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2 examples of Defect Density metrics and KPIs

What are Defect Density metrics?

Crafting the perfect Defect Density metrics can feel overwhelming, particularly when you're juggling daily responsibilities. That's why we've put together a collection of examples to spark your inspiration.

Copy these examples into your preferred app, or you can also use Tability to keep yourself accountable.

Find Defect Density metrics with AI

While we have some examples available, it's likely that you'll have specific scenarios that aren't covered here. You can use our free AI metrics generator below to generate your own strategies.

Examples of Defect Density metrics and KPIs

Metrics for Assessing software quality

  • 1. defect density

    Defect density measures the number of defects per unit of software size, usually per thousand lines of code (KLOC)

    What good looks like for this metric: 1-5 defects per KLOC

    Ideas to improve this metric
    • Improve code reviews
    • Implement automated testing
    • Enhance developer training
    • Increase test coverage
    • Use static code analysis
  • 2. code coverage

    Code coverage measures the percentage of code that is executed by automated tests

    What good looks like for this metric: 70-80%

    Ideas to improve this metric
    • Write more unit tests
    • Implement integration testing
    • Use better testing tools
    • Collaborate closely with QA team
    • Regularly refactor code for testability
  • 3. mean time to resolve (MTTR)

    MTTR measures the average time taken to resolve a defect once it has been identified

    What good looks like for this metric: Less than 8 hours

    Ideas to improve this metric
    • Streamline incident management process
    • Automate triage tasks
    • Improve defect prioritization
    • Enhance developer expertise
    • Implement rapid feedback loops
  • 4. customer-reported defects

    This metric counts the number of defects reported by end users or customers

    What good looks like for this metric: Less than 1 defect per month

    Ideas to improve this metric
    • Implement thorough user acceptance testing
    • Conduct regular beta tests
    • Enhance support and issue tracking
    • Improve customer feedback channels
    • Use user personas in development
  • 5. code churn

    Code churn measures the amount of code changes over a period of time, indicating stability and code quality

    What good looks like for this metric: 10-20%

    Ideas to improve this metric
    • Encourage smaller, iterative changes
    • Implement continuous integration
    • Use version control effectively
    • Conduct regular code reviews
    • Enhance change management processes

Metrics for Quality and Reliability

  • 1. Defect Density

    Measures the number of defects per unit size of the software, usually per thousand lines of code

    What good looks like for this metric: 1-10 defects per KLOC

    Ideas to improve this metric
    • Implement code reviews
    • Increase automated testing
    • Enhance developer training
    • Use static code analysis tools
    • Adopt Test-Driven Development (TDD)
  • 2. Mean Time to Failure (MTTF)

    Measures the average time between failures for a system or component during operation

    What good looks like for this metric: Varies widely by industry and system type, generally higher is better

    Ideas to improve this metric
    • Conduct regular maintenance routines
    • Implement rigorous testing cycles
    • Enhance monitoring and alerting systems
    • Utilise redundancy and failover mechanisms
    • Improve codebase documentation
  • 3. Customer-Reported Incidents

    Counts the number of issues or bugs reported by customers within a given period

    What good looks like for this metric: Varies depending on product and customer base, generally lower is better

    Ideas to improve this metric
    • Engage in proactive customer support
    • Release regular updates and patches
    • Conduct user feedback sessions
    • Improve user documentation
    • Monitor and analyse incident trends
  • 4. Code Coverage

    Indicates the percentage of the source code covered by automated tests

    What good looks like for this metric: 70-90% code coverage

    Ideas to improve this metric
    • Increase unit testing
    • Use automated testing tools
    • Adopt continuous integration practices
    • Refactor legacy code
    • Integrate end-to-end testing
  • 5. Release Frequency

    Measures how often new releases are deployed to production

    What good looks like for this metric: Depends on product and development cycle; frequently updated software is often more reliable

    Ideas to improve this metric
    • Adopt continuous delivery
    • Automate deployment processes
    • Improve release planning
    • Reduce deployment complexity
    • Engage in regular sprint retrospectives

Tracking your Defect Density metrics

Having a plan is one thing, sticking to it is another.

Don't fall into the set-and-forget trap. It is important to adopt a weekly check-in process to keep your strategy agile – otherwise this is nothing more than a reporting exercise.

A tool like Tability can also help you by combining AI and goal-setting to keep you on track.

Tability Insights DashboardTability's check-ins will save you hours and increase transparency

More metrics recently published

We have more examples to help you below.

Planning resources

OKRs are a great way to translate strategies into measurable goals. Here are a list of resources to help you adopt the OKR framework:

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