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SUMMARY & CONCLUSIONSTesting of complex products is typically carried out within planned timelines and cycles to assess system-level reliability. However, despite these efforts, overall reliability targets are often not met, and there remains ambiguity around the appropriate point to end testing and how to measure its effectiveness. Ending testing too early risks overlooking critical failure modes, which can result in elevated field failure rates. Key challenges include determining when sufficient testing has been performed and whether all significant failure modes have been identified [1].This paper presents a method for defining the optimal stopping point for testing during the development phase of complex systems. It also proposes a framework for evaluating the effectiveness of system-level testing based on the discovery of failure modes or symptoms throughout various stages of product development.The proposed method shares conceptual similarities with the Crow AMSAA model [2] in terms of data collection, treating each unique failure mode as a contributor to reliability growth. By tracking each distinct failure or symptom, the method provides insights into design maturity, the effectiveness of system testing in exposing failure modes, and the duration required to uncover them. Failure modes and symptoms are categorized into five progressive phases:This categorization helps guide test teams in deciding whether continued testing is justified and whether critical failure modes have been sufficiently uncovered.Analyzing the rate at which new failure modes are discovered allows for more accurate estimation of test duration for current and future programs. Additionally, it offers a quantifiable measure of test effectiveness, supporting the optimization of test strategies and methodologies.