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Bug Closed Count

Definitions​

  • Bug: An identified defect or error in the software.
  • Bug Close: When a reported bug is fixed and verified to be resolved.
  • Bug Close Count: The number of bugs closed within a specific timeframe (e.g., weekly, monthly).
  • Average Closed Bugs per Week: The average number of bugs closed each week over a chosen period (e.g., past month, quarter, or year).

Explanation of Charts​

The Line Chart provides a combined view of bug closures within a certain date range:

  • Horizontal Axis: Represents time (e.g., weeks, months)
  • Vertical Axis: Number of bugs closed
  • Top left corner: Gives total average count of bugs for that month.

Interpretation​

  • Identifying Trends: The line chart helps visualise trends in bug resolution over time.
  • Increased Bug Close Count: May indicate improved bug identification, testing effectiveness, or faster resolution processes.
  • Decreased Bug Close Count: Could suggest fewer bugs being introduced, a backlog of unresolved bugs, or changes in bug reporting practices.
  • Identifying Bottlenecks: Analysing trends can help identify potential bottlenecks in the bug resolution workflow.

Key Points​

  • Improved Efficiency: Tracking Bug Close Count helps assess the effectiveness of your bug resolution process.
  • Proactive Bug Management: Identifying trends allows for proactive measures to address potential bug influx or slowdowns.
  • Resource Allocation: Insights from Bug Close Count data can help allocate resources for bug fixing and prevention efforts.

Conclusion​

Monitoring Bug Close Count provides valuable insights into your team's bug resolution performance. By analysing trends and identifying areas for improvement, you can optimise your bug tracking and fixing processes, leading to a more robust software product.

Descriptive Statistics​

  • Increased Average Bug Closures: This could indicate a surge in new bug introductions or a focus on resolving existing backlog.
  • Decreased Average Bug Closures: This might reflect a decline in new bugs due to improved development practices or a shift in testing priorities.