This study applies canonical correlation analysis to investigate the relationships between source-code (SC) complexity and fault-correction (FC) activity. Product and process measures collected during the development of a commercial real-time product provide the data for this analysis. Sets of variables represent SC complexity and FC activity. A canonical model represents the relationships between these sets. s-significant canonical correlations along 2 dimensions support the hypothesis that SC complexity exerted a causal influence on FC activity during the system-test phase of the real-time product. Interpretation of the s-significant canonical correlations suggests that two subsets of product measures had different relationships with process activity. One is related to design-change activity that resulted in faults, and the other is related directly to faults. Further, faults having less impact on the system-test process associated with design-change activity that occurred during the system-test phase, while those having more impact associated with SC complexity at entry to the system-test phase. The study demonstrates canonical correlation analysis as a useful exploratory tool for understanding influences that affected past development efforts. However, generalization of the canonical relationships to all software development efforts is untenable since the model does not represent many important influences on the modeled latent variables, e.g., schedule pressure, testing effort, product domain, and level of engineering expertise.