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Collaborative Research: SHF: Small: Reuse and Migration of GUI Tests

Collaborative Research: SHF: Small: Reuse and Migration of GUI Tests
协作研究:SHF:小型:GUI 测试的重用和迁移
批准号:
2006278
负责人:
Na Meng
金额:
$25.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-08-01 至 2024-07-31

项目摘要

项目成果

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中文摘要
翻译
具有图形用户界面(gui)的软件应用程序已成为人们日常生活中必不可少的一部分,为了确保其质量,需要进行充分的测试。当手动执行GUI测试时,它是一个昂贵且乏味的过程,需要许多测试人员探索用户界面并检查输出是否如预期的那样。相比之下,由于缺乏人类测试人员通常拥有的领域知识,现有的自动化测试技术效率较低。在这个项目中,研究人员将探索手动GUI测试的重用和迁移,这是补充现有自动GUI测试研究的另一种途径。该项目背后的直观观察是,开发人员倾向于在同一应用程序的不同平台版本或同一领域内的不同应用程序中使用类似的GUI设计。因此,考虑到应用程序之间细微的实现差异,可以通过适当的调整来重用探索序列、输入值和预期输出。该项目有望提高GUI测试过程的覆盖率和生产力,从而产生具有更高质量和更少缺陷的GUI应用程序。此外,合并的培训和教育活动将为参与者提供获得研究经验的机会,成为高素质的研究人员和实践者。在这个项目中,pi将回答研究问题:是否以及如何在自动GUI测试中重用现有的GUI测试并进行必要的调整。特别是,研究人员将致力于生成GUI代码嵌入来表示GUI视图的语义,并开发新的GUI视图映射技术来映射不同应用程序之间的GUI视图。研究人员还将研究如何将现有GUI测试中的输入值约束和事件序列约束提取为领域知识,如何跨平台和应用程序边界转换这些知识,以及如何将转换后的知识纳入目标应用程序的自动GUI测试生成过程。此外,研究人员将开发技术来识别现有测试oracle的潜在可重用性,基于测量它们与新上下文的适合性,以及通过总结同一领域中软件应用程序的共同行为来创建新测试oracle的技术。这个项目的发现旨在阐明重用和迁移任何测试用例(如单元测试和集成测试)的更普遍的问题,以及创建有意义的测试oracle的开放问题的解决方案。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
Software applications with Graphical User Interfaces (GUIs) have become essential in people's daily lives, and sufficient testing is a necessity to ensure their quality. When performed manually, GUI testing is a costly and tedious process requiring many human testers to explore the user interface and check whether the output is as expected. In contrast, existing automated testing techniques are less effective due to the lack of availability of domain knowledge that human testers typically possess. In this project, the investigators will explore the reuse and migration of manual GUI tests, an alternative route to complement existing automatic GUI testing research. The intuitive observation behind the project is that developers tend to use similar GUI designs in different platform versions of a same application or different applications within the same domain. Therefore, it is possible to reuse the exploration sequences, input values, and expected output with proper adaptations taking into account the subtle implementation differences between applications. The project is expected to enhance the coverage and productivity of GUI-testing processes, leading to GUI applications with higher quality and fewer defects. Additionally, the incorporated training and education activities will provide opportunities for participants to acquire research experience and become highly qualified researchers and practitioners. In this project, the PIs are going to answer the research question: whether and how existing GUI tests can be reused in automatic GUI testing with necessary adaptation. In particular, the investigators will work on the generation of GUI-code embeddings to represent the semantics of GUI views and develop novel GUI-view mapping techniques to map GUI views among different applications. The investigators will also study how input-value constraints and event-sequence constraints in existing GUI tests can be extracted as domain knowledge, how such knowledge can be translated across platform and application boundaries, as well as how the translated knowledge can be incorporated into the automatic GUI-test generation process of the target application. Moreover, the investigators will develop techniques to identify the potential reusability of existing test oracles based on measuring their fitness with the new context, and techniques to create new test oracles by summarizing common behaviors of software applications in the same domain. The findings of this project are intended to shed light on the more general problem of reusing and migrating any test cases such as unit tests and integration tests, as well as the solution to the open problem of creating meaningful test oracles.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(1)
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科研奖励(0)
会议论文
DOI: 10.1109/saner53432.2022.00047
发表时间: 2022-03
期刊: 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)
影响因子: --
作者: [Yan Zhao;Enyi Tang;Haipeng Cai;Xi Guo;Xiaoyin Wang;Na Meng]
通讯作者: Yan Zhao;Enyi Tang;Haipeng Cai;Xi Guo;Xiaoyin Wang;Na Meng
CAREER: Data-Driven Debugging of Complex Program Changes
CRII: SHF: Analysis and Automation of Global Systematic Changes
国内基金
海外基金
Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    SATOSHI NAWATA
  • 依托单位:
Cell Research
Cell Research
Cell Research (细胞研究)