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coding-principles

Language-agnostic coding principles for maintainability, readability, and quality. Use when implementing features, refactoring code, or reviewing code quality.

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Language-Agnostic Coding Principles

Core Philosophy

  1. Maintainability over Speed: Prioritize long-term code health over initial development velocity
  2. Simplicity First: Choose the simplest solution that meets requirements (YAGNI principle)
  3. Design Convergence: Deliver the current required outcome with the least new design surface. Selecting persistent state, public or cross-boundary contracts, behavioral modes, reusable abstractions, or component splits carries enough surface to justify the full convergence process first.
  4. Explicit over Implicit: Make intentions clear through code structure and naming
  5. Delete over Comment: Remove unused code instead of commenting it out

Code Quality

Continuous Improvement

  • Refactor related code inside the accepted outcome and governing boundaries when it reduces the change's risk or maintenance cost
  • Improve code structure incrementally
  • Keep the codebase lean and focused
  • Delete code proven obsolete by the requested change after checking its callers; report uncertain or out-of-scope cleanup separately

Readability

  • Use meaningful, descriptive names drawn from the problem domain
  • Use full words in names; abbreviations are acceptable only when widely recognized in the domain
  • Use descriptive names; single-letter names are acceptable only for loop counters or well-known conventions (i, j, x, y)
  • Extract magic numbers and strings into named constants
  • Keep code self-documenting where possible

Function Design

Parameter Management

  • Group related positional parameters into an object, struct, or dictionary when call-site clarity or coordinated evolution requires it. Retain positional parameters when their order is conventional and the call remains clear, or an external/public signature requires them
  • Preserve external/public signatures unless their migration is part of the accepted outcome or governing artifact

Single Responsibility

  • Each function should do one thing well
  • Extract a function when independently changing responsibilities or obscured control flow make the current unit harder to understand, verify, or reuse; retain a cohesive domain flow when extraction would create artificial coupling
  • Extract complex logic into separate, well-named functions
  • Functions should have a single level of abstraction

Function Organization

  • Pure functions when possible (no side effects)
  • Separate data transformation from side effects
  • Use early returns to reduce nesting
  • Use early returns or extraction when nesting obscures state transitions or decision ownership; retain nested structure when it maps the domain decision more clearly

Error Handling

Error Management Principles

  • Always handle errors: Log with context or propagate explicitly
  • Log appropriately: Include context for debugging
  • Protect sensitive data: Mask or exclude passwords, tokens, PII from logs
  • Fail fast: Detect and report errors as early as possible

Error Propagation

  • Use language-appropriate error handling mechanisms
  • Propagate errors to appropriate handling levels
  • Provide meaningful error messages
  • Include error context when re-throwing

Dependency Management

Loose Coupling via Parameterized Dependencies

  • Inject external dependencies as parameters (constructor injection for classes, function parameters for procedural/functional code)
  • Depend on abstractions, not concrete implementations
  • Minimize inter-module dependencies
  • Facilitate testing through mockable dependencies

Reference Representativeness

Verifying References Before Adoption

When adopting patterns, APIs, or dependencies from existing code:

  • IF a reference sample covers only nearby files → THEN confirm the pattern is representative by checking relevant repository usage before adopting
  • IF multiple approaches coexist in the repository → THEN identify the majority pattern and make a deliberate choice — selecting whichever is nearest is insufficient
  • IF adopting an external dependency (library, plugin, SDK) → THEN verify repository-wide usage and compatibility evidence; when that evidence cannot determine the required version, record the unresolved version decision and the evidence needed to settle it
  • IF following an existing pattern → THEN state the reason for following it when an alternative exists (e.g., consistency with surrounding code, avoiding breaking changes, pending coordinated update)

Principle

Nearby code is a starting point for investigation, not a sufficient basis for adoption. Verify that what you reference is representative of the repository's conventions and current best practices before using it as a model.

Performance Considerations

Optimization Approach

  • Measure first: Profile before optimizing
  • Focus on algorithms: Algorithmic complexity > micro-optimizations
  • Use appropriate data structures: Choose based on access patterns
  • Resource management: Handle memory, connections, and files properly

When to Optimize

  • After identifying actual bottlenecks through profiling
  • When performance issues are measurable
  • Optimize only after measurable bottlenecks are identified, not during initial development

Code Organization

Structural Principles

  • Group related functionality: Keep related code together
  • Separate concerns: Domain logic, data access, presentation
  • Consistent naming: Follow project conventions
  • Module cohesion: High cohesion within modules, low coupling between

File Organization

  • One primary responsibility per file
  • Logical grouping of related functions/classes
  • Clear folder structure reflecting architecture
  • Split a file when it contains independently changing responsibilities or creates material navigation, coupling, or verification cost; retain a cohesive file when splitting would add avoidable coupling or navigation cost

Commenting Principles

Default: code first

Names, types, and structure are the primary medium. A comment earns its place only by carrying information the code itself cannot express. When in doubt, improve the name instead of adding a comment.

The test for every comment

A comment is justified only if it answers one of these:

  • Why: reasoning, trade-off, or constraint behind a non-obvious decision
  • Limitation / edge case: a boundary a reader cannot infer from the code
  • Public API contract: behavior, inputs, outputs of an exported interface

One comment per decision. If a comment restates what the names and control flow already show, delete it and rename instead.

Comment Scope

  • Comment the why, limits, and public contracts (per the test above); let names and structure carry everything else, including the "how"
  • Record historical context in version control commit messages, not in comments
  • Delete commented-out code (retrieve from git history when needed)

Comment Quality

  • Base comments on stable rationale, limits, and contracts rather than dates, versions, or temporary state
  • Update comments when changing code
  • Use proper grammar and formatting
  • Write for future maintainers

Refactoring Approach

Safe Refactoring

  • Small steps: Make one change at a time
  • Maintain working state: Keep tests passing
  • Verify behavior: Run tests after each change
  • Incremental improvement: Make the smallest sufficient improvement in each increment

Refactoring Triggers

  • Code duplication (DRY principle)
  • Functions that contain independently changing responsibilities or obscured control flow
  • Complex conditional logic
  • Unclear naming or structure

Security Principles

Secure Defaults

  • Store credentials and secrets through environment variables or dedicated secret managers
  • Use parameterized queries (prepared statements) for all database access
  • Use established cryptographic libraries provided by the language or framework
  • Generate security-critical values (tokens, IDs, nonces) with cryptographically secure random generators
  • Encrypt sensitive data at rest and in transit using standard protocols

Input and Output Boundaries

  • Validate all external input at system entry points for expected format, type, and length
  • Encode output appropriately for its rendering context (HTML, SQL, shell, URL)
  • Return only information necessary for the caller in error responses; log detailed diagnostics server-side

Access Control

  • Apply authentication to all entry points that handle user data or trigger state changes
  • Verify authorization for each resource access, not only at the entry point
  • Grant only the permissions required for the operation (files, database connections, API scopes)
  • For changes involving identity or protected resources, prioritize authentication and per-resource authorization review

For concrete detection patterns used by security review, see references/security-checks.md.

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