Code Quality Tracking

Code quality affects velocity, bugs, and team morale. Good quality tracking identifies trends and improvement areas. Bad tracking becomes bureaucratic overhead that teams ignore. This guide covers practical code quality measurement.

Quality Metrics

Key Metrics

What to Track

CODE QUALITY METRICS
════════════════════

TEST COVERAGE:
─────────────────────────────────────
What to track:
├── Line coverage (basic)
├── Branch coverage (better)
├── Coverage on new code (best)
├── Coverage trend over time
└── Direction matters

Good approach:
├── New code must maintain coverage
├── Track trend, not absolute
├── Identify untested critical paths
├── Quality of tests matters too
└── Meaningful coverage

BUG METRICS:
─────────────────────────────────────
├── Bugs found in production
├── Bug density (bugs per KLOC)
├── Time to fix
├── Escaped defect rate
├── Trend over time
└── Quality indicator

CODE COMPLEXITY:
─────────────────────────────────────
├── Cyclomatic complexity
├── Cognitive complexity
├── File/function length
├── Dependency count
├── Hot spots (complex + changed often)
└── Maintainability

CODE REVIEW:
─────────────────────────────────────
├── Time to first review
├── Time to merge
├── Review comments trend
├── Review thoroughness
├── Process health
└── Collaboration measure

Quality Gates

Automated Checks

QUALITY GATES
═════════════

CI PIPELINE GATES:
─────────────────────────────────────
Stage 1: Build
├── Compiles
├── Linting passes
├── Format check
└── Basic health

Stage 2: Tests
├── Unit tests pass
├── Integration tests pass
├── Coverage not decreased
└── Functional quality

Stage 3: Analysis
├── Security scan
├── Dependency check
├── Complexity check
├── Static analysis
└── Deep quality

EXAMPLE PIPELINE:
─────────────────────────────────────
build → lint → test → coverage → security → deploy
  │       │      │        │          │
  ▼       ▼      ▼        ▼          ▼
 Must    Must   Must     Check     Check
 pass    pass   pass     trend     alerts

QUALITY GATES CONFIG:
─────────────────────────────────────
# Example quality rules
coverage:
  new_code_coverage: >= 80%
  coverage_change: >= 0%  # No decrease

complexity:
  max_function_complexity: 15
  max_file_length: 400

security:
  high_severity: block
  medium_severity: warn

Tracking in GitScrum

Integrating Quality

GITSCRUM QUALITY TRACKING
═════════════════════════

TASK LABELS:
─────────────────────────────────────
├── bug: Defects found
├── tech-debt: Quality work
├── refactor: Code improvement
├── test: Test addition
└── Categorize quality work

DEFINITION OF DONE:
─────────────────────────────────────
Include quality:
├── ☐ Tests written
├── ☐ Code reviewed
├── ☐ No new warnings
├── ☐ Documentation updated
├── Quality baked in
└── Not afterthought

BUG TRACKING:
─────────────────────────────────────
├── Log all bugs
├── Track source (dev, QA, prod)
├── Severity labels
├── Time to fix
├── Trend analysis
└── Quality visibility

QUALITY REPORTS:
─────────────────────────────────────
Sprint report includes:
├── Bugs created vs fixed
├── Tech debt addressed
├── Test additions
├── Quality trend
└── Regular review

Improvement Process

Getting Better

QUALITY IMPROVEMENT
═══════════════════

IDENTIFY HOTSPOTS:
─────────────────────────────────────
Focus effort:
├── Complex + frequently changed
├── High bug density areas
├── Untested critical paths
├── Developer pain points
├── Data-driven focus
└── Biggest impact

ALLOCATE TIME:
─────────────────────────────────────
Regular investment:
├── 10-20% for quality work
├── Each sprint, some improvement
├── Part of feature work
├── Not a separate phase
├── Continuous investment
└── Sustainable approach

MEASURE IMPROVEMENT:
─────────────────────────────────────
Track over time:
├── Coverage trending up?
├── Bug density trending down?
├── Complexity stable?
├── Team velocity stable/up?
├── Quality enabling speed?
└── Progress visible

CELEBRATE WINS:
─────────────────────────────────────
├── Note quality improvements
├── Share in retros
├── Recognize effort
├── Build momentum
└── Positive reinforcement

Best Practices

For Quality Tracking

1. Trends over absolutes — Direction matters
2. Automate gates — Quality in CI
3. Part of definition of done — Baked in
4. Regular investment — Each sprint
5. Focus on hotspots — Biggest impact

Anti-Patterns

QUALITY TRACKING MISTAKES:
✗ Hard coverage numbers
✗ Quality as separate phase
✗ Metrics without action
✗ Gaming metrics
✗ Ignoring trends
✗ No automation
✗ Blame on quality issues
✗ Quality vs speed false choice

Related Solutions

• Continuous integration best practices
• Test automation strategies
• Managing technical debt during rapid development