Practise vocabulary for discussing technical debt: tech debt ratio, hotspot analysis, principal vs. interest metaphor, and debt prioritisation for stakeholders.
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A tech lead says 'Our tech debt ratio is 18%.' What does this metric express?
Tech debt ratio = remediation cost ÷ development cost × 100. An 18% ratio means fixing the debt would cost 18% of what it took to build the system. SonarQube surfaces this metric.
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A senior engineer says 'That module is a hotspot — high churn and low coverage.' What does 'hotspot' mean here?
A hotspot combines high change frequency (churn) with poor quality indicators like low coverage or high complexity. Hotspot analysis (popularised by Adam Tornhill) prioritises which debt to address first.
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A product manager asks why the team is slow. The architect replies: 'We're paying interest on the debt.' What does 'interest' mean in this metaphor?
In the principal vs. interest metaphor, the principal is the original shortcuts taken, and the interest is the ongoing productivity drag — slower development, more bugs — incurred each sprint until the debt is paid down.
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During sprint planning, the team says they want to 'pay down debt' in the next sprint. What does this phrase mean?
'Paying down debt' means investing effort to refactor or improve areas of poor code quality, reducing future interest payments (i.e., removing the ongoing drag on velocity and reliability).
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A CTO presents to the board: 'We need to prioritise this debt because it sits on the critical path.' Which framing best supports this argument to non-technical stakeholders?
Stakeholder communication about debt works best when framed in business terms: delayed features, outage risk, and difficulty hiring/retaining engineers. Translating technical debt into business impact is a key skill for engineering leaders.