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automated testing of Web Applications Using Combinatorial Strategies

Journal of Computer Science & Technology 2017年第1期32卷 199-210页

作者： Xiao-Fang Qi Zi-Yuan Wang Jun-Qiang Mao Peng Wang School of Computer Science and Engineering Southeast University Nanjing 211189 China Key Laboratory of Computer Network and Information Integration Ministry of Education Nanjing 211189 China School of Computer Science and Technology Nanjing University of Posts and Telecommunications Nanjing 210023 China

Recently, testing techniques based on dynamic exploration, which try to automatically exercise every possible user interface element, have been extensively used to facilitate fully testing web applications. Most of such testing tools are however not effective in reaching dynamic pages induced by form interactions due to their emphasis on handling client-side scripting. In this paper, we present a combinatorial strategy to achieve a full form test and build an automated test model. We propose an algorithm called pairwise testing with constraints （PTC） to iraplement the strategy. Our PTC algorithm uses pairwise coverage and handles the issues of semantic constraints and illegal values. We have implemented a prototype tool ComjaxTest and conducted an empirical study on five web applications. Experimental results indicate that our PTC algorithm generates less form test cases while achieving a higher coverage of dynamic pages than the general pairwise testing algorithm. Additionally, our ComjaxTest generates a relatively complete test model and then detects more faults in a reasonable amount of time, as compared with other existing tools based on dynamic exploration.

关键词： automated testing combinatorial testing web application

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Iterative Android automated testing

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Frontiers of Computer Science 2023年第5期17卷 15-26页

作者： Yi ZHONG Mengyu SHI Youran XU Chunrong FANG Zhenyu CHEN State Key Laboratory for Novel Software Technology Nanjing UniversityNanjing 210093China School of Big Data and Computer Science Chongqing College of Mobile CommunicationChongqing 400065China

With the benefits of reducing time and workforce,automated testing has been widely used for the quality assurance of mobile applications(APPs).Compared with automated testing,manual testing can achieve higher coverage in complex interactive Activities.And the effectiveness of manual testing is highly dependent on the user operation process(UOP)of experienced testers.Based on the UOP,we propose an iterative Android automated testing(IAAT)method that automatically records,extracts,and integrates UOPs to guide the test logic of the tool across the complex Activity iteratively.The feedback test results can train the UOPs to achieve higher coverage in each iteration.We extracted 50 UOPs and conducted experiments on 10 popular mobile APPs to demonstrate IAAT’s effectiveness compared with Monkey and the initial automated tests.The experimental results show a noticeable improvement in the IAAT compared with the test logic without human knowledge.Under the 60 minutes test time,the average code coverage is improved by 13.98%to 37.83%,higher than the 27.48%of Monkey under the same conditions.

关键词： quality assurance automated testing UOP test coverage

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Model-based automated testing of JavaScript Web applications via longer test sequences

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Frontiers of Computer Science 2022年第3期16卷 53-66页

作者： Pengfei GAO Yongjie XU Fu SONG Taolue CHEN School of Information Science and Technology ShanghaiTech UniversityShanghai 201210China Department of Computer Science University of SurreyGuildford GU27XHUK

JavaScript has become one of the most widely used languages for Web development.Its dynamic and event-driven features make it challenging to ensure the correctness of Web applications written in JavaScript.A variety of dynamic analysis techniques have been proposed which are,however,limited in either coverage or scalability.In this paper,we propose a simple,yet effective,model-based automated testing approach to achieve a high code-coverage within the time budget via testing with longer event sequences.We implement our approach as an open-source tool LJS,and perform extensive experiments on 21 publicly available benchmarks.On average,LJS is able to achieve 86.5%line coverage in 10 minutes.Compared with JSDEP,a state-of-the-art breadth-first search based automated testing tool enriched with partial order reduction,the coverage of LJS is 11%-19%higher than that of JSDEP on real-world large Web applications.Our empirical findings support that proper longer test sequences can achieve a higher code coverage in JavaScript Web application testing.

关键词： model-based testing automated testing JavaScript Web applications

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AWeb Application Fingerprint Recognition Method Based on Machine Learning

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 887-906页

作者： Yanmei Shi Wei Yu Yanxia Zhao Yungang Jia School of Integrated Circuit Science and Engineering Tianjin University of TechnologyTianjin300382China College of International Business Zhejiang Yuexiu UniversityShaoxing312030China School of Public Administration Zhejiang Gongshang UniversityHangzhou310018China Tianjin Branch of National Computer Network Emergency Response Technical Team/Coordination Center of China Tianjin300100China

Web application fingerprint recognition is an effective security technology designed to identify and classify web applications,thereby enhancing the detection of potential threats and attacks.Traditional fingerprint recognition methods,which rely on preannotated feature matching,face inherent limitations due to the ever-evolving nature and diverse landscape of web applications.In response to these challenges,this work proposes an innovative web application fingerprint recognition method founded on clustering techniques.The method involves extensive data collection from the Tranco List,employing adjusted feature selection built upon Wappalyzer and noise reduction through truncated SVD dimensionality reduction.The core of the methodology lies in the application of the unsupervised OPTICS clustering algorithm,eliminating the need for preannotated labels.By transforming web applications into feature vectors and leveraging clustering algorithms,our approach accurately categorizes diverse web applications,providing comprehensive and precise fingerprint recognition.The experimental results,which are obtained on a dataset featuring various web application types,affirm the efficacy of the method,demonstrating its ability to achieve high accuracy and broad coverage.This novel approach not only distinguishes between different web application types effectively but also demonstrates superiority in terms of classification accuracy and coverage,offering a robust solution to the challenges of web application fingerprint recognition.

关键词： Web application fingerprint recognition unsupervised learning clustering algorithm feature extraction automated testing network security

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