Software Engineering Metrics
A comprehensive collection of metrics for team health, developer experience, delivery, and more.
Published: January 2025
Project Management
These metrics are for measuring and improving software engineering practices across multiple dimensions including team health, developer experience, delivery efficiency, productivity, code quality, and accessibility.
Measuring and analyzing your team's core performance indicators can help teams and organizations understand their current state, identify areas for improvement, and track progress over time.
Team Health & Collaboration
| Name | Description | Abbr. | Common Usage | Ideal Target | Interpretation | Calculation | Visualization | How to Capture |
|---|---|---|---|---|---|---|---|---|
| Autonomy Score | Assesses the level of autonomy team members feel they have. | Evaluate empowerment and decision-making | ≥ 85% | Higher = more empowered team | Average score from autonomy survey questions | Radar chart | Conduct regular autonomy surveys | |
| Communication Effectiveness | Evaluates the clarity and frequency of communication within the team. | Identify communication strengths and gaps | ≥ 90% | Higher = more effective communication | Percentage of team members satisfied with communication | Bar chart | Use team communication satisfaction surveys | |
| Conflict Resolution Rate | Tracks the percentage of conflicts resolved within a specified timeframe. | Monitor conflict management efficiency | ≥ 95% | Higher = effective conflict resolution | (Resolved Conflicts / Total Conflicts) × 100 | Line chart | Track conflict resolution metrics | |
| Learning and Development Opportunities | Evaluates the availability and uptake of growth opportunities. | Monitor professional development support | ≥ 90% | Higher = better support for growth | Percentage of team members satisfied with learning opportunities | Bar chart | Survey team on learning opportunities | |
| Psychological Safety Index | Assesses the extent to which team members feel safe to take risks and be vulnerable. | PSI | Evaluate openness and trust within the team | ≥ 80% | Higher = safer and more open environment | Percentage of positive responses to safety-related survey items | Bar chart | Use psychological safety assessments |
| Recognition Frequency | Tracks how often team members recognize each other's contributions. | Foster a culture of appreciation | ≥ 2 per week | Higher = more appreciative culture | Average number of recognitions per team member per week | Line chart | Monitor peer recognition tools | |
| Team Morale Score | Measures the overall enthusiasm and persistence of team members. | Assess team engagement and resilience | ≥ 4.0 (on 1–5 scale) | Higher = more engaged and resilient team | Average score from morale survey questions | Line chart over time | Conduct regular morale surveys | |
| Trust Level | Measures the degree of trust among team members. | Monitor interpersonal relationships | ≥ 85% | Higher = stronger team cohesion | Average score from trust survey questions | Radar chart | Use trust assessment surveys | |
| Work-Life Balance Satisfaction | Assesses team members' satisfaction with their work-life balance. | Evaluate potential burnout risks | ≥ 80% | Higher = better balance and well-being | Average score from work-life balance survey questions | Gauge chart | Survey work-life balance satisfaction |
Developer Experience
| Name | Description | Abbr. | Common Usage | Ideal Target | Interpretation | Calculation | Visualization | How to Capture |
|---|---|---|---|---|---|---|---|---|
| Collaboration Effectiveness | Evaluates the quality of collaboration among team members. | Monitor team dynamics | ≥ 90% | Higher = better collaboration | Average score from collaboration surveys | Radar chart | Conduct collaboration effectiveness surveys | |
| Context Switching Frequency | Measures how often developers switch between tasks or projects. | Identify multitasking impact | < 3 per day | Lower = more focused work | Average number of context switches per day | Line chart | Use time-tracking tools | |
| Developer Satisfaction Score | Measures overall satisfaction of developers with their tools and processes. | DSS | Assess developer happiness | ≥ 80% | Higher = more satisfied developers | Average score from regular surveys | Gauge chart | Conduct developer satisfaction surveys |
