Overview | |
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Applicability | Scrum-based projects |
Definition (Hover Text) | Measures the total number of defects (bugs) linked to closed user stories of a sprint. |
Source Tools | Jira, Azure Boards |
Graph type | Line chart |
Filters | <None> |
Hover Format on KPI | Sprint Name: <<Percentage Value>> Defects: <<Value>> Closed Stories: <<Value>> |
Fields on Explore Overlay |
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Business Logic | |
Calculation Formula | No. of defects tagged to all stories closed in an iteration/ Total no. of stories closed in the iteration. |
KPI Settings |
*Please note:- Global mappings and default Jira statuses of sprint reports will apply if the KPI level settings are not used. |
Trend | A downward trend is desirable |
Maturity Levels | M1: > 175% M2: 175% -125% M3: 125%-75% M4: 75-25% M5: 25%
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Instance level thresholds | Set the desired defect injection rate threshold |
Configurations | |
Processor Fields | Whenever we update the defect mapping and issue type mapping, whether we add or remove any issue type, we must run the processor. This is necessary to show the changes in the KPI. Defect Mapping : |
Mandatory fields | Project Settings
Defect Mapping :
Issue type Mapping :
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How to Validate KPI | |
Suggested ways of working |
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Sample JQLs | project in ("XYZ") and component ="ABC" and type in (Defect) and issueFunction in linkedIssuesOf("type in (Story) AND sprint in(406)") |
Best Practices | |
Automate Testing | Implement automated testing (unit, integration, and end-to-end tests) to catch defects early in the development process. |
Pair Programming | Implement pair programming to increase code quality and reduce the likelihood of defects being introduced. |
Adopt TDD/BDD | Use Test-Driven Development (TDD) or Behavior-Driven Development (BDD) methodologies to write tests before code, ensuring that functionality is well-defined and tested from the start. |
Use Static Analysis Tools | Implement static code analysis tools to automatically check code for potential defects and enforce coding standards. |
Benefits of KPI | |
Quality Measurement | It helps in measuring the quality of the code being produced and identifying areas where improvements are needed. |
Predictability | Understanding the defect injection rate can help in forecasting the amount of rework required and in planning more accurately. |
Cost Reduction | Reducing the defect injection rate can lead to lower costs associated with fixing bugs, especially those found later in the development cycle or after release. |
Process Improvement | By tracking this metric, teams can identify stages in the development process where defects are commonly introduced and take steps to improve those stages. |
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