Setting Up A Clean Code Checklist

As a QA Architect, I was raised on Uncle Bob's clean coding practices. But AI brings a whole new dimension to writing clean code. Here are some AI clean coding practices I’ve written for my upcoming GitHub Copilot classes. In the spirit of Uncle Bob, we’ll call these Uncle Mike’s AI Clean Code! 🔤 Descriptive naming for promptability — Use clear, meaningful names to help AI understand the function or variable’s intent. 💬 Comment as prompt — Write natural-language comments that act as prompts for AI-assisted code completion. 🧩 Standardize function signatures — Keep function patterns predictable so AI can autocomplete with more accuracy. 🪓 Modular and intent-based design — Break code into small, purpose-driven chunks to guide AI generation better. 📘 AI-readable docstrings — Include concise docstrings that clearly explain the function’s purpose and return value. ✨ Consistent formatting & indentation — Apply standard formatting so AI can easily parse and continue your code style. 🚫 Avoid abbreviations — Spell out names fully to eliminate confusion and improve AI's contextual understanding. 🗂️ Use semantic sectioning — Group related code under labeled comments to help AI follow code structure. 🔢 Avoid magic numbers and strings — Replace unexplained literals with named constants for clarity and reuse. 📥 Prompt-driven variable initialization — Name variables based on their source or purpose to guide AI suggestions. ✅ Write self-descriptive tests — Give test functions names that clearly describe expected behavior and edge cases. 🧹 Avoid code noise — Remove dead code and clutter to prevent misleading AI completions. 🏗️ Prompt-aware file structure — Organize files logically so AI tools can infer intent from directory and file names.

Hey, devs! 👋 Today, let's dive into the essentials of writing code that's not only functional but also clean and easy to maintain in JavaScript. If you've ever come back to your own code and thought, "What was I even doing here?" – this post is for you! 😆 Step 1: Keep It Simple Focus on simplicity! Avoid complex structures unless absolutely necessary. Simple code is easier to understand and maintain. Step 2: Use Descriptive Variable Names Make your variable names meaningful. For instance, instead of x or temp, try userName or totalPrice – future-you (and your teammates) will thank you! Step 3: Stick to Consistent Formatting  Consistency in code style is key. Use linters like ESLint and stick to one style guide, whether it’s Google, Airbnb, or your team’s own. Step 4: Modularize with Functions Break down your code into small, reusable functions. Each function should do one thing and do it well – no spaghetti code here! Step 5: Add Comments Sparingly but Wisely Only comment on complex logic that’s hard to understand, but avoid over-commenting. Code should be self-explanatory where possible! Step 6: Test Regularly Testing isn’t just for final stages. Write and run tests as you go to ensure each piece works before moving on. Tools like Jest make this easy in JavaScript! Step 7: Refactor Often Regularly revisit and refactor your code. Small improvements over time lead to cleaner, more efficient codebases in the long run! Writing clean code takes practice, but it’s so worth it for your growth as a developer. Start small, and soon it’ll be second nature! P.S. What’s your top tip for writing clean JavaScript? Let’s share and learn together in the comments! #softwareengineer

