软件测试中英文对照外文翻译文献

STUDY PAPER ON TEST CASE GENERATION FOR GUI BASED TESTING

ABSTRACT

With the advent of WWW and outburst in technology and software development, testing the software

became a major concern. Due to the importance of the testing phase in a software development lifecycle,

testing has been divided into graphical user interface (GUI) based testing, logical testing, integration

testing, etc.GUI Testing has become very important as it provides more sophisticated way to interact with

the software. The complexity of testing GUI increased over time. The testing needs to be performed in a

way that it provides effectiveness, efficiency, increased fault detection rate and good path coverage. To

cover all use cases and to provide testing for all possible (success/failure) scenarios the length of the test

sequence is considered important. Intent of this paper is to study some techniques used for test case

generation and process for various GUI based software applications.

KEYWORDS

GUI Testing, Model-Based Testing, Test Case, Automated Testing, Event Testing.

1. INTRODUCTION

Graphical User Interface (GUI) is a program interface that takes advantage of the computer's

graphics capabilities to make the program easier to use. Graphical User Interface (GUI) provides

user an immense way to interact with the software [1]. The most eminent and essential parts of

the software that is being used today are Graphical User Interfaces (GUIs) [8], [9]. Even though

GUIs provides user an easy way to use the software, they make the development process of the software tangled [2].

Graphical user interface (GUI) testing is the process of testing software's graphical user interface

to safeguard it meets its written specifications and to detect if application is working functionally correct. GUI testing involves performing some tasks and comparing the result with the expected output. This is performed using test cases. GUI Testing can be performed either manually by

humans or automatically by automated methods.

Manual testing is done by humans such as testers or developers itself in some cases and it is often

error prone and there are chances of most of the test scenarios left out. It is very time consuming

also. Automated GUI Testing includes automating testing tasks that have been done manually before, using automated techniques and tools. Automated GUI testing is more, efficient, precise, reliable and cost effective.

A test case normally consists of an input, output, expected result and the actual result. More than

one test case is required to test the full functionality of the GUI application. A collection of test

cases are called test suite. A test suite contains detailed guidelines or objectives for each

collection of test cases.

Model Based Testing (MBT) is a quick and organized method which automates the testing process through automated test suite generation and execution techniques and tools [11]. Model based testing uses the directed graph model of the GUI called event-interaction graph (EIG) [4] and event semantic interaction graph (ESIG). Event interaction graph is a refinement of event flow graph (EFG) [1]. EIG contains events that interact with the business logic of the GUI application. Event Semantic Interaction (ESI) is used to identify set of events that need to be tested together in multi-way interactions [3] and it is more useful when partitioning the events according to its functionality.

This paper is organized as follow: Section 2 provides some techniques, algorithms used to generate test cases, a method to repair the infeasible test suites are described in section 3, GUI testing on various types of softwares or under different conditions are elaborated in section 4, section 5 describes about testing the GUI application by taking event context into consideration and last section concludes the paper.

2. TEST CASE GENERATION

2.1. Using GUI Run-Time State as Feedback

Xun Yuan and Atif M Memon [3], used GUI run time state as feedback for test case generation and the feedback is obtained from the execution of a seed test suite on an Application Under Test (AUT).This feedback is used to generate additional test cases and test interactions between GUI events in multiple ways. An Event Interaction Graph (EIG) is generated for the application to be tested and seed test suites are generated for two-way interactions of GUI events. Then the test suites are executed and the GUI’s run time state is recorded. This recorded GUI run time state is used to obtain Event Semantic Interaction(ESI) relationship for the application and these ESI are used to obtain the Event Semantic Interaction Graph(ESIG).The test cases are generated and ESIGs is capable of managing test cases for more than two-way interactions and hence forth 2-, 3-,4-,5- way interactions are tested. The newly generated test cases are tested and additional faults are detected. These steps are shown in Figure 1. The fault detection effectiveness is high than the two way interactions and it is because, test cases are generated and executed for combination of events in different execution orders.

