dimensional-analysis

Dimensional analysis prevents arithmetic bugs by enforcing strict unit consistency and detecting scaling errors in DeFi protocols. It traces dimensional logic through operations to ensure token and share amounts are not accidentally mismatched.

Automated dimensional analysis detects precision loss by annotating numeric variables with scaling factors and propagating these dimensions through arithmetic operations. It identifies mismatches and scaling errors during function calls to validate dimensional consistency.

Yes, you can use dimensional analysis to audit financial systems. It performs comprehensive checks on codebases involving numeric computations and unit conversions to identify unit mismatches and prevent catastrophic financial loss.

The best way to trace scaling factors is through automated annotation and propagation tracing. This systematically tags variables with dimensional units and follows the logic through function calls to detect any dimensional inconsistencies.

Yes, dimensional analysis operates without external dependencies. It orchestrates a self-contained multi-step pipeline including vocabulary discovery, anchor annotation, propagation tracing, and bug validation directly on the current repository.

You should run a dimensional analysis report before production deployment to catch precision scaling bugs. It is essential for codebases involving complex numeric computations, unit conversions, and fixed-point arithmetic like DeFi protocols.