Adaptive Workflow-Aware Orchestration for Improving Reliability in End-to-End Testing of Dynamic Web Systems

Abstract

Building reliable automated testing for modern web systems is difficult because user interfaces change frequently, rendering is often asynchronous, and test runs in CI environments experience variable performance. These factors create false failures that disappear on rerun and consume significant engineering time. While common browser-automation frameworks improve stability compared to older approaches, many suites still behave like fixed scripts that expect one exact screen sequence, making them vulnerable when optional screens, banners, or pop-ups appear. This paper introduces a workflow-aware orchestration method that represents user journeys as checkpoints with validation rules, rather than as a rigid list of steps. During execution, the runner identifies the current screen from stable semantic signals, selects safe next actions, and applies conservative recovery only when needed. Failures are organized into operational categories using standardized run artifacts to support faster triage and controlled rerun policies. In addition, the paper provides a practical overview of freely available testing platforms across multiple layers of a quality pipeline, illustrating how teams can reduce dependence on fragile UI workflows by shifting many checks to lower-cost layers. A step-by-step case study of a typical enterprise journey (sign-in, dashboard navigation, multi-page data entry, review, and confirmation) demonstrates how the approach manages an intermittent modal that appears after the first data-entry page. The runner recognizes the modal as a valid transient state, resolves it safely, re-validates checkpoint conditions, and continues to the final confirmation while maintaining traceable evidence of any recovery actions. The discussion highlights improved run signal quality and reduced diagnostic effort under CI variability.