Fragment-Based Test Generation For Web Apps
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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 improves the precision and recall of the inferred models by 70 suites with test actions that have nearly 100 of the web app even if the execution environment is varied. The test oracles generated by FRAGGEN can detect 98.7 being highly tolerant to web app dynamism, making them suitable for regression testing.
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