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33rd IEEE/ACM International Conference on Automated Software Engineering (ASE)

作者： Gao, Xiang Tan, Shin Hwei Dong, Zhen Roychoudhury, Abhik Natl Univ Singapore Singapore Singapore Southern Univ Sci & Technol Shenzhen Peoples R China

ISBN: (数字)9781450359375

ISBN: (纸本)9781450359375

Symbolic execution of android applications is challenging as it involves either building a customized VM for android or modeling the android libraries. Since the android Runtime evolves from one version to another, building a high-fidelity symbolic execution engine involves modeling the effect of the libraries and their evolved versions. Without simulating the behavior of android libraries, path divergence may occur due to constraint loss when the symbolic values flow into android framework and these values later affect the subsequent path taken. Previous works such as JPF-android have relied on the modeling of execution environment such as libraries. In this work, we build a dynamic symbolic execution engine for android apps, without any manual modeling of execution environment. Environment (or library) dependent control flow decisions in the application will trigger an on-demand program synthesis step to automatically deduce a representation of the library. This representation is refined on-the-fly by running the corresponding library multiple times. The overarching goal of the refinement is to enhance behavioral coverage and to alleviate the path divergence problem during symbolic execution. Moreover, our library synthesis can be made context-specific. Compared to traditional synthesis approaches which aim to synthesize the complete library code, our context-specific synthesis engine can generate more precise expressions for a given context. The evaluation of our dynamic symbolic execution engine, built on top of JDART, shows that the library models obtained from program synthesis are often more accurate than the semi-manual models in JPF-android. Furthermore, our symbolic execution engine could reach more branch targets, as compared to using the JPF-android models.

关键词： android testing Symbolic execution Program synthesis

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FuRong: Fusing Report of Automated android testing on Multi-Devices 20

FuRong: Fusing Report of Automated Android Testing on Multi-...

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42nd ACM/IEEE International Conference on Software Engineering - Companion Proceedings (ICSE-Companion) / 42nd ACM/IEEE International Conference on Software Engineering - Software Engineering in Practice (ICSE-SEIP)

作者： Tian, Yuanhan Yu, Shengcheng Fang, Chunrong Li, Peiyuan Nanjing Univ State Key Lab Novel Software Technol Nanjing Peoples R China

ISBN: (纸本)9781450371223

Automated testing has been widely used to ensure the quality of android applications. However, incomprehensible testing results make it difficult for developers to understand and fix potential bugs. This paper proposes FuRong, a novel tool, to fuse bug reports of high-readability and strong-guiding-ability via analyzing the automated testing results on multi-devices. FuRong builds a bug model with complete context information, such as screenshots, operation sequences, and logs from multi-devices, and then leverages pretrained Decision Tree classifier (with 18 bug category labels) to classify bugs. FuRong deduplicates the classified bugs via Levenshtein distance and finally generates the easy-to-understand report, not only context information of bugs, where possible causes and fix suggestions for each bug category are also provided. An empirical study of 8 open-source android applications with automated testing on 20 devices has been conducted, the results show the effectiveness of FuRong, which has a bug classification precision of 93.4% and a bug classification accuracy of 87.9%. Video URL: https://***/LUkFTc32B6k

关键词： android testing Automated testing Bug Report Bug Classification

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OAT: An Optimized android testing Framework Based on Reinforcement Learning 1

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17th International Conference on Theoretical Aspects of Software Engineering (TASE)

作者： Du, Mengjun Li, Peiyang Song, Lian Chan, W. K. Jiang, Bo Beihang Univ Sch Comp Sci & Engn State Key Lab Software Dev Environm Beijing Peoples R China City Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China

ISBN: (数字)9783031352577

ISBN: (纸本)9783031352560;9783031352577

Automated testing of android applications is always a challenging task. Deep reinforcement learning can continuously optimize the current exploration strategy through the interaction with the application under test and can explore application states that are difficult to reach in the testing process. However, existing state-of-the-art deep reinforcement learning techniques rely on coarse GUI state definitions, which make them hard to explore interesting application states even with the guidance of reward function. In this work, we propose OAT, an optimized automated testing tool for android applications based on deep reinforcement learning. OATis designedwith a pair of fine-grained state representation and reward function to provide more effective reward incentives for reinforcement learning. OAT also adopts the Monte Carlo Tree Search (MCTS) strategy to more effectively explore promising GUI states. Our experimental evaluation shows that OAT is more effective than the state-of-the-art android application testing techniques in terms of both code coverage and fault detection.

