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johndoe6345789
dd33d9823d
- Implemented functionality tests covering page navigation, header behavior, form handling, and error management. - Created mobile-responsive tests to ensure touch interactions, viewport adaptability, and safe area respect. - Developed visual regression tests for home page layout, typography, color consistency, and interactive elements. - Added a test runner script for easier execution of E2E tests with various options.
154 lines
3.8 KiB
Markdown
154 lines
3.8 KiB
Markdown
Here’s a practical, engineering-grade set of coding principles that actually keep a codebase healthy over years—not just during the honeymoon phase. Think of this as preventative maintenance, not moral philosophy 🛠️🧠.
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⸻
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1. Smallness Is a Feature
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Large things rot faster.
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• Small files
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• Small functions
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• Small modules
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• Small responsibilities
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If a file feels “important,” it’s probably doing too much. Decomposition beats cleverness every time.
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Size is friction. Friction accumulates.
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⸻
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2. One Reason to Change
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This is the only part of SOLID that really matters in practice.
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• Every file should exist for one reason
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• If a change request makes you touch unrelated logic, the boundary is wrong
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Violations show up as:
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• “While I’m here…” edits
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• Fear-driven refactors
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• Accidental breakage
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⸻
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3. Make State Explicit (and Rare)
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Hidden state is technical debt wearing camouflage.
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• Prefer pure functions
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• Push IO to the edges
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• Name state transitions clearly
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• Avoid “ambient” globals, singletons, magic context
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If you can’t explain when state changes, it will betray you at scale 🧨.
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⸻
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4. Clarity Beats Brevity
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Concise code is nice. Readable code survives.
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• Prefer obvious over clever
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• Use boring names that describe intent
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• Avoid dense expressions that require mental simulation
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The best compliment for code:
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“I didn’t have to think.”
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⸻
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5. Structure > Comments
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Comments decay. Structure persists.
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• Encode intent in function names and types
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• Let data shape explain behavior
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• Use comments only for why, never what
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If you need a paragraph to explain a function, split the function.
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⸻
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6. Types Are a Design Tool
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Even in dynamic languages.
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• Types clarify contracts
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• They force edge cases into daylight
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• They prevent “just trust me” APIs
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A good type definition is executable documentation 📐.
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⸻
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7. Tests Define Reality
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Untested code is hypothetical.
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• Tests lock in behavior
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• Refactors without tests are rewrites in disguise
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• Focus on behavior, not implementation
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Healthy ratio:
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• Few unit tests per function
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• Strong integration tests per feature
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⸻
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8. Errors Are First-Class
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Failure paths deserve the same respect as success paths.
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• Handle errors explicitly
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• Avoid silent fallbacks
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• Fail fast, fail loud, fail usefully
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Most production bugs live in “this can’t happen” branches.
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⸻
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9. Consistency Is More Valuable Than Correctness
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A consistent codebase is navigable—even if imperfect.
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• Same patterns everywhere
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• Same naming conventions
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• Same folder logic
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Inconsistency multiplies cognitive load faster than any algorithmic inefficiency.
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⸻
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10. Refactor Continuously, Not Heroically
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Big refactors are usually a smell.
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• Refactor as you touch code
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• Leave things slightly better than you found them
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• Don’t let cleanup pile up into fear
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Entropy is real. You either fight it daily or lose spectacularly 🌪️.
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⸻
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11. Design for Deletion
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The best code is easy to remove.
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• Avoid tight coupling
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• Prefer composition over inheritance
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• Keep feature boundaries clean
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If you can’t delete a feature safely, it owns you—not the other way around.
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⸻
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12. Tooling Is Part of the Codebase
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Linters, formatters, CI, and automation are not optional polish.
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• Enforce rules mechanically
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• Remove human judgment where possible
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• Let tools be the bad cop
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Humans are bad at consistency. Machines love it 🤖.
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⸻
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The Meta-Principle
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A good codebase optimizes for future humans, not present cleverness.
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Every line you write is a tiny act of communication across time. Write like Future-You is tired, busy, and slightly annoyed—but still clever enough to appreciate clean design.
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Entropy never sleeps. Engineers must 😄
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