How do you set coding standards and code reviews for web teams?

Long Answer

Scaling a multi-developer web team requires consistency without slowing delivery. My approach is to codify “how we build” once, automate it everywhere, and iterate with data. The pillars are a shared playbook, automated enforcement, deliberate code reviews, and continuous learning.

1) Write a pragmatic engineering playbook

Document the happy path. The playbook includes: naming and folder conventions, style guides (Prettier, ESLint, TypeScript rules), API patterns (REST/GraphQL standards, error models), environment and secrets handling, logging formats, accessibility expectations, and testing strategy (unit, integration, end-to-end). Keep it short, example-first, and versioned in the repo. Add Architecture Decision Records (ADRs) for non-obvious trade-offs so newcomers understand “why,” not just “what.”

2) Automate quality gates to shift left

Humans should review design and risk—tools catch the rest. I wire pre-commit hooks (lint, type check, tests), pre-push CI (build, unit tests, coverage floor, bundle size guardrails), and branch protection (required checks, required reviews). Formatters run auto-fix; linters block on unsafe patterns. Dependency scanning (SCA), basic SAST, and license checks run in CI. For web perf, we add a Lighthouse budget to fail PRs that exceed size or performance thresholds.

3) Define a clear code review rubric

Ambiguity creates friction. Reviewers follow a shared rubric:

• Correctness & tests: logic, edge cases, tests match behavior.
  
• Security & privacy: input validation, authz checks, secrets, PII handling.
  
• Performance: query and render costs, caching, bundle impact.
  
• Accessibility & UX: semantic HTML, ARIA, keyboard nav, color contrast.
  
• Maintainability: readability, smaller diffs, self-documenting names, ADR references.
  
• Consistency: standards, design system usage, error conventions.
  We use checklists in PR templates so authors validate items before requesting review.
  

4) Keep PRs small and reviewable

We optimize for flow efficiency. Aim for PRs under a few hundred lines, single-purpose, with screenshots, test plans, and migration notes. For wide changes (renames, formatting), isolate them in separate PRs to preserve signal. Use draft PRs early to get architectural feedback. For risky changes, prefer pairing/mobbing and design spikes.

5) Ownership and reviewers

Code ownership files map directories to teams; at least one owner approves changes. We rotate reviewer pairs to spread knowledge and reduce silos. For critical paths (auth, payments), we require a security champion sign-off. The author proposes reviewers in the PR, but the ownership map is the source of truth.

6) Execution SLA and etiquette

Set expectations: acknowledge within work hours, first response < 4 business hours, approval/changes requested within one day for normal PRs. Etiquette: be kind, be specific, and suggest fixes (“consider extracting this to a hook”). Avoid subjective style nits that tools can enforce. Disagree and commit after a decision is recorded in an ADR or ticket.

7) Testing posture and coverage

We require types-first development (TypeScript), unit tests for pure logic, component tests for UI states, and a fast E2E smoke for flows. We track coverage thresholds for critical modules rather than global vanity numbers. Snapshots are purposeful and limited. For accessibility, we include automated checks and manual keyboard passes in the PR checklist.

8) CI/CD integration and branch strategy

Trunk-based development with short-lived branches reduces merge pain. Feature flags decouple deploy from release; preview environments attach to PRs for reviewers and PMs to verify UX. CI enforces all gates; CD promotes after green builds and smoke tests. For monorepos, we run affected-only pipelines to keep feedback fast.

9) Metrics and continuous improvement

We monitor DORA metrics (deployment frequency, lead time, change failure rate, MTTR) plus review time, PR size, and rework percentage. Every retro reviews these numbers and a quality dashboard (lint debt, flaky tests, perf budget drift). When a metric drifts, we adjust policies—raise the coverage bar, split modules, speed up CI hot paths.

10) Learning loop and onboarding

New joiners complete a guided onboarding path: fork the repo, pass all hooks, ship a small change, write an ADR, and complete one review. We record good PR examples and maintain a review handbook with dos/don’ts and code snippets. Regular brown bags share lessons from incidents and pattern libraries.

11) Exceptions and judgment

Standards are guardrails, not handcuffs. For urgent fixes, we allow a time-boxed bypass with a follow-up PR (tests, docs). For experiments, we use flags and sandboxes that never block main. The rule is simple: if you diverge, document why and for how long.

By codifying standards, automating enforcement, and focusing human review on design, risk, and maintainability, a multi-developer web team stays fast without sacrificing code quality. The process scales with headcount and reduces variance, while the learning loop ensures practices evolve with the product.

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Table

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Common Mistakes

• Writing a 50-page standard that nobody reads or updates.
  
• Relying on reviewers for styling and easy lint issues instead of automating.
  
• Allowing jumbo PRs that mix refactors, features, and formatting.
  
• No ownership mapping; reviews bounce or stall.
  
• Treating code review as gatekeeping rather than collaborative improvement.
  
• Chasing global coverage %, ignoring critical paths and flaky tests.
  
• Lacking performance or accessibility checks; regressions slip in.
  
• No metrics; process debates become opinion wars rather than data-driven.
  
  

Sample Answers

Junior:
“I follow the team playbook, run linters and tests locally, and open small PRs with screenshots and a test plan. I use the PR checklist and respond quickly to feedback.”

Mid:
“I help maintain the ESLint/Prettier/TypeScript config and CODEOWNERS. I keep PRs small, add component tests, and use preview environments for reviewers. I give specific, actionable feedback and link to our standards.”

Senior:
“I co-own the engineering playbook and ADRs, implement branch protection and CI quality gates, and define the review rubric. I monitor DORA and review-time metrics, run retros on drift, and pair on risky changes. I ensure security, performance, and accessibility are first-class in reviews.”

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Evaluation Criteria

Strong answers describe a written playbook, automated quality gates, a review rubric, and small PR practice. They include CODEOWNERS, branch protection, preview environments, and data (DORA, review time) to improve. They call out security, performance, and accessibility as explicit review lanes, and use ADRs for decisions. Red flags: hand-wavy “we do reviews,” no automation, mega PRs, standards only in people’s heads, or measuring success purely by velocity without quality signals.

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Preparation Tips

• Create a minimal playbook with examples; add an ADR template.
  
• Configure Prettier/ESLint/TypeScript and pre-commit hooks; fail CI on violations.
  
• Write a PR template with a checklist (tests, a11y, perf, security).
  
• Add CODEOWNERS and branch protection; require green CI and at least one owner approval.
  
• Set up preview environments for PRs.
  
• Define a review rubric and share “good PR” examples.
  
• Instrument metrics (DORA, review time, PR size) and review them at retro.
  
• Pilot on one squad, gather feedback, then roll out org-wide.
  
  

Real-world Context

A marketplace team cut lead time 35% by enforcing small PRs, CODEOWNERS, and preview envs; review time dropped from days to hours. A fintech added SAST/SCA and a security checklist to PRs; vulnerabilities declined and fixes happened earlier. A media company introduced ADRs and a review rubric that included accessibility; bug regressions fell and a11y issues were caught pre-release. Across teams, the common thread was automation for basics and human focus on design, risk, and user impact.

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Key Takeaways

• Write a concise engineering playbook with examples and ADRs.
  
• Automate quality gates; keep PRs small and single-purpose.
  
• Use a review rubric covering correctness, security, performance, and accessibility.
  
• Map ownership with CODEOWNERS and protect branches.
  
• Measure with DORA and review-time metrics; iterate in retros.
  
  

Practice Exercise

Scenario:
You are the new Technical Lead (Web Development) for a team of eight. Reviews are slow, PRs are huge, and regressions reach production.

Tasks:

1. Draft a one-page playbook: style, folder structure, API patterns, testing levels, and ADR usage.
   
2. Add Prettier/ESLint/TypeScript, pre-commit hooks, and CI checks (build, tests, coverage floor, Lighthouse budget).
   
3. Create CODEOWNERS and branch protection requiring green CI and one owner approval.
   
4. Write a PR template with checklist (security, a11y, perf, test plan, screenshots).
   
5. Pilot “small PR” policy and preview environments; set an SLA for review response and approval.
   
6. Establish a review rubric and hold a workshop to align examples of “good feedback.”
   
7. Instrument DORA + review-time dashboards; set targets and discuss at retro.
   
8. Capture two ADRs for recent architectural choices; link them in related PRs.
   
   

Deliverable:
A working governance and automation setup that produces smaller PRs, faster reviews, fewer regressions, and clear accountability—demonstrating a scalable coding standards and code review process for a multi-developer web team.