关键词： android testing Deep reinforcement learning Reward function

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Test Report Generation for android App testing Via Heterogeneous Data Analysis

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IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 2023年第5期49卷 3032-3051页

作者： Fang, Chunrong Yu, Shengcheng Su, Ting Zhang, Jing Tian, Yuanhan Liu, Yang Nanjing Univ State Key Lab Novel Software Technol Nanjing 210093 Jiangsu Peoples R China East China Normal Univ Sch Software Engn Shanghai Key Lab Trustworthy Comp Shanghai 200050 Peoples R China Nanyang Technol Univ Singapore 639798 Singapore

The rising of the android market demands higher quality assurance of android applications (apps) to sharpen the competitive edge, and techniques for traditional software have problems adapting for mobile apps. android apps often require testing on a large-scale device cluster, which produces a large amount of test reports consisting of heterogeneous data, e.g., hardware information, GUI screenshots, runtime logs. Such data are hard to merge to be unified analyzed, while they serve as an essential basis for bug inspection and fixing. Existing test report generation or analysis techniques can only handle testing data from different devices separately. They simply list all the information to app developers and have no further processing to summarize test reports. Besides, they neglect the inner connection of the heterogeneous data. Such techniques cannot improve the report reviewing effectiveness and efficiency, and they can hardly find the inner links and rules of the bug occurrence on different devices. As a result, developers still need to devote many efforts to inspect and fix bugs. In this paper, a large amount of test reports are investigated by the authors, as to construct a structured bug model to analyze heterogeneous data of the testing results. According to the investigation, we also define the Bug Inconsistency of testing results from multiple devices and build a novel bug taxonomy. In general, an automated approach is proposed to generate structured and comprehensible test reports from raw testing results from multiple devices. Based on the approach, a tool, namely BreGat, is implemented to evaluate the classification and deduplication capability of our approach. The experimental results of 30 android apps on 20 devices show that BreGat can successfully cover 83% bug categories and exclude 76% duplicate bugs. Furthermore, a user study involving 16 developers shows that our test reports are more comprehensible and BreGat greatly improves the bug inspection

关键词： Computer bugs testing Graphical user interfaces Operating systems Mobile applications Taxonomy Inspection android testing GUI testing test report generation

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A Concurrent Approach for Improving the Efficiency of android CTS testing

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JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 2018年第5期34卷 1287-1306页

作者： Liu, Chien-Hung Chen, Woei-Kae Chen, Shu-Ling Natl Taipei Univ Technol Dept Comp Sci & Informat Engn Taipei 106 Taiwan Southern Taiwan Univ Sci & Technol Dept Ind Management & Informat Tainan 700 Taiwan

The Compatibility Test Suite (CTS) is a set of JUnit tests presented by Google to help manufactures to ensure if their android devices are in compliance with the android compatibility standards. However, the CTS contains a huge number of test cases and, hence, it usually would take several hours to complete the CTS tests. This could seriously affect the development schedule of android devices, especially when the CTS test is included in the daily system integration. To reduce the time to perform CTS tests and shorten the time-to-market of android devices, this paper presents a concurrent approach for improving the CTS test efficiency. Particularly, the CTS tests are decomposed into multiple tasks that are executed on different devices concurrently. The execution results of the devices are then merged to generate the CTS test report. In addition, various task scheduling algorithms are employed and different partitioning methods are presented in the approach. A cloud-based testing platform is developed to support the proposed approach. To evaluate the effectiveness of the proposed approach, several empirical experiments were conducted. The experimental results show that the efficiency of CTS test can be much improved as the number of devices increases. Moreover, the results also indicate that the Longest Job First scheduling and mixed partitioning methods can result in better test efficiency.

关键词： android testing software testing android compatibility testing compatibility test suite CTS

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A Concurrent Approach for Improving the Efficiency of android CTS testing

A Concurrent Approach for Improving the Efficiency of Androi...

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International Computer Symposium (ICS)

作者： Liu, Chien-Hung Chen, Woie-Kae Chen, Shu-Ling Natl Taipei Univ Technol Dept Comp Sci & Informat Engn Taipei Taiwan Southern Taiwan Univ Sci & Technol Dept Management & Informat Technol Tainan Taiwan

ISBN: (纸本)9781509034383

The Compatibility Test Suite (CTS) is provided by Google to help manufactures to ensure if their android devices are in compliance with the android compatibility standards. However, the CTS contains a huge number of test cases and it usually would take several hours to complete the CTS tests. This could seriously affect the development schedule of android devices, especially when the CTS test is included in the daily system integration. To reduce the time to perform CTS tests and shorten the time-to-market of android devices, this paper presents an approach for improving the CTS test efficiency. Particularly, the CTS test is decomposed into multiple tasks to be executed on different devices concurrently. In addition, the task scheduling and partitioning methods are considered in the approach. A cloud-based testing platform is developed to support the proposed approach. The experimental results show that the efficiency of CTS test can be much improved as the number of devices increases. Moreover, the results also indicate that the Longest Job First (LJF) scheduling and mixed partitioning methods can result in better test efficiency.

关键词： android testing Software testing android Compatibilty testing Compatibility Test Suite

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android App testing: A Model for Generating Automated Lifecycle Tests 4

Android App Testing: A Model for Generating Automated Lifecy...