There also some disadvantages in this feedback mechanism. This method is designed focusing on GUI applications. It will be different for applications that have intricate underlying business logic and a simple GUI. As multi-way interactions test cases are generated, large number of test cases will be generated. This feedback mechanism is not automated.

Figure 1. Test Case Generation Using GUI Runtime as Feedback

2.2. Using Covering Array Technique

Xun Yuan et al [4], proposed a new automated technique for test case generation using covering arrays (CA) for GUI testing. Usually 2-way covering are used for testing. Because as number of events in a sequence increases, the size of test suite grows large, preventing from using sequences longer than 3 or 4. But certain defects are not detected using this coverage strength. Using this technique long test sequences are generated and it is systematically sampled at particular coverage strength. By using covering arrays t-way coverage strength is being maintained, but any length test sequences can be generated of at least t. A covering array, CA(N; t, k, v), is an N × k array on v symbols with the property that every N × t sub-array contains all ordered subsets of size t of the v symbols at least once.

As shown in Figure 2, Initially EIG model is created which is then partitioned into groups of interacting events and then constraints are identified and used to generate abstract model for testing. Long test cases are generated using covering array sampling. Event sequences are generated and executed. If any event interaction is missed, then regenerate test cases and repeat the steps.

The disadvantages are event partition and identifying constraints are done manually.

Figure 2. Test Generation Using Covering Array

2.3. Dynamic Adaptive Automated test Generation

Xun Yuan et al [5], suggested an algorithm to generate test suites with fewer infeasible test cases and higher event interaction coverage. Due to dynamic state based nature of GUIs, it is necessary and important to generate test cases based on the feedback from the execution of tests. The proposed framework uses techniques from combinatorial interaction testing to generate tests and basis for combinatorial interaction testing is a covering array. Initially smoke tests are generated and this is used as a seed to generate Event Semantic Interaction (ESI) relationships. Event Semantic Interaction Graph is generated from ESI. Iterative refinement is done through genetic algorithm. An initial model of the GUI event interactions and an initial set of test sequences based on the model are generated. Then a batch of test cases are generated and executed. Code coverage is determined and unexecutable test cases are identified. Once the infeasible test cases are identified, it is removed and the model is updated and new batch of test cases are generated and the steps are followed till all the uncovered ESI relationships are covered. These automated test case generation process is shown in Figure 3. This automated test generation also provides validation for GUIs.

The disadvantages are event contexts are not incorporated and need coverage and test adequacy criteria to check how these impacts fault detection.

Figure 3. Automated Test Case Generation

3. REPAIRING TEST SUITES

Si Huang et al [6], proposed a method to repair GUI test suites using Genetic algorithm. New test cases are generated that are feasible and Genetic algorithm is used to develop test cases that provide additional test suite coverage by removing infeasible test cases and inserting new feasible test cases. A framework is used to automatically repair infeasible test cases. A graph model such as EFG, EIG, ESIG and the ripped GUI structure are used as input. The main controller passes

generator along with the strength of testing. This covering array generator generates an initial set of event sequences. The covering array information is send to test case assembler and it assembles this into concrete test cases. These are passed back to the controller and test suite repair phase begins. Feasible test cases are returned by the framework once the repair phase is complete. Genetic algorithm is used as a repair algorithm. An initial set of test cases are executed and if there is no infeasible test cases, it exits and is done. If infeasible test cases are present, it then begins the repair phase. A certain number of iterations are set based on an estimate of how large the repaired test suite will be allowed to grow and for each iteration the genetic algorithm is executed. The algorithm adds best test case to the final test suites. Stopping criteria’s are used to stop the iterations.

The advantages are it generates smaller test suites with better coverage on the longer test sequences. It provides feasible test cases. But it is not scalable for larger applications as execution time is high. As GUI ripping is used, the programs that contain event dependencies may not be discovered.

