Automated model-based test generation presents a viable alternative to the costly manual test creation currently employed for regression testing of web apps. However, existing model inference techniques rely on threshold-based whole-page comparison to establish state equivalence, which cannot reliably identify near-duplicate web pages in modern web apps. Consequently, existing techniques produce inadequate models for dynamic web apps, and fragile test oracles, rendering the generated regression test suites ineffective. We propose a model-based test generation technique, FragGen , that eliminates the need for thresholds, by employing a novel state abstraction based on page fragmentation to establish state equivalence. FragGen also uses fine-grained page fragment analysis to diversify state exploration and generate reliable test oracles. Our evaluation shows that FragGen outperforms existing whole-page techniques by detecting more near-duplicates, inferring better web app models and generating test suites that are better suited for regression testing. On a dataset of 86,165 state-pairs, FragGen detected 123% more near-duplicates on average compared to whole-page techniques. The crawl models inferred by FragGen have 62% more precision and 70% more recall on average. FragGen also generates reliable regression test suites with test actions that have nearly 100% success rate on the same version of the web app even if the execution environment is varied. The test oracles generated by FragGen can detect 98.7% of the visible changes in web pages while being highly robust, making them suitable for regression testing.

中文翻译：

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Web 应用程序的基于片段的测试生成

基于模型的自动化测试生成为当前用于 Web 应用程序回归测试的昂贵的手动测试创建提供了一种可行的替代方案。然而，现有的模型推理技术依赖于基于阈值的整页比较来建立状态等价性，这不能可靠地识别现代网络应用程序中的近乎重复的网页。因此，现有技术为动态 Web 应用程序和脆弱的测试 oracle 生成了不充分的模型，使生成的回归测试套件无效。我们提出了一种基于模型的测试生成技术，FragGen ，通过采用基于页面碎片的新颖状态抽象来建立状态等效性，从而消除了对阈值的需求。FragGen 还使用细粒度的页面碎片分析来多样化状态探索并生成可靠的测试预言。我们的评估表明FragGen 通过检测更多近似重复、推断更好的 Web 应用程序模型和生成更适合回归测试的测试套件，优于现有的整页技术。在 86,165 个状态对的数据集上，与整页技术相比，FragGen 检测到的近似重复项平均多出 123%。推断的爬行模型FragGen 的准确率平均提高 62%，召回率平均提高 70%。FragGen 还生成可靠的回归测试套件，即使执行环境不同，测试操作在同一版本的 Web 应用程序上也具有接近 100% 的成功率。生成的测试预言机FragGen 可以检测到网页中 98.7% 的可见变化，同时具有很高的鲁棒性，使其适用于回归测试。