| Interruptions per Day | Counts the average number of work interruptions per day. | Assess focus time | < 5 | Lower = better focus | Average number of interruptions reported | Bar chart | Use interruption tracking tools | |
| Meeting Load | Tracks the amount of time developers spend in meetings. | Balance focus time and meetings | < 10% of work hours | Lower = more focus time | (Meeting hours / Total work hours) × 100 | Line chart | Analyze calendar data | |
| Onboarding Time | Time taken for new developers to become productive. | Evaluate onboarding efficiency | < 2 weeks | Lower = faster onboarding | Time from start date to first meaningful contribution | Line chart | Monitor onboarding progress | |
| Time to First Pull Request | Time from onboarding to first pull request submission. | TTFPR | Monitor initial engagement | < 1 week | Lower = quicker engagement | Time from start date to first PR | Bar chart | Track pull request submissions |
| Tooling Satisfaction | Measures satisfaction with development tools and environments. | Identify tooling issues | ≥ 85% | Higher = better tooling experience | Average score from tooling surveys | Gauge chart | Conduct tooling satisfaction surveys | |
| Workflow Friction Score | Assesses perceived obstacles in the development workflow. | Detect process bottlenecks | < 20% | Lower = smoother workflows | Percentage of developers reporting friction | Bar chart | Use workflow assessment surveys |
Agile & Delivery
| Name | Description | Abbr. | Common Usage | Ideal Target | Interpretation | Calculation | Visualization | How to Capture |
|---|---|---|---|---|---|---|---|---|
| Average Developer SP Completed | Measures individual developer productivity. | Track developer throughput | Team-specific | Throughput per developer | Completed SP / # of Developers | Bar chart per developer | Use project management tools to track story points per developer | |
| Average Story Point Size | Average size of user stories in story points. | Monitor story sizing consistency | 2–5 points | Larger = possibly undersplit work | Total SP / # of Stories | Pie chart | Analyze story point assignments in backlog | |
| Cycle Time per Story Point | Average time to complete one story point. | CTSP | Measure development efficiency | 0.5–1.5 days | Lower = higher productivity | Total Cycle Time / Completed SP | Scatter plot | Track time from start to completion per story point |
| Estimation Accuracy | Assesses the accuracy of story point estimations. | EA | Improve estimation processes | 85–115% | 100% = perfect estimation | (Estimated SP / Actual SP) × 100 | Histogram | Compare estimated vs. actual story points |
| Estimation Variance | Measures the variance between estimated and actual story points. | EV | Analyze estimation consistency | ±10–15% | Closer to 0% = better estimation | ((Actual - Estimated) / Estimated) × 100 | Box plot | Calculate variance in estimation data |
| Predictability Index | Measures how well the team meets its sprint commitments. | PI | Forecast sprint delivery accuracy | 90–100% | Higher = more accurate forecasting | (Completed SP / Committed SP) × 100 | Gauge chart | Monitor sprint commitments vs. completions |
| Productivity Loss (Unplanned) | Quantifies productivity loss due to unplanned work. | Evaluate impact of unplanned tasks | < 10% | Higher = more productivity lost | (UWR²) / 100 | Line chart | Analyze unplanned work ratio | |
| Sprint Spillover Rate | Measures the percentage of work not completed in the sprint. | Identify scope creep in sprints | < 10% | Lower = better sprint completion | (Spillover SP / Total SP Committed) × 100 | Area chart | Track incomplete work per sprint | |
| Story Points Completed vs Committed | Compares completed work to what was committed in the sprint. | Evaluate delivery reliability | 90–100% | How much was actually delivered | (Completed SP / Committed SP) × 100 | Line chart | Compare committed vs. completed story points | |
| Total Cycle Time | Total time from work start to deployment. | TCT | Measure end-to-end development duration | Varies by team | Shorter = faster delivery | Deployment Time – First Commit Time | Line chart | Track time from development start to deployment |
