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Quality Engineering

The disciplines that turn code that compiles into code that survives production. Language-agnostic, applies across the languages/ tracks.

Sections

The three pillars

  • Testing — taxonomy (unit / integration / contract / E2E / property / fuzz / mutation / load / snapshot), test doubles, coverage, flakiness, fixtures, TDD/BDD.
  • Performance — measurement, profiling (CPU / memory / allocation / flame graphs), benchmarking, latency budgets, memory, concurrency overhead, regression detection.
  • Build Systems — dependency management, reproducible builds, CI build optimisation, caching, supply-chain hardening, cross-compilation.

Code-level quality signals

  • Static Analysis & Linting — linters, formatters, type-checkers, SAST; what can be proved without running the code.
  • Code Coverage — line / branch / mutation coverage; the diagnostic value vs the "coverage as KPI" trap.
  • Code Quality Metrics — cyclomatic / cognitive complexity, coupling & cohesion, churn & hotspots, duplication, maintainability index, health dashboards.
  • Code Review — the engineering side: what to look for, in what order, how to give technically useful feedback (the soft-skills / communication side lives in Soft-Skills).

Deeper verification

  • Dynamic Analysis & Sanitizers — ASan / TSan / UBSan / Valgrind, coverage-guided dynamic analysis, runtime contracts; the memory-safety and concurrency bugs you can only catch by running the code.
  • Formal Methods & Verification — formal specs, model checking, TLA+, property/contract verification, proof assistants; proving properties instead of testing for them — and when that's worth it.

Release & operational quality

  • Release Engineering — versioning (semver / calver), changelogs, RC / GA flow, artifact signing, SBOMs, rollback, deprecation policy.
  • Quality Gates — the policy layer that decides "is this change allowed to merge / deploy?"; required CI checks, branch protection, merge queues, deploy gates.
  • Documentation Quality — Diataxis, API docs, runbooks, ADRs, doc-as-code, doc testing.

Measuring & managing quality

  • Engineering Metrics & DORA — the DORA four keys, flow metrics, the SPACE framework, lead/cycle time, reliability metrics; using metrics to improve without falling into Goodhart's law.
  • Technical Debt Management — what debt actually is, the debt quadrant, measuring it, prioritising paydown, and stopping its accumulation.