Verifying android applications using Java PathFinder

Merwe, Heila van der; Merwe, Brink van der; Visser, Willem

doi:10.1145/2382756.2382797

Cited by 67 publications

(43 citation statements)

References 4 publications

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“…In our previous work [4], [5] we created an Android environment model manually to verify Android applications using JPF. We found that the Android environment is very complex and that components often have references and dependencies on other parts of the system or native libraries without which they would not be setup correctly or they might not run at all.…”

Section: A Environment Modelingmentioning

confidence: 99%

“…The first paper entitled "Verifying Android Applications on Java PathFinder" [4], describes the design and implementation of JPF-Android. The second paper, "Execution and Property Specifications for JPF-Android" [5], discusses the syntax of JPF-Android's input script and how events are simulated on the application under test and the addition of Checklists to monitor and verify the execution of Android applications during runtime.…”

Section: Progressmentioning

confidence: 99%

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Verification of Android Applications

Merwe

2015

2015 IEEE/ACM 37th IEEE International Conference on Software Engineering

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This study investigates an alternative approach to analyze Android applications using model checking. We develop an extension to Java PathFinder (JPF) called JPF-Android to verify Android applications outside of the Android platform. JPF is a powerful Java model checker and analysis engine that is very effective at detecting corner-case and hard-to-find errors using its fine-grained analysis capabilities. JPF-Android provides a simplified model of the Android application framework on which an Android application can run and it can generate input events or parse an input script containing sequences of input events to drive the execution of the application. JPF-Android traverses all execution paths of the application by simulating these input events and can detect common property violations such as deadlocks and runtime exceptions in Android applications. It also introduces user defined execution specifications called Checklists to verify the flow of application execution.

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Section: A Environment Modelingmentioning

confidence: 99%

Section: Progressmentioning

confidence: 99%

Verification of Android Applications

Merwe

2015

2015 IEEE/ACM 37th IEEE International Conference on Software Engineering

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“…In contrast, our approach utilizes information from symbolic execution also when constructing the sequencing of events. Several other symbolic execution tools have been build specifically for Android [14,25]. Related tools for automated testing of web applications, which are also driven by user events, include Apollo [6] for PHP and Kudzu [23] for JavaScript.…”

Section: Related Workmentioning

confidence: 99%

Automated testing with targeted event sequence generation

Jensen

Prasad

Møller

2013

Proceedings of the 2013 International Symposium on Software Testing and Analysis

161

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Automated software testing aims to detect errors by producing test inputs that cover as much of the application source code as possible. Applications for mobile devices are typically event-driven, which raises the challenge of automatically producing event sequences that result in high coverage. Some existing approaches use random or model-based testing that largely treats the application as a black box. Other approaches use symbolic execution, either starting from the entry points of the applications or on specific event sequences. A common limitation of the existing approaches is that they often fail to reach the parts of the application code that require more complex event sequences.We propose a two-phase technique for automatically finding event sequences that reach a given target line in the application code. The first phase performs concolic execution to build summaries of the individual event handlers of the application. The second phase builds event sequences backward from the target, using the summaries together with a UI model of the application. Our experiments on a collection of open source Android applications show that this technique can successfully produce event sequences that reach challenging targets.

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“…Thus, they assume the tester has a valid and complete model of the application. Van der Merwe et al [van der Merwe et al, 2012] present a model checking approach to verify Android applications as an extension to Java PathFinder 1 (JPF). This extension enables the Android AUT's code to be run on the Java Virtual Machine using different event sequences to detect when errors occur.…”

Section: Functional Sustainabilitymentioning

confidence: 99%

Automated Pattern-Based Testing of Mobile Applications

Morgado

Paiva

Faria

2014

2014 9th International Conference on the Quality of Information and Communications Technology

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Testing is essential to improve the quality of a product and is, thus, a crucial part of any development process. However, the amount of time and resources companies dedicate to it is usually reduced, which justifies the high focus of the community on improving testing automation. Considering the importance smartphones have acquired in our daily lives, it is extremely important to define techniques to test mobile applications in order to ensure their quality.This document presents a testing approach and tool (iMPAcT) to improve the automation of mobile testing based on the presence of recurring behaviour, UI Patterns. It combines reverse engineering, pattern matching and testing. The reverse engineering process is responsible for crawling the application, i.e. to analyse the state of the application and to interact with it by firing events. The pattern matching tries to identify the presence of UI patterns based on a catalogue of patterns. When a UI Pattern from the catalogue is detected, a test strategy is applied. These test strategies are called UI Test Patterns. These three phases work in an iterative way: the patterns and identified and tested between firing of events, i.e. the process alternates between exploring the application and testing the UI Patterns. The process is dynamic and fully automatic not requiring any previous knowledge about the application under test.A catalogue of patterns is presented in this document. It has UI Patterns to identify on mobile applications and UI Test Patterns defining generic test strategies to test them. These patterns are generic and, thus, can be applied to any application.In order to validate the overall approach we have conducted three experiments. The goal is to analyse the capacity of iMPAcT of finding failures and assess if the results are reliable. In addition, we also measured the execution time and events coverage. Este documento apresenta uma abordagem de teste, e respetiva ferramenta (iMPAcT), para melhorar a automação de teste de aplicações móveis baseado na presença de comportamento recorrente, padrões de UI. Esta abordagem combina engenharia reversa, deteção de padrões e teste. O processo de engenharia reversa é responsável pela exploração da aplicação, ou seja, pela análise do estado da aplicação e a interação com ela através de eventos. O processo de deteção de padrões baseia-se num catálogo de padrões para identificar padrões de UI. Quando um padrão de UI do catálogo é detetado, uma estratégia de teste é aplicada. Estas estratégias de teste denominam-se padrões de teste. Estas três fases trabalham de forma iterativa: os padrões são identificados e testados entre eventos, ou seja, o processo alterna entre a exploração da aplicação e o teste dos padrões de UI. O processo é dinâmico e completamente automático e não necessita de qualquer conhecimento prévio acerca da aplicação a testar.Um catálogo de padrões é apresentado neste documento. Contém padrões de UI para serem identificados em aplicações móveis e padrões de teste que definem estratégias ...

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Verifying android applications using Java PathFinder

Cited by 67 publications

References 4 publications

Verification of Android Applications

Verification of Android Applications

Automated testing with targeted event sequence generation

Automated Pattern-Based Testing of Mobile Applications

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