| 引用本文: | 王博,陈冲,邓明,董震,林友芳,郝丹.移动应用GUI测试自动生成技术综述.软件学报,2025,36(6):2713-2746 |
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| 移动应用GUI测试自动生成技术综述 |
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王博1,2, 陈冲1,2, 邓明1,2, 董震3, 林友芳1,2, 郝丹4,5
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1.北京交通大学 计算机与信息技术学院, 北京 100044;2.交通数据分析与挖掘北京市重点实验室(北京交通大学), 北京 100044;3.复旦大学 计算机科学与技术学院, 上海 200438;4.北京大学 计算机学院, 北京 100871;5.高可信软件技术教育部重点实验室 (北京大学), 北京 100871
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| 摘要: |
| 移动应用是近10年来兴起的新型计算模式, 深刻地影响人民的生活方式. 移动应用主要以图形用户界面(graphical user interface, GUI)方式交互, 而对其进行人工测试需要消耗大量人力和物力. 为此, 研究者提出针对移动应用GUI的测试自动生成技术以提升测试效率并检测潜在缺陷. 收集了145篇相关论文, 系统地梳理、分析和总结现有工作. 提出了“测试生成器-测试环境”研究框架, 将该领域的研究按照所属模块进行分类. 特别地, 依据测试生成器所基于的方法, 将现有方法大致分为基于随机、基于启发式搜索、基于模型、基于机器学习和基于测试迁移这5个类别. 此外, 还从缺陷类别和测试动作等其他分类维度梳理现有方法. 收集了该领域中较有影响力的数据集和开源工具. 最后, 总结当前面临的挑战并展望未来的研究方向. |
| 关键词: 软件测试 GUI测试 测试生成 移动应用测试 安卓应用 |
| DOI：10.13328/j.cnki.jos.007313 |
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| 基金项目:国家自然科学基金(62202040) |
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| Survey on Automated GUI Test Generation Techniques of Mobile Applications |
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WANG Bo1,2, CHEN Chong1,2, DENG Ming1,2, DONG Zhen3, LIN You-Fang1,2, HAO Dan4,5
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1.School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China;2.Beijing Key Lab of Traffic Data Analysis and Mining (Beijing Jiaotong University), Beijing 100044, China;3.School of Computer Science, Fudan University, Shanghai 200438, China;4.School of Computer Science, Peking University, Beijing 100871, China;5.Key Lab of High Confidence Software Technologies (Peking University), Ministry of Education, Beijing 100871, China
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| Abstract: |
| Mobile applications, a new computing mode that has emerged in the past decade, significantly impact people’s lifestyles. Mobile applications primarily interact through graphical user interfaces (GUIs) and conducting manual testing for them requires significant manpower and material resources. In response to this, researchers propose automated GUI test generation techniques for mobile applications to enhance testing efficiency and detect potential defects. This study collects 145 relevant papers and systematically sorts out, analyzes, and summarizes existing work. This study proposes a research framework called “Test Generator-Test Environment” to categorize research in this domain based on the modules to which it belongs. Particularly, this study classifies existing methods roughly into five categories according to the methods on which the test generator is based: random-based, heuristic-search-based, model-based, machine-learning-based, and test-migration-based approaches. Furthermore, this study analyzes and discusses existing methods from other classification dimensions, such as defect categories and test action categories. Additionally, influential datasets and open-source tools in this field are compiled. Finally, this study summarizes the current challenges and provides an outlook on future research directions. |
| Key words: software testing graphical user interface (GUI) testing test generation mobile application testing Android APP |
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