The Computational Singular Perturbation (CSP) technique is applied as an automated diagnostic tool to classify various ignition regimes encountered in auto-ignition processes in HCCI combustion. Various model problems representing HCCI combustion are simulated using high-fidelity computation with detailed chemistry for hydrogen-air system. The simulation data are then analyzed by CSP. In spatially homogeneous systems ignition, the occurrence of two branches of positive eigenvalues characterizes chain-branching and thermal ignition. Their merging point serves as a good indicator of the completion of the explosive stage of ignition. In spatially non homogeneous systems, this merging point can also be used to differentiate front propagation from homogeneously igniting kernels. Furthermore, to classify the front propagation as deflagration or spontaneous ignition, first the reaction zone is identified as the locus of minimum number of fast exhausted time scales (based on user-specified error thresholds). Next, the relative importance of transport and chemistry is determined in the region ahead of the reaction zone. Importance index I (Quantitative) and characteristic Damköhler number (Qualitative) are employed as criteria to discriminate the spontaneous ignition front from the deflagration front. These diagnostic tools applied to 1D laminar and 2D turbulent ignition problems allow automated detection of different ignition regimes at different times and location during the ignition events. The implication of the results in the context of modeling auto-ignition of nearly homogeneous turbulent mixtures is discussed.