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This invention discloses a dynamic quality analysis and optimization system method based on the ultimate computing power of a development model, belonging to the field of software engineering process measurement and quality prediction optimization technology. It addresses the difficulties in quality decision-making caused by inconsistent and untraceable multi-source process data, static defect analysis, and the unstable and easily reversed linkage prediction of productivity and defect escape rate. The method unifies the reading of project process data and standardizes, completes, and weights the data according to a data dictionary to form a unified dataset, automatically generating and versioning the stored documents. It statistically analyzes defect severity and weighted defect quantity within a rolling time window, calculating the defect density sequence and Cpk. A two-layer linkage prediction model is constructed, with gating corrections for productivity and defect escape rate. Satisfaction regression and Monte Carlo output distribution results are used for quality decision-making.