IT-02
Bug Ratio Spike in Single Sprint
Issue Type Distribution
Default severity: medium
Product BacklogMetricsQuality
What it detects
The bug ratio in a specific sprint is significantly above the team\'s historical average — a one-sprint quality crisis. May indicate a bad release, regression after a major change, or a test phase artificially concentrated in one sprint. baseline_bug_ratio = AVG(bug_ratio, last config.it.baseline_sprints) // default: 4 sprints current_bug_ratio = bug_ratio(current_sprint)
Detection formula
IF current_bug_ratio > baseline_bug_ratio * config.it.spike_multiplier // default: 2.0x THEN FLAG bug_spike IF current_bug_ratio > config.it.critical_bug_ratio THEN CRITICAL Report: which bugs, linked to which features, opened by whomExamples in practice
- A team shows the bug ratio in a specific sprint is significantly above the team\'s historical average while spike multiplier is set to 2.0x.
- Example signal: The bug ratio in a specific sprint is significantly above the team\'s historical average — a one-sprint quality crisis.
Suggested response
Rebalance issue-type mix and debt trends so quality signals stay intentional.
Coaching playbook
Symptom
The bug ratio in a specific sprint is significantly above the team\'s historical average — a one-sprint quality crisis. May indicate a bad release, regression after a major change, or a test phase artificially concentrated in one sprint. baseline_bug_ratio = AVG(bug_ratio, last config.it.baseline_sprints) // default: 4 sprints current_bug_ratio = bug_ratio(current_sprint)
Why it matters
When "Bug Ratio Spike in Single Sprint" keeps appearing, the team is signalling a repeatable process gap. Left unexamined, the pattern hides where work really stalls and makes improvement metrics harder to trust.
What you can achieve
Rebalance issue-type mix and debt trends so quality signals stay intentional.
Facilitation questions
- What system change would stop "Bug Ratio Spike in Single Sprint" from firing again?
- What do the cited issues have in common — same root cause or same workaround?
- Who owns the two-week experiment and how will we verify on the next import?
Run this rule against your own tracker data with Flow Analyzer.