4. GUI TESTING ON VARIOUS APPLICATIONS

4.1. Industrial Graphical User Interface Systems

Penelope Brooks et al [7], developed GUI testing methods that are relevant to industry applications that improve the overall quality of GUI testing by characterizing GUI systems using data collected from defects detected to assist testers and researchers in developing more effective test strategies. In this method, defects are classified based on beizer’s defect taxonomy. Eight levels of categories are present each describing specific defects such as functional defects, functionality as implemented, structural defects, data defects, implementation defects, integration defects, system defects and test defects. The categories can be modified and added according to the need. If any failures occur, it is analyzed under which defect category it comes and this classification is used to design better test oracle to detect such failures, better test case algorithm may be designed and better fault seeding models may be designed.

Goal Question Metric (GQM) Paradigm is used. It is used to analyze the test cases, defects and source metrics from the tester / researcher point of view in the context of industry-developed GUI software. The limitations are, the GUI systems are characterized based on system events only. User Interactions are not included.

4.2. Community-Driven Open Source GUI Applications

Qing Xie and Atif M. Memon [8], presented a new approach for continuous integration testing of web-based community-driven GUI-based Open Source Software(OSS).As in OSS many developers are involved and make changes to the code through WWW, it is prone to more defects and the changes keep on occurring. Therefore three nested techniques or three concentric loops are used to automate model-based testing of evolving GUI-based OSS. Crash testing is the innermost technique operates on each code check-in of the GUI software and it is executed frequently with an automated GUI testing intervention and performs quickly also. It reports the software crashes back to the developer who checked in the code. Smoke testing is the second technique operates on each day's GUI build and performs functional reference testing of the newly integrated version of the GUI, using the previously tested version as a baseline. Comprehensive Testing is the outermost third technique conducts detailed comprehensive GUI integration testing of a major GUI release and it is executed after a major version of GUI is available. Problems are reported to all the developers who are part of the development of the particular version.

flaws that persist across multiple versions GUI-based OSS are detected by this approach fully automatically. It provides feedback. The limitation is that the interactions between the three loops are not defined.

4.3. Continuously Evolving GUI-Based Software Applications

Qing Xie and Atif M. Memon [9], developed a quality assurance mechanism to manage the quality of continuously evolving software by Presenting a new type of GUI testing, called crash testing to help rapidly test the GUI as it evolves. Two levels of crash testing is being described: immediate feedback-based crash testing in which a developer indicates that a GUI bug was fixed in response to a previously reported crash; only the select crash test cases are re run and the developer is notified of the results in a matter of seconds. If any code changes occur, new crash test cases are generated and executed on the GUI. Test cases are generated that can be generated and executed quickly and cover all GUI functionalities. Once EIG is obtained, a boolean flag is associated with each edge in the graph. During crash testing, once test cases that cover that particular edge are generated, then the flag is set. If any changes occur, boolean flag for each edge is retained. Test cases are executed and crashes during test execution are used to identify serious problems in the software. The crash testing process is shown in Figure 4. The effectiveness of crash test is known by the total number of test cases used to detect maximum faults. Significantly, test suite size has no impact on number of bugs revealed.

This crash testing technique is used to maintain the quality of the GUI application and it also helps in rapidly testing the application. The drawbacks are, this technique is used for only testing GUI application and cannot used in web applications, Fault injection or seeding technique, which is used to evaluate the efficiency of the method used is not applied here.

Figure 4. Crash Testing Process

4.4. Rapidly Evolving Software

Atif M. Memon et al [10], made several contributions in the area of GUI smoke testing in terms of GUI smoke test suites, their size, fault detection ability and test oracle. Daily Automated Regression Tester (DART) framework is used to automate GUI smoke testing. Developers work on the code during day time and DART automatically launches the Application Under Test (AUT) during night time, builds it and runs GUI smoke tests. Coverage and error report are mailed to developer. In DART all the process such as Analyzing the AUT’s GUI structure using GUI ripper, Test case generation, Test oracle generation, Test case executor, Examining the

and test oracles are generated. Fault seeding is used to evaluate fault detection techniques used. An adequate number of faults of each fault type are seeded fairly.