| Unplanned Work Ratio | Proportion of unplanned work in a sprint. | UWR | Assess sprint planning effectiveness | < 20% | Lower = better sprint planning | (Unplanned SP / Total SP Completed) × 100 | Bar chart over sprints | Monitor unplanned work in sprint retrospectives |
Productivity
| Name | Description | Abbr. | Common Usage | Ideal Target | Interpretation | Calculation | Visualization | How to Capture |
|---|---|---|---|---|---|---|---|---|
| Change Failure Rate | Percentage of deployments causing failures in production. | Monitor deployment quality | < 15% | Lower = more stable releases | (Failed deployments / Total deployments) × 100 | Bar chart | Use deployment tracking tools | |
| Cycle Time | Time from work start to completion. | Monitor development process efficiency | Varies | Lower = faster delivery | Time between work start and completion | Line chart | Track task durations in project management tools | |
| Deployment Frequency | Measures how often code is deployed to production. | Assess delivery speed | Multiple times per day | Higher = faster delivery | Number of deployments per day/week | Line chart | Monitor deployment logs | |
| Flow Efficiency | Ratio of active work time to total elapsed time. | Evaluate process efficiency | ≥ 40% | Higher = more efficient workflow | (Active time / Total time) × 100 | Line chart | Analyze time tracking data | |
| Lead Time for Changes | Time from code commit to deployment in production. | Evaluate development efficiency | < 1 day | Lower = quicker delivery | Time between commit and production deployment | Line chart | Track commit and deployment timestamps | |
| Mean Time to Recovery | Average time to restore service after a failure. | MTTR | Assess incident response efficiency | < 1 hour | Lower = faster recovery | Total downtime / Number of incidents | Line chart | Monitor incident resolution times |
| Pull Request Review Time | Average time taken to review and merge pull requests. | Assess code review efficiency | < 24 hours | Lower = quicker reviews | Total review time / Number of PRs | Line chart | Track pull request timestamps | |
| Rework Rate | Percentage of code rewritten or deleted shortly after creation. | Identify code stability issues | < 30% | Lower = more stable code | (Rewritten code / Total code) × 100 | Bar chart | Analyze version control history | |
| Work in Progress (WIP) | Number of tasks currently in progress. | Monitor workload and capacity | Varies | Lower = better focus | Count of tasks in progress | Bar chart | Use project management tools |
Code Quality & Maintainability
| Name | Description | Abbr. | Common Usage | Ideal Target | Interpretation | Calculation | Visualization | How to Capture |
|---|---|---|---|---|---|---|---|---|
| Code Churn | Tracks the frequency of code changes over time. | Monitor code stability | Lower is better | Lower = more stable code | Lines of code added, modified, or deleted over a period | Line chart | Analyze version control history (e.g., Git) for code change frequency. | |
| Code Duplication | Percentage of code that is duplicated across the codebase. | Identify redundancy | < 5% | Lower = less redundancy | (Duplicated lines / Total lines) × 100 | Pie chart | Use static analysis tools (e.g., SonarQube) to detect duplicate code segments. | |
| Code Health Score | Aggregated score representing the overall health of the codebase. | Monitor code quality | ≥ 8/10 | Higher = better code health | Composite metric from tools like CodeScene | Gauge chart | Utilize tools like CodeScene to assess code health based on various factors. | |
| Code Smells | Instances of patterns in the code that may indicate deeper problems. | Detect potential issues | Fewer is better | Lower = cleaner code | Count of code smell instances identified | Bar chart | Employ static code analysis tools to identify code smells. | |
| Comment Density | Ratio of comment lines to total lines of code. | Assess code documentation | ≥ 20% | Higher = better documentation | (Comment lines / Total lines) × 100 | Bar chart | Analyze codebase to calculate the ratio of comment lines to total lines. | |
| Cyclomatic Complexity | Measures the number of linearly independent paths through the code. | CC | Evaluate code complexity | ≤ 10 | Lower = simpler code | Count of decision points plus one | Bar chart | Use static analysis tools to calculate cyclomatic complexity. |
