What is Technical Debt Ratio (TDR)?
The Technical Debt Ratio is a quantitative metric that expresses the cost of fixing all known technical debt as a percentage of the cost of rewriting the entire application from scratch.
The Technical Debt Ratio is a quantitative metric that expresses the cost of fixing all known technical debt as a percentage of the cost of rewriting the entire application from scratch. It provides a single number that summarizes the overall health of a codebase.
TDR = (Remediation Cost ÷ Development Cost) × 100
A TDR of 5% means fixing all known issues would cost 5% of what a complete rewrite would cost — healthy. A TDR of 15% is concerning. Above 20% indicates the codebase is in serious trouble and approaching what Richard Ewing calls the Technical Insolvency Date.
The TDR is calculated by static analysis tools like SonarQube, which estimate remediation time for each issue and model development cost based on codebase size. While the absolute numbers are estimates, the trend over time is highly informative.
Why It Matters
The TDR provides a single, trackable metric for board-level reporting on codebase health. Saying "our TDR is 8% and trending down" is infinitely more useful than "we have some tech debt." It enables comparisons across projects and time periods.
How to Measure
1. **Automated**: Use SonarQube or CodeClimate to calculate TDR automatically.
2. **Manual**: Estimate hours to fix all known issues ÷ estimate hours for full rewrite.
3. **Track Quarterly**: The trend matters more than the absolute number.
4. **Benchmark**: <5% excellent, 5-10% good, 10-20% concerning, >20% critical.
Frequently Asked Questions
What is a good technical debt ratio?
Below 5% is excellent. 5-10% is good. 10-20% is concerning and needs active management. Above 20% is critical and likely approaching the Technical Insolvency Date.
How do you calculate technical debt ratio?
TDR = (Remediation Cost ÷ Development Cost) × 100. Tools like SonarQube calculate this automatically based on static analysis.
Related Terms
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Richard Ewing is a Product Economist and AI Capital Auditor. He helps companies translate technical complexity into financial clarity.
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