The disadvantages are Some part of code are missed by smoke tests, Some of the bugs reported by DART are false positive, Overall effectiveness of DART depends on GUI ripper capabilities, Not available for industry based application testing, Faults that are not manifested on the GUI will go undetected

5. INCORPORATING EVENT CONTEXT

Xun Yuan et al [1], developed a new criterion for GUI testing. They used a combinatorial interaction testing technique. The main motivation of using combinatorial interaction is to incorporate context and it also considers event combinations, sequence length and include all possible event. Graph models are used and covering array is used to generate test cases which are the basis for combinatorial interaction testing.

A tool called GUITAR (GUI Testing Framework) is used for testing and this provides functionalities like generate test cases, execute test cases, verify correctness and obtain coverage reports. Initially using GUI ripper, a GUI application is converted into event graph and then the events are grouped depending on functionality and constraints are identified. Covering array is generated and test sequences are produced. Test cases are generated and executed. Finally coverage is computed and a test adequacy criterion is analyzed.

The advantages are: contexts are incorporated, detects more faults when compared to the previous techniques used. The disadvantages are infeasible test cases make some test cases unexecutable, grouping events and identifying constraints are not automated.

Figure 5. Testing Process

6. CONCLUSIONS

In this paper, some of the various test case generation methods and various types of GUI testing adapted for different GUI applications and techniques are studied. Different approaches are being used under various testing environment. This study helps to choose the test case generation technique based on the requirements of the testing and it also helps to choose the type of GUI test to perform based on the application type such as open source software, industrial software and the software in which changes are checked in rapidly and continuously.

REFERENCES

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[2]Xun Yuan, Myra B. Cohen, Atif M. Memon, (2010) “GUI Interaction Testing: Incorporating Event Context”, IEEE Transactions on Software Engineering, vol. 99.

A. M. Memon, M. E. Pollack, and M. L. Soffa, (2001) “Hierarchical GUI test case generation using automated planning”, IEEE Transactions on Software Engineering, Vol. 27, no. 2, pp. 144-155.

X. Yuan and A. M. M emon, (2007) “Using GUI run-time state as feedback to generate test cases”, in International Conference on Software Engineering (ICSE), pp. 396-405.

X. Yuan, M. Cohen, and A. M. Memon, (2007) “Covering array sampling of input event sequences for automated GUI testing”, in International Conference on Automated Software Engineering (ASE), pp. 405-408.

X. Yuan, M. Cohen, and A. M. Memon, (2009) “Towards dynamic adaptive automated test generation for graphical user interfaces”, in First International Workshop on TESTing Techniques & Experimentation Benchmarks for Event-Driven Software (TESTBEDS), pp. 1-4.

Si Huang, Myra Cohen, and Atif M. Memon, (2010) “Repairing GUI Test Suites Using a Genetic Algorithm, “in Proceedings of the 3rd IEEE InternationalConference on Software Testing Verification and Validation (ICST).

P. Brooks, B. Robinson, and A. M. Memon, (2009) “An initial characterization of industrial graphical user interface systems”, in ICST 2009: Proceedings of the 2nd IEEE International Conference on Software Testing, Verification and Validation, Washington, DC, USA: IEEE Computer Society.

Q. Xie, and A.M. Memon (2006) “Model-based testing of community driven open-source GUI applications”, in International Conference on Software Maintenance (ICSM), pp. 145-154.

Q. Xie and A. M. Memon, (2005) “Rapid “crash testing” for continuously evolving GUI- based software applications”, in International Conference on Software Maintenance (ICSM), pp. 473-482.

A. M. Memon and Q. Xie, (2005) “Studying the fault-detection effectiveness of GUI test cases for rapidly evolving software”, IEEE Transactions on Software Engineering, vol. 31, no. 10, pp. 884-896.

