Technical Debt Calculator

Updated 27 March 2026

Find out what your technical debt is actually costing. Input your team metrics to calculate annual cost, monthly burn, velocity impact, and 5-year projection.

Your Engineering Team

Moderate severity
100 = all deps current

Annual Cost Breakdown

$985k
Annual Cost
Total debt cost per year
$82k
Monthly Burn
Cost per calendar month
30%
Velocity Impact
Sprint capacity lost to debt
45
Bugs / Sprint
Estimated defects introduced
5-Year Projected Cost (if debt is left unaddressed)
Compound growth rate: 20%/year based on dependency freshness
$7.3M
Technical debt compounds. Unaddressed debt grows as systems become harder to change, attracting more workarounds, increasing onboarding time, and slowing all future development.
Debt Severity Assessment
Moderate
Moderate. Beginning to affect velocity. Plan dedicated debt sprints.

Calculations use industry-standard benchmarks. Actual costs vary by team, codebase, and context.

The Technical Debt Quadrant

Martin Fowler's debt quadrant categorises debt by two dimensions: whether it was deliberate or inadvertent, and whether it was reckless or prudent.

Deliberate/Reckless
'We don't have time for design'

Knowingly taking on debt without a plan to repay it. Highest long-term cost.

Deliberate/Prudent
'We'll ship now and refactor in v2'

Conscious debt taken with full awareness and a repayment plan.

Inadvertent/Reckless
'What is layered architecture?'

Debt accumulated through lack of knowledge or skill. Often the most prevalent.

Inadvertent/Prudent
'Now we know how we should have done it'

Debt discovered after the fact when better practices are learned.

Frequently Asked Questions

What counts as technical debt?

Technical debt is the accumulated cost of shortcuts, quick fixes, and deferred improvements in your codebase. It includes: code that is difficult to understand or modify, missing tests, outdated dependencies with known vulnerabilities, architectural decisions that made sense then but limit you now, and documentation gaps that slow onboarding and debugging. The defining characteristic is that it makes future changes more expensive than they would be in a clean system.

How do I estimate my debt percentage?

Debt percentage is the proportion of your engineering team's time consumed by debt-related activities: fixing bugs caused by fragile code, navigating complex legacy systems, working around architectural limitations, handling dependency conflicts, and dealing with flaky tests. Survey your team: ask engineers how many hours per week they spend on debt vs new features. Be honest. Most teams underestimate by 30-50%.

What is a realistic test coverage target?

Industry benchmarks suggest 70-80% line coverage as a healthy minimum for production applications. Below 60% coverage, defect escape rates increase substantially. Note that coverage percentage alone is a poor metric, it matters whether the right code is covered. Critical business logic and integration points should be tested regardless of aggregate coverage numbers.

How is the 5-year compound cost calculated?

The calculator models technical debt as a compound interest problem. Unaddressed debt grows because each addition to a complex codebase adds more complexity than it would in a clean system. The compound rate is modelled at 15-25% per year, with higher rates for codebases with more outdated dependencies (which generate security incidents and forced migration work). This aligns with CAST Software research on software quality economics.

What does velocity impact mean?

Velocity impact is the percentage of your team's productive capacity consumed by debt. A team with 25% debt impact delivers roughly 75% of the feature throughput they would achieve with no debt. This has compounding effects: slower velocity means competitors ship faster, engineers burn out dealing with fragile code, and the debt backlog grows as the system becomes harder to change.

What is dependency freshness and why does it matter?

Dependency freshness measures how current your third-party libraries and frameworks are. A score of 100 means all dependencies are on current major versions. A score of 30 means most dependencies are multiple major versions behind. Low freshness correlates with: known security vulnerabilities, incompatibilities with new tooling, difficult future upgrades, and higher maintenance burden. Outdated dependencies are also a primary driver of debt compound growth because deferred upgrades become progressively more expensive.