Demo Code Quality Metrics Standards

Documentation Index

Fetch the complete documentation index at: https://notes.kodekloud.com/llms.txt

Use this file to discover all available pages before exploring further.

https://github.com/JeremyMorgan/Claude-Code-Reviewing-Prompts

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Audit prompt (used to generate the analysis)

> Analyze code complexity across the codebase:

    Look for complex functions/methods.

    Also look at functions/methods and calculate/evaluate:

    1. CYCLOMATIC COMPLEXITY
      - Functions with complexity > 10
      - Nested if/else depth
      - Switch statement complexity
      - Recommend refactoring for high complexity

    2. COGNITIVE COMPLEXITY
      - How hard is the code to understand?
      - Nested loops and conditions
      - Recursive calls
      - Mixed levels of abstraction

    3. LINES OF CODE METRICS
      - Functions over 50 lines
      - Files over 300 lines
      - Classes over 500 lines
      - Identify candidates for splitting

    4. COUPLING METRICS
      - Afferent coupling (dependencies on this module)
      - Efferent coupling (dependencies of this module)
      - Instability index
      - Identify tightly coupled modules

    5. COHESION ANALYSIS
      - Are related functions grouped?

Provide specific refactoring recommendations for complex areas.

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What this audit looks for (quick reference)

• Cyclomatic complexity: counts decision points (if/else, switch, loops, logical operators, ternary). Typical threshold: > 10 → consider refactor.
• Cognitive complexity: a human-centered score reflecting how hard the code is to understand (deep nesting, mixed abstractions).
• Lines-of-code (LOC) metrics: functions > 50 LOC, files > 300 LOC, classes > 500 LOC suggest candidates for splitting.
• Coupling: afferent/efferent coupling and instability — identify tightly coupled modules that are hard to change or test.
• Cohesion: whether related functions are grouped and whether modules follow single-responsibility.

• Cyclomatic complexity is objective and easy to calculate.
• Cognitive complexity is subjective but reducing it improves maintainability and reviewability.

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Initial files identified by the audit

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Executive summary

• The codebase is generally small and well-structured at a module level.
• The principal hotspot is the authentication route handler (routes/auth.js): the login handler mixes validation, DB access, credential verification, token creation, and error mapping in a single long function.
• Recommended immediate actions: split responsibilities (validation, service layer, token utility, error mapping) to reduce cyclomatic and cognitive complexity and to enable easier unit testing.

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1. Cyclomatic Complexity

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High complexity function (> 10)

• Location: routes/auth.js (approx lines 17–96)
• Cyclomatic Complexity: 12
• Concerns:
  • Multiple decision points: validation checks, user lookup results, password verification, error-code mapping (switch), token creation flow.
  • Nested if/else depth and switch statement increase branching.

• Extract responsibilities into separate functions:
  • Input validation
  • User lookup
  • Password check
  • Token generation
  • Error mapping (use an error-mapper utility instead of inline switch)

1. Input validation (e.g., !errors.isEmpty())
2. User lookup result (user found or not)
3. Password validation success/failure
4. Presence of error.code
5. Error mapping switch (multiple cases)
6. Token creation and response paths

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2. Cognitive Complexity

• The login handler mixes domain and infrastructure logic (DB queries and business rules), increasing mixed abstractions and cognitive load.
• Nested conditionals reach three levels deep, making the flow harder to reason about during reviews.
• Recommendation: move DB and infra logic into a service layer so the route handler becomes an orchestrator that composes those services.

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3. Lines-of-Code (LOC) Metrics

• Functions > 50 LOC: 1 (the login handler, ~80 lines) — candidate for splitting.
• Files > 300 LOC: none.
• Classes > 500 LOC: none.
• Recommendation: split the large handler into well-named functions or service modules to improve readability and unit testing.

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4. Coupling Metrics

• The authentication module depends on several external libraries (validation, DB client, JWT).
• Afferent/efferent coupling is moderate — expected for authentication—but introducing dependency injection for the DB client and token utility will improve testability and reduce tight coupling.

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5. Cohesion Analysis

• Overall project modules are cohesive (server, config, routes), but the login handler violates single-responsibility by handling multiple concerns within one function.
• Recommendation: reorganize into smaller cohesive modules (validation, authService, tokenUtil, errorMapper).

• Extract validation into a helper function (throws structured error on validation failure).
• Move authentication logic into an authService that encapsulates user lookup and password verification.
• Create a tokenUtil for JWT generation.
• Consolidate DB/infrastructure error mapping into a small errorMapper utility.

// validateLoginRequest.js
const { validationResult } = require('express-validator');
const ValidationError = require('../errors/ValidationError');

const validateLoginRequest = (req) => {
  