U. Farooq, C. P. Lam, and H. Li, (2008) “Towards automated test sequence generation”, in Australian Software Engineering Conference, pp. 441-450.

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研究基于GUI测试生成的测试用例

摘要

随着 WWW的出现和信息技术与软件开发的发展，软件测试成为一个主要问题。由于软件开发生命周期中的测试阶段的重要性，测试划分为图形用户界面(GUI) 基于测试、逻辑测试、集成测试等。GUI 测试已成为非常重要的部分，因为它提供了更加先进的方式与软件交互。随着时间的推移，测试 GUI 的复杂性不断增加。它提供了效能、效率、增加了故障检测率和良好的路径覆盖的方式执行测试的需要。涵盖所有用例，并提供所有可能的（成功/失败）情况都测试的测试长度序列被认为是重要的。本文的目的是研究一些用于测试用例生成的技术和基于过程的各种图形用户界面的软件应用。

关键字

GUI测试，基于模型的测试，测试用例，自动化测试，事件测试。

1、介绍

图形用户界面 (GUI) 是一个程序界面，充分利用了计算机的图形功能，使程序更易于使用。图形用户界面 (GUI) 为用户提供了交互软件非常好的途径。现今被使用的最杰出和最必要的软件是图形用户界面 (GUIs)。即使图形用户界面提供了用户使用软件的简单方法，但是它们会使开发过程的软件复杂化。

图形用户界面 (GUI) 测试是过程的软件测试，以保障它满足其书面的规格，并检测应用程序是否正确工作。GUI 测试涉及执行一些任务，并比较结果与预期的输出。这是使用测试用例执行的。GUI 测试可以由人类手动或通过自动化的方法自动执行。

手动测试通过人类如测试人员或开发人员本身在某些情况下，通常是容易出错和有很大部分遗漏的测试方案的时候进行的。它是非常耗时的。自动化 GUI 测试包括自动化测试任务，必须在手动完成之前，使用自动化的技术和工具。自动化 GUI 测试高效、精确、可靠和低成本。

一个测试用例通常包括输入、输出、预期结果和实际结果。多个测试用例是被需要的，用来测试 GUI 应用程序的全部功能。测试用例的集合称为测试套件。测试套件包含详细的指引或测试用例的每个集合的目标。

模型基于测试 (MBT) 是一种快速的和有组织的方法，可以在自动测试过程中通过自动化的测试套件的生成和执行的技术和工具测试。基于模型的测试使用GUI 称为事件交互图 (EIG) 和事件语义的交互图（ESIG）的有向的图模型。事件交互图是细化的事件流图 (EFG) 。EIG 包含与 GUI 应用程序的业务逻辑进行交互的事件。事件语义互动 (ESI) 用于标识组需要一起测试，在多路互动中的事件和分区的事件，根据其功能时更有用。

2、测试用例生成

2.1、使用GUI运行时状态反馈

Xun Yuan和Atif M Menmon使用 GUI 测试用例生成的反馈和从执行种子测试套件对应用程序下测试（AUT）获得的反馈。此反馈用于生成附加测试用例和在GUI事件中以多种方式之间进行交互。为进行测试的应用程序生成事件交互图(EIG) 和双向交互的 GUI 事件生成的种子测试套件。然后执行测试套件和记录GUI的运行时的状态。此GUI运行时状态记录用于获取应用程序的事件语义交互(ESI)关系，这些ESI用于获取事件语义互动图(ESIG)。生成测试用例和ESIGs 是能够管理多个双向交互测试用例，因此提出 2-、3-，4-，5-方式交互进行测试。新生成的测试案例都经过测试，并附加故障检测。这些步骤如图1所示。故障检测效率高于两种方式的相互作用，这是因为，生成测试用例并以不同的决策执行不同的事件组合。

此信息反馈机制也有一些弊端。此方法被设计的重点在GUI应用程序。它将不同的应用程序具有复杂基础业务逻辑和一个简单的GUI。由于生成多路交互测试用例，将会生成大量的测试用例。这种反馈机制不被自动化。