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4th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2020

作者： Motan, Malik Zein, Samer Birzeit University Master of Software Engineering Palestine

ISBN: (数字)9781728190907

ISBN: (纸本)9781728190907

android is currently the dominating OS in the market. An immense number of android apps is deployed to the Google Play store every year. android apps are no longer merely focusing on entertainment or socialization. In fact, the literature shows that apps specializing in critical domains such as health, education and even the military are growing in numbers. This puts more pressure on app developers to produce quality apps. Research shows that current android app testing approaches rely heavily on manual testing. Research in automatic test generation for android apps focuses mostly on automated GUI testing, with some approaches introducing model-based testing for test case inputs. However, no studies focus on generating lifecycle tests automatically, especially for testing lifecycle method conformance. In this research, we present a model-based solution approach as a tool to conduct assertion lifecycle tests automatically for android activity lifecycle callback methods. Our objective is to build a framework to generate such a model. Finally, we evaluated our proposed framework in two ways. First using a group case study. Then we evaluate our work using 10 real world open source android applications. The results of our evaluation are promising and show that our proposed framework is useful for detecting errors. © 2020 IEEE.

关键词： android Lifecycle android Apps android testing Model-Based

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Comparison Analysis of android GUI testing Frameworks by Using an Experimental Study

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Procedia Computer Science 2018年 135卷 736-748页

作者： Meiliana Irwandhi Septian Ricky Setiawan Alianto Daniel Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480

android is the most popular mobile operating systems on the market share in 2nd Quarter 2017 android operating system get 87.7% of mobile operating system on the market share. The mobile device Graphical user interfaces (GUI) are one of the main components to be tested for quality assurance. GUI testing is important since they often make up for half of the resource code of the application and GUI is used to interact with the application. Automating these tests is very useful since it saves a lot of time and money. However, the tools or frameworks that are available for automating the tests are often not suitable for developer needs, mainly because of the lack of functionality. Therefore, automated testing framework evaluation is needed. With a comparison study provided, developers will able to consider about testing framework that can fit their needs easily. In this study, we selected top 4 most used android GUI testing frameworks that will be evaluated by using experimental study. Those frameworks are: Espresso, Appium, Calabash and UI Automator. We also selected the criteria used in this study to evaluate those frameworks. We selected those criteria by identified the best criteria to testing android application base on our literature analysis. Furthermore, the study resulted in characterization of those frameworks from experiment of a simple android application.

关键词： android testing testing framework gui testing automated testing

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METFORD - Mutation testing Framework fOR android

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JOURNAL OF SYSTEMS AND SOFTWARE 2025年 222卷

作者： Vincenzi, Auri M. R. Kuroishi, Pedro H. Bispo, Joao da Veiga, Ana R. C. da Mata, David R. C. Azevedo, Francisco B. Paiva, Ana C. R. Univ Fed Sao Carlos Dept Comp Sao Carlos SP Brazil Univ Porto Fac Engn INESC TEC Porto Portugal Univ Porto Fac Engn Porto Portugal

Mutation testing maybe used to guide test case generation and as a technique to assess the quality of test suites. Despite being used frequently, mutation testing is not so commonly applied in the mobile world. One critical challenge in mutation testing is dealing with its computational cost. Generating mutants, running test cases over each mutant, and analyzing the results may require significant time and resources. This research aims to contribute to reducing android mutation testing costs. It implements mutation testing operators (traditional and android-specific) according to mutant schemata (implementing multiple mutants into a single code file). It also describes an android mutation testing framework developed to execute test cases and determine mutation scores. Additional mutation operators can be implemented in JavaScript and easily integrated into the framework. The overall approach is validated through case studies showing that mutant schemata have advantages over the traditional mutation strategy (one file per mutant). The results show mutant schemata overcome traditional mutation in all evaluated aspects with no additional cost: it takes 8.50% less time for mutant generation, requires 99.78% less disk space, and runs, on average, 6.45% faster than traditional mutation. Moreover, considering sustainability metrics, mutant schemata have 8,18% less carbon footprint than traditional strategy.

关键词： Mutation testing Mutant schemata Mobile testing android testing Mutation testing framework

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A compatibility testing platform for android multimedia applications

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MULTIMEDIA TOOLS AND APPLICATIONS 2019年第4期78卷 4885-4904页

作者： Liu, Chien-Hung Natl Taipei Univ Technol Dept Comp Sci & Informat Engn 1Sect 3Chung Hsiao E Rd Taipei 106 Taiwan

Along with the widespread use of smartphones, android has become one of the major platforms for multimedia applications (apps). However, due to the fast evolution of android operating system and the fragmentation of android devices, it becomes important for an android multimedia app to be tested on different devices to ensure that the app is compatible with and run well on any of the devices so as to provide consistent user experiences. This paper presents a cloud testing platform (CTP) that allows android multimedia apps to be tested automatically against a scalable number of physical devices in parallel. Particularly, CTP provides five types of testing to ensure the compatibility of apps from different perspectives, including GUI testing, acceptance testing, stress testing, crash testing, and installation/uninstallation testing. Further, to facilitate identifying the bugs of apps, in addition to test results, CTP also provides the video, screenshots, and performance data corresponding to the tests. Moreover, CTP can also generate a GUI state diagram that can be used to analyze app's behavior and is helpful for crash diagnosis and debugging. The case study shows that CTP can be effective in ensuring the compatibility of android multimedia apps while saving test time and effort.

关键词： Multimedia app testing android compatibility testing android testing Software testing

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