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Bug Age

What is this metric?

The amount of time it takes a bug to fix.

Why is it important?

  1. Help the team to establish an effective hierarchical response mechanism for bugs. Focus on the resolution of important problems in the backlog.
  2. Improve team's and individual's bug fixing efficiency. Identify good/to-be-improved practices that affect bug age age

Which dashboard(s) does it exist in

How is it calculated?

Similar to requirement lead time, this metric equals resolution_date - created_date of issues in type "BUG".

Data Sources Required

This metric relies on issues collected from Jira, GitHub, or TAPD.

Data Transformation Required

This metric relies on the 'type-bug' configuration in Jira, GitHub or TAPD's transformation rules while adding/editing a blueprint. This configuration tells DevLake what issues are bugs.

SQL Queries

The following SQL shows how to find the bug age of a specific bug.

-- lead_time_minutes is a pre-calculated field whose value equals 'resolution_date - created_date'
lead_time_minutes/1440 as bug_age_in_days
type = 'BUG'

If you want to measure the mean bug age in the screenshot below, please run the following SQL in Grafana.

with _bugs as(
DATE_ADD(date(i.resolution_date), INTERVAL -DAY(date(i.resolution_date))+1 DAY) as time,
AVG(i.lead_time_minutes/1440) as issue_lead_time
FROM issues i
join board_issues bi on = bi.issue_id
join boards b on bi.board_id =
-- $board_id is a variable defined in Grafana's dashboard settings to filter out issues by boards in ($board_id)
and i.status = "DONE"
and i.type = 'BUG'
and $__timeFilter(i.resolution_date)
-- the following condition will remove the month with incomplete data
and i.resolution_date >= DATE_ADD(DATE_ADD($__timeFrom(), INTERVAL -DAY($__timeFrom())+1 DAY), INTERVAL +1 MONTH)
group by 1

date_format(time,'%M %Y') as month,
issue_lead_time as "Mean Bug Age in Days"
FROM _bugs

How to improve?

  1. Observe the trend of bug age and locate the key reasons.
  2. Compare the age of bugs by severity levels, types (business, functional classification), affected components, etc.