中英文参考文献格式

中文参考文献格式 参考文献（即引文出处）的类型以单字母方式标识： M——专著，C——论文集，N——报纸文章，J——期刊文章，D——学位论文，R——报告，S——标准，P——专利；对于不属于上述的文献类型，采用字母“Z”标识。 参考文献一律置于文末。其格式为： （一）专著 示例 [1] 张志建.严复思想研究[M]. 桂林：广西师范大学出版社，1989. [2] 马克思恩格斯全集：第1卷[M]. 北京：人民出版社，1956. [3] [英]蔼理士.性心理学[M]. 潘光旦译注.北京：商务印书馆，1997. （二）论文集 示例 [1] 伍蠡甫.西方文论选[C]. 上海：上海译文出版社，1979. [2] 别林斯基.论俄国中篇小说和果戈里君的中篇小说[A]. 伍蠡甫.西方文论选：下册[C]. 上海：上海译文出版社，1979. 凡引专著的页码，加圆括号置于文中序号之后。 （三）报纸文章 示例 [1] 李大伦.经济全球化的重要性[N]. 光明日报，1998-12-27，（3） （四）期刊文章 示例 [1] 郭英德.元明文学史观散论[J]. 北京师范大学学报（社会科学版），1995（3）. （五）学位论文 示例 [1] 刘伟.汉字不同视觉识别方式的理论和实证研究[D]. 北京：北京师范大学心理系，1998. （六）报告 示例 [1] 白秀水，刘敢，任保平. 西安金融、人才、技术三大要素市场培育与发展研究[R]. 西安：陕西师范大学西北经济发展研究中心，1998. （七）、对论文正文中某一特定内容的进一步解释或补充说明性的注释，置于本页地脚，前面用圈码标识。 参考文献的类型 根据GB3469-83《文献类型与文献载体代码》规定，以单字母标识： M——专著（含古籍中的史、志论著） C——论文集 N——报纸文章 J——期刊文章 D——学位论文 R——研究报告 S——标准 P——专利 A——专著、论文集中的析出文献 Z——其他未说明的文献类型 电子文献类型以双字母作为标识： DB——数据库 CP——计算机程序 EB——电子公告

中英文论文对照格式

英文论文APA格式 英文论文一些格式要求与国内期刊有所不同。从学术的角度讲，它更加严谨和科学，并且方便电子系统检索和存档。 版面格式

表格 表格的题目格式与正文相同，靠左边，位于表格的上部。题目前加Table后跟数字，表示此文的第几个表格。 表格主体居中，边框粗细采用0.5磅；表格内文字采用Times New Roman，10磅。 举例： Table 1. The capitals, assets and revenue in listed banks

图表和图片 图表和图片的题目格式与正文相同，位于图表和图片的下部。题目前加Figure 后跟数字，表示此文的第几个图表。图表及题目都居中。只允许使用黑白图片和表格。 举例： Figure 1. The Trend of Economic Development 注：Figure与Table都不要缩写。 引用格式与参考文献 1. 在论文中的引用采取插入作者、年份和页数方式，如"Doe (2001, p.10) reported that …" or "This在论文中的引用采取作者和年份插入方式，如"Doe (2001, p.10) reported that …" or "This problem has been studied previously (Smith, 1958, pp.20-25)。文中插入的引用应该与文末参考文献相对应。 举例：Frankly speaking, it is just a simulating one made by the government, or a fake competition, directly speaking. (Gao, 2003, p.220). 2. 在文末参考文献中，姓前名后，姓与名之间以逗号分隔；如有两个作者，以and连接；如有三个或三个以上作者，前面的作者以逗号分隔，最后一个作者以and连接。 3. 参考文献中各项目以“点”分隔，最后以“点”结束。 4. 文末参考文献请按照以下格式：

中英文论文参考文献标准格式 超详细

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————————————————————————————————作者：————————————————————————————————日期：

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