| Halstead Metrics | Measures various aspects of code complexity based on operators and operands. | Analyze code complexity | Varies | Lower = simpler code | Calculated using Halstead's formulas | Line chart | Utilize tools that compute Halstead metrics based on code analysis. | |
| Maintainability Index | Quantifies how maintainable the codebase is, considering complexity, size, and documentation. | MI | Assess code maintainability | ≥ 85 | Higher = easier to maintain | Composite score based on Halstead Volume, Cyclomatic Complexity, and Lines of Code | Gauge chart | Use static analysis tools to compute the maintainability index. |
| Technical Debt Ratio | Ratio of the cost to fix issues to the cost to develop the software. | Evaluate codebase health | < 5% | Lower = healthier codebase | (Remediation cost / Development cost) × 100 | Gauge chart | Estimate remediation and development costs using project management tools. | |
| Test Coverage | Percentage of codebase covered by automated tests. | Evaluate test comprehensiveness | ≥ 80% | Higher = better test coverage | (Tested code lines / Total code lines) × 100 | Pie chart | Use testing tools to measure the extent of code covered by tests. | |
| Time to Modification | Average time between code creation and its first modification. | TTM | Assess code stability | Longer is better | Longer = more stable code | Time between code commit and first modification | Line chart | Analyze version control history to determine modification timelines. |
Frontend Accessibility
| Name | Description | Abbr. | Common Usage | Ideal Target | Interpretation | Calculation | Visualization | How to Capture |
|---|---|---|---|---|---|---|---|---|
| Accessibility Issue Resolution Time | Average time to fix identified accessibility issues. | Monitor responsiveness to accessibility problems | < 5 days | Lower = quicker issue resolution | Total resolution time / Number of issues | Line chart | Track issue resolution times using issue tracking systems. | |
| Accessibility Score | Quantitative measure of a product's accessibility compliance. | Assess overall accessibility status | ≥ 90% | Higher = better accessibility | Based on automated and manual testing results | Gauge chart | Use accessibility evaluation tools to compute compliance scores. | |
| Alt Text Coverage | Percentage of images with descriptive alt text. | Provide context for non-visual users | 100% | Higher = fully described visuals | (Images with alt text / Total images) × 100 | Pie chart | Analyze image elements to ensure presence of alt attributes. | |
| Captioning Coverage | Percentage of multimedia content with captions. | Support users with hearing impairments | 100% | Higher = fully accessible media | (Captioned media / Total media) × 100 | Bar chart | Review multimedia content for caption availability. | |
| Color Contrast Ratio | Measures text and background color contrast. | Ensure readability for users with visual impairments | ≥ 4.5:1 | Higher = better readability | Contrast ratio calculations per WCAG standards | Bar chart | Use color contrast analysis tools to verify compliance. | |
| Error Density | Number of accessibility errors per page or component. | Identify areas needing improvement | < 5 errors/page | Lower = fewer accessibility issues | Total errors / Number of pages | Heatmap | Utilize accessibility testing tools to detect and count errors. | |
| Keyboard Navigation Score | Effectiveness of navigating the interface using a keyboard. | Ensure operability without a mouse | ≥ 95% | Higher = better keyboard accessibility | Percentage of interface navigable via keyboard | Line chart | Test interface for keyboard navigability and record results. | |
| Screen Reader Compatibility | Degree to which content is accessible using screen readers. | Support users relying on assistive technologies | ≥ 90% | Higher = better screen reader support | Based on testing with various screen readers | Bar chart | Conduct tests using different screen readers to assess compatibility. | |
| WCAG Compliance Level | Degree to which content meets WCAG standards (A, AA, AAA). | Monitor adherence to accessibility guidelines | AA or AAA | Higher = more comprehensive compliance | Evaluation against WCAG criteria | Bar chart | Perform audits using WCAG evaluation tools to determine compliance level. |