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Excessive test mode power-ground noise in nanometer scale chips causes large delay uncertainties in scan chains, resulting in a highly elevated rate of timing failures. The hybrid timing violation types in scan chains, compounded by their possibly intermittent manifestations, invalidate the conventional assumptions in scan chain fault behavior, significantly increasing the ambiguity and difficulty in diagnosis. In this paper, we propose a novel methodology to identify the root cause of scan chain timing failures. The proposed work addresses the challenge of diagnosing multiple permanent or intermittent timing faults in scan chains and the associated clock trees, which closely approximate the realistic failure mechanisms observed in silicon. Instead of relying on fault simulation that is incapable of approximating the intermittent fault manifestation, the proposed technique characterizes the impact of timing faults by analyzing the phase movement of scan patterns. Extracting fault-sensitive statistical features of phase movement information provides strong signals for the precise identification of fault locations and types. The manifestation probability of each fault is furthermore computed through a mathematical transformation framework which accurately models the behavior of multiple faults as a Markov chain. The identification of failing scan cells enables a further examination of the possible delay defects in the scan clock buffers, which ascertains the possible root causes of the observed scan chain failures. The proposed scheme characterizes the timing impact of the defective clock buffers by extracting the change in the delay distribution of the clock paths, enabling the effective pruning of unrealistic fault hypotheses that would result in highly deviant timing behavior. Simulation results have confirmed that the proposed methodology can yield highly accurate diagnosis results for complex fault manifestations.