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 |
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Mandatory fields | Project Settings
| Issue Type Mapping
WorkFlow Status Mapping Status considered for Issue closure eg; Closed, Done, Ready for Delivery
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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