The computational singular perturbation (CSP) technique is applied as an automated diagnostic tool to classify ignition regimes encountered in homogeneous charge compression ignition (HCCI) engines. 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 a homogeneous system, the occurrence of two branches of explosive eigenvalues characterizes chain-branching and thermal ignition. Their merging point serves as a good indicator of the completion of the explosive stage of ignition. However, the merging point diagnostics is insufficient to differentiate spontaneous ignition from deflagration. As an alternate method, the active reaction zones are first identified by the locus of minimum number of fast exhausted time scales (based on user-specified error thresholds). Subsequently, the relative importance of transport and chemistry is determined in the region ahead of the reaction zone. A new index I^T, defined as the sum of the absolute values of the importance indices of diffusion and convection of temperature to the slow dynamics of temperature, serves as a criterion to differentiate spontaneous ignition from deflagration regimes. These diagnostic tools are applied to 1D and 2D ignition problems under laminar and turbulent mixture conditions, respectively, allowing 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 autoignition of nearly homogeneous turbulent mixtures is discussed.