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Issue Reopen Rate

Measure how effectively bugs and problems are being fixed and whether the initial fixes are truly addressing the root cause.

Track Reopen Rates Now

Monitoring the quality of your issue resolution process and the overall stability of your software

with the

Issue Reopen Rate

Measure how effectively bugs and problems are being fixed and whether the initial fixes are truly addressing the root cause.

Track Reopen Rates Now
Issue Reopen RateIssue Reopen RateIssue Reopen Rate

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“Great product with great support!

Keypup is extremely flexible in its reporting. Once you get your raw data connected, there is almost nothing it can't do. There is a wealth of tables, charts and other reports available. As Director of a software development team, I use Keypup to report on our work efficiencies to senior managment. Keypup makes this task very simple to produce each week.”

Brad B.

Director, Software Development

Benefits of the Issue Reopen Rate metric

By tracking the Issue Reopen Rate, you can identify potential problems in your development workflow and take corrective action. A consistently high rate might indicate a need for better bug reporting practices, more thorough root cause analysis, improved testing procedures, or increased communication between developers and testers.

Addressing these issues can lead to higher quality software, reduced development costs, and improved user satisfaction. It's a key indicator of whether your team is truly resolving issues or just putting bandages on them.

Key Readings of the Issue Reopen Rate metric

A low Issue Reopen Rate indicates that issues are generally being resolved correctly the first time. This suggests that developers are thoroughly investigating problems, implementing effective solutions, and adequately testing their fixes before closing the issue.

A high Issue Reopen Rate, however, is a red flag. It suggests that fixes are incomplete, incorrect, or not addressing the underlying problem, leading to the issue recurring. This can stem from rushed fixes, inadequate testing, a lack of understanding of the root cause, or even communication breakdowns between developers and testers.

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