"Anyone can write code. But writing code that doesn’t make your future self cry? That’s where the real devs stand out." Here are 7 techniques to write clean, professional code that you’ll be proud of:  --- 1. Stop Using Stupid Names   Bad names are code crimes. Period.   - Variables like `temp`, `data`, or `x` tell you nothing.   - Functions like `doStuff()` belong in the trash.  ✅ Use names that explain what something does or holds.   Good: `calculateFinalInvoice()`   Bad: `doCalc()`  --- 2. Kill the Nested Hell   Nested `if` statements 4 levels deep? That’s a bug in itself.   - Use early returns to flatten your code logic.   - Guard clauses make your code clean, readable, and maintainable.  ✅ Clean Example:   ```python   if not isValid(user):       return errorResponse()  processUser(user)   ```   --- 3. Comments Don’t Fix Crap Code   - Don’t write comments to explain messy code. Fix the code instead.   - Write comments that add value: explain *why* something is done, not *what* it does.  Bad: `// This function adds two numbers.`   Good: `// Handles edge case when input is null.`  --- 4. Break Big Functions — Now   If your function scrolls off the screen, you’ve already lost.   - A function should do one thing only.   - Break tasks into smaller, reusable functions.  ✅ 50 lines of logic → 5 clean, readable functions.  --- 5. Hardcoding is Lazy   Ever seen `if (status == 200)`? Replace it with constants or enums.   - Magic numbers and strings make your code fragile.   - Write once. Reuse everywhere.  ✅ Example:   ```javascript   if (response.status === HTTP_STATUS_OK) {       handleSuccess();   }   ``` --- 6. Eliminate Repeated Code   Duplication is technical debt you’ll pay back with interest.   - Use functions, loops, or constants to DRY (Don’t Repeat Yourself).   - If you write the same code twice, refactor.  ✅ Rule: Copy-paste? Nope. Fix it.  --- 7. Write Code That’s Tested, Not Trusted   If you “think” your code works, you’re guessing.   - Write unit tests to prove it works.   - Tested code gives you confidence to refactor and deploy.  ✅ Tests = less fear, fewer bugs, and happier users.  --- Clean code is a necessity.  Stop writing code you’re embarrassed to show in a PR. Start writing code that future engineers (including you) will thank you for.  Which of these habits are you working on? Drop your favorite clean code tip below! 👇 -- P.S: If you're preparing for a SDE role , do check out my ultimate guide for behavioral interviews. It’s the perfect blueprint for cracking the behavioral interviews where most get eliminated and for breaking into big tech, startups, or MAANG companies. Here’s the link → https://lnkd.in/drnsTNhU (160+ engineers are already using it)

Here’s how to clean up messy frontend and backend code—for good: ☑ Frontend Refactoring (React, Vue, Svelte) 1. Modularize the UI → Break large components into smaller, reusable ones → Use component libraries (like Storybook) to enforce consistency 2. Tame the State Monster → Ditch prop drilling for Context, Zustand, or Vuex → Clean up unused state and only lift when necessary 3. Prevent Useless Renders → Use memo, useMemo, useCallback, or Vue’s computed → Code-split and lazy load for faster UX 4. Modernize Your Styles → Try Tailwind, CSS-in-JS, or scoped styles in Vue → Remove dead CSS and centralize theme tokens 5. Lint It or Regret It → Add ESLint, Prettier, and TypeScript for sanity → Automate formatting in CI 6. Shrink Your Bundle → Enable tree shaking, dynamic imports, and minification → Tools like Vite, Webpack, or esbuild make it easy — ☑ Backend Refactoring (Node, Express, Nest, Django, Rails) 1. Modular by Design → Use MVC or Hexagonal to separate concerns → Prefer grouping by feature, not layers 2. Service Layer FTW → Keep business logic out of controllers → Easier to test, scale, and maintain 3. Database Speed Boost → Add indexes, cache smartly (Redis), and avoid N+1 queries → Normalize or denormalize based on query patterns 4. Make Your APIs a Joy to Use → Use pagination, filtering, and proper HTTP status codes → REST is great—but consider GraphQL for flexibility 5. Go Async or Go Home → Offload heavy work to queues (Bull, Sidekiq, Celery) → Use async/await where I/O blocking hurts 6. Test. Then Test Again. → Split large functions into testable units → Write unit + integration tests and run them on every commit — Cross-Cutting Musts → Atomic commits with clear messages → API docs with Swagger or JSDoc → Automate tests and linting with CI/CD — Refactoring isn’t just technical debt cleanup—it’s developer self-respect. If this helped, repost to help clean up someone else’s codebase too. Or DM me if you want to apply these to your stack.

I’ve reviewed close to 2000+ code review requests in my career. At this point, it’s as natural to me as having a cup of coffee. However, from a senior engineer to now an engineering manager, I’ve learned a lot in between. If I had to learn to review code all over again, this would be the checklist I follow (inspired from my experience) 1. Ask clarifying questions:      - What are the exact constraints or edge cases I should consider?      - Are there any specific inputs or outputs to watch for?      - What assumptions can I make about the data?      - Should I optimize for time or space complexity?  2. Start simple:      - What is the most straightforward way to approach this?      - Can I explain my initial idea in one sentence?      - Is this solution valid for the most common cases?      - What would I improve after getting a basic version working?  3. Think out loud:      - Why am I taking this approach over another?      - What trade-offs am I considering as I proceed?      - Does my reasoning make sense to someone unfamiliar with the problem?      - Am I explaining my thought process clearly and concisely?  4. Break the problem into smaller parts:      - Can I split the problem into logical steps?      - What sub-problems need solving first?      - Are any of these steps reusable for other parts of the solution?      - How can I test each step independently?  5. Use test cases:      - What edge cases should I test?      - Is there a test case that might break my solution?      - Have I checked against the sample inputs provided?      - Can I write a test to validate the most complex scenario?  6. Handle mistakes gracefully:      - What’s the root cause of this mistake?      - How can I fix it without disrupting the rest of my code?      - Can I explain what went wrong to the interviewer?      - Did I learn something I can apply to the rest of the problem?  7. Stick to what you know:      - Which language am I most confident using?      - What’s the fastest way I can implement the solution with my current skills?      - Are there any features of this language that simplify the problem?      - Can I use familiar libraries or tools to save time?  8. Write clean, readable code:      - Is my code easy to read and understand?      - Did I name variables and functions meaningfully?      - Does the structure reflect the logic of the solution?      - Am I following best practices for indentation and formatting?  9. Ask for hints when needed:      - What part of the problem am I struggling to understand?      - Can the interviewer provide clarification or a nudge?      - Am I overthinking this?      - Does the interviewer expect a specific approach?  10. Stay calm under pressure:      - What’s the first logical step I can take to move forward?      - Have I taken a moment to reset my thoughts?      - Am I focusing on the problem, not the time ticking away?      - How can I reframe the problem to make it simpler?  

One of the best advice I’ve received from a senior early in my career was to read Clean Code by Robert C. This is one of the most impactful books I’ve ever read. It forever changed how I used to code. If I had to summarize the 10 most important principles from the book, they would be: 1. Meaningful Names - Choose clear, descriptive names that reveal the intent of your code. - Names should help others understand the purpose without extra context. - Example: Use `totalCost` instead of `x` for clarity. 2. Small Functions - Keep functions small and focused on a single task. - If a function exceeds 20 lines, consider refactoring. - Example: A `calculateTotal()` function should only handle calculations, not logging. 3. DRY Principle (Don’t Repeat Yourself) - Avoid code duplication to reduce maintenance complexity and potential bugs. - Aim for reusability and modularity in your code. - Example: Use a `processUserInput()` function rather than repeating the same logic multiple times. 4. Avoid Comments - Write self-explanatory code to minimize the need for comments. - Outdated comments can mislead, so focus on making the code itself clear. - Example: Refactor a complicated `for` loop into a well-named function rather than explaining it with comments. 5. Error Handling - Separate error handling from business logic to keep code clean. - Handle exceptions gracefully to maintain resilience. - Example: Use a `try-catch` block around critical operations and log errors in a dedicated function. 6. Readable Code - Prioritize readability over cleverness to make the code easy to understand. - Consistent formatting and naming conventions enhance code clarity. - Example: Use clear indentation and consistent variable names like `userName` and `userAge`. 7. Single Responsibility Principle (SRP) - Ensure each class and function has one responsibility or reason to change. - This principle makes the code more modular and easier to test. - Example: A `User` class should only handle user-related data, not database operations. 8. Dependency Injection - Rely on interfaces or abstractions rather than concrete implementations. - This approach decouples components and makes the code more flexible and testable. - Example: Inject a `PaymentProcessor` interface into a `Checkout` class rather than using a specific payment gateway directly. 9. Testing - Write automated tests to validate your code and catch bugs early. - Tests act as a safety net, ensuring code behaves as expected after changes. - Example: Use unit tests to verify that a `calculateDiscount()` function returns the correct value for various input scenarios. 10. Refactoring - Continuously improve your code through refactoring to maintain quality. - Refactoring should be an ongoing process, not a one-time task. - Example: Regularly revisit old code to simplify logic or reduce duplication, like merging similar methods into one.