Overview | |
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Definition (Hover Text) | It shows the number of defects reopened in a given period against the total number of defects closed. The average reopened time to reopen is also available for all the reopened defects. | |
Source Tools | Jira | |
Graph type | Single Stats Reopened defects/ Total closed defects (fraction) Reopen Rate (in percentage) Average Time to Reopen (in hrs)
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Filters | Priority | |
Fields on Explore | Issue ID Issue Description Issue Status Priority Closed Date Reopen Rate Time taken to reopen
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Business Logic | |
Calculation Formula | All defects created in the last 12 months are considered in the calculation | |
Trend | NA | |
Maturity Levels | NA | |
Instance level thresholds | NA | |
Configurations | |
Processor Fields | NA | |
Mandatory fields | Status to identify Closed defects | |
How to Validate KPI | |
Suggested ways of working | you can use JQL to find issues where the status transitioned from a closed or resolved state back to an active state. | |
Sample JQLs | Project in ("<jira project name>") and issuetype in (Defect) and status CHANGED FROM closed TO open | |
Benefits of KPI | |
How does the KPI help | Improves Code Quality: Tracking the defect reopen rate highlights recurring issues, enabling teams to focus on improving the initial fix quality and reducing the number of rework cycles. Identifies Process Gaps: It helps identify testing, requirements, or communication weaknesses that may lead to incomplete fixes or misunderstandings during development. Enhances Team Accountability: Monitoring reopen rates fosters accountability among team members by making the quality of resolutions visible and encouraging more thorough reviews and testing. Optimizes Resource Allocation: By reducing reopened defects, teams can save time and resources, allowing them to focus on new features and enhancements rather than rework.
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