp. 7780
Author(s):  
Dokyeong Kwon ◽  
Junseok Kwon
Keyword(s):  
Visual Tracking ◽  
Deep Neural Network ◽  
Learning Algorithm ◽  
State Of The Art ◽  
Tracking System ◽  
Network Architectures ◽  
Tracking Accuracy ◽  
Algorithm Performance ◽  
Q Learning ◽  
Number Of Visits

In this study, we present a novel tracking system, in which the tracking accuracy can be considerably enhanced by state prediction. Accordingly, we present a new Q-learning-based reinforcement method, augmented by Wang–Landau sampling. In the proposed method, reinforcement learning is used to predict a target configuration for the subsequent frame, while Wang–Landau sampler balances the exploitation and exploration degrees of the prediction. Our method can adapt to control the randomness of policy, using statistics on the number of visits in a particular state. Thus, our method considerably enhances conventional Q-learning algorithm performance, which also enhances visual tracking performance. Numerical results demonstrate that our method substantially outperforms other state-of-the-art visual trackers and runs in realtime because our method contains no complicated deep neural network architectures.

scholarly journals Multimedia and Reading Ways: a State of the Art

Comunicar ◽  
2009 ◽  
Vol 17 (33) ◽  
pp. 213-219 ◽  
Author(s):  
Javier Díaz-Noci
Keyword(s):  
User Interface ◽  
State Of The Art ◽  
Point Of View ◽  
Digital Text ◽  
Digital Edition ◽  
Digital Language

Multimedia is one of the less studied characteristics, probably because of the less-developed level of the digital language. Along with hypertext and interactivity, it is one of the characteristics that defines the digital edition. Those characteristics have been always studied from the point of view of production, although not so much from the point of view of reception. How do users read a digital text? The reader’s participation, reading depth, different trailblazing, the relation user-interface and the conception of multimedia text as a module of a database introduce major changes in the reception of the text, which can and must be studied.La multimedialidad es una de las características menos estudiadas, tal vez por menos desarrolladas, del nuevo lenguaje digital. Junto con el hipertexto y la interactividad, constituye una de las características que definen el discurso digital. Estas características siempre se han estudiado desde el punto de vista de la producción, no tanto desde el punto de vista de la recepción. ¿Cómo leen los usuarios un texto digital? La participación del lector, la profundidad de la lectura, los distintos recorridos y propósitos por la superficie y los niveles más profundos del texto, la relación del usuario con la interfaz y la concepción del texto multimedia como módulo en una base de datos introducen cambios sustanciales en la recepción del texto que pueden y deben ser estudiados.

A Commit Messages-Based Bug Localization for Android Applications

2019 ◽  
Vol 29 (04) ◽  
pp. 457-487 ◽  
Author(s):  
Tao Zhang ◽  
Wenjun Hu ◽  
Xiapu Luo ◽  
Xiaobo Ma
Keyword(s):  
Open Source ◽  
Software Maintenance ◽  
State Of The Art ◽  
Bug Localization ◽  
Two Phase ◽  
Android Apps ◽  
Bug Reports ◽  
Android Applications ◽  
The Given ◽  
General Method

Recently, there has been consistent growth in Android applications (apps). Under these circumstances, software maintenance for Android apps becomes an essential and important task. The core of software maintenance is to locate bugs in source files. Previous bug localization approaches mainly focus on open-source desktop software (e.g. Eclipse, Mozilla, GCC). Even though a few studies locate the bugs in the Android apps, they are dedicated to a special app named ZXing, without developing a general method to locate the bugs in Android apps by taking into account the unique characteristics of Android apps’ bug reports. Such characteristics include fewer number of historical bug reports, insufficient detailed description, etc. These characteristics hinder existing localization approaches from being directly delivered to Android apps, because lack of enough information degrades the performance of those localization approaches relying on historical bug reports. Commit messages include more informative data which can provide the details of reported bugs. Therefore, in this paper, we propose a novel information retrieval-based approach which utilizes commit messages to locate new bugs in Android apps. This approach not only considers the structured textual similarity between the given bug and the candidate source files, but also computes the unstructured textual similarities between the new bug and the commit messages linked to the corresponding source files. According to the experimental results on 10 popular open-source Android apps managed by GitHub, our approach outperforms the state-of-the-art bug localization methods that include BugLocator, BLUiR, and two-phase model.

scholarly journals Temporal network alignment via GoT-WAVE

2019 ◽  
Vol 35 (18) ◽  
pp. 3527-3529 ◽  
Author(s):  
David Aparício ◽  
Pedro Ribeiro ◽  
Tijana Milenković ◽  
Fernando Silva
Keyword(s):  
User Interface ◽  
State Of The Art ◽  
Source Code ◽  
Network Alignment ◽  
Supplementary Information ◽  
Temporal Network ◽  
Temporal Networks ◽  
Supplementary Data ◽  
Node Similarity ◽  
User Friendly

Abstract Motivation Network alignment (NA) finds conserved regions between two networks. NA methods optimize node conservation (NC) and edge conservation. Dynamic graphlet degree vectors are a state-of-the-art dynamic NC measure, used within the fastest and most accurate NA method for temporal networks: DynaWAVE. Here, we use graphlet-orbit transitions (GoTs), a different graphlet-based measure of temporal node similarity, as a new dynamic NC measure within DynaWAVE, resulting in GoT-WAVE. Results On synthetic networks, GoT-WAVE improves DynaWAVE’s accuracy by 30% and speed by 64%. On real networks, when optimizing only dynamic NC, the methods are complementary. Furthermore, only GoT-WAVE supports directed edges. Hence, GoT-WAVE is a promising new temporal NA algorithm, which efficiently optimizes dynamic NC. We provide a user-friendly user interface and source code for GoT-WAVE. Availability and implementation http://www.dcc.fc.up.pt/got-wave/ Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals An Efficient Functional Test Generation Method For Processors Using Genetic Algorithms

2015 ◽  
Vol 66 (4) ◽  
pp. 185-193 ◽  
Author(s):  
Ján Hudec ◽  
Elena Gramatová
Keyword(s):  
Genetic Algorithms ◽  
Test Generation ◽  
Functional Test ◽  
Evolutionary Strategies ◽  
Instruction Set ◽  
Functional Tests ◽  
Automatic Test Generation ◽  
Code Coverage ◽  
Fitness Functions

Abstract The paper presents a new functional test generation method for processors testing based on genetic algorithms and evolutionary strategies. The tests are generated over an instruction set architecture and a processor description. Such functional tests belong to the software-oriented testing. Quality of the tests is evaluated by code coverage of the processor description using simulation. The presented test generation method uses VHDL models of processors and the professional simulator ModelSim. The rules, parameters and fitness functions were defined for various genetic algorithms used in automatic test generation. Functionality and effectiveness were evaluated using the RISC type processor DP32.

Sign in / Sign up

Export Citation Format

Share Document