Web application failure detection relies mostly on the tester’s creativity, leaving test automation to only ease executing repetitive tasks. Existing automated testing techniques opt for test path diversity or input generation but not the tester’s behavioral patterns. For example, testing deeply nested business logic, proper form submission, or non-redundant navigation are not considered. This paper proposes eBAT, an automated testing approach that considers those testers Einteraction patterns from observation. A behavior-driven action selection strategy is derived from these patterns to interact with the system. Actionable elements (buttons, links, inputs, etc.) obtained through state abstraction and interaction pattern-wise grouping are operated in a tree-based manner. The effectiveness and efficiency of eBAT are evaluated as the unique number of failures detected and the detection rate respectively. Results compared against the state-of-the-art indicate significant improvement in failure detection with similar code coverage. Moreover, eBAT outperforms the baseline failure detection rate in 5 out of 6 benchmark projects.