Best practices for using the Z Framework effectively.

• Always use mpmath with dps=50 for precision-critical calculations
• Validate numerical stability across different precision levels
• Document precision requirements for each calculation

• Use bootstrap methods with minimum 1000 samples
• Report confidence intervals: CI [lower, upper]
• Include statistical significance: p-values
• Document validation methodology

• Validate claims with independent datasets
• Cross-validate results across different N ranges
• Document reproducibility procedures

• Separate mathematical core from application logic
• Use modular design for reusable components
• Maintain clean separation between domains

• Use vectorized operations where possible
• Implement parallel processing for large datasets
• Cache expensive computations

• Validate input parameters
• Handle numerical edge cases gracefully
• Provide informative error messages

• Include mathematical derivations
• Document parameter selection rationale
• Provide complete reproduction instructions

• Test across multiple scale ranges
• Validate against known mathematical results
• Include negative controls and edge cases

• Submit critical findings for independent verification
• Document limitations and assumptions
• Include sensitivity analyses

• User Guide
• Code Standards
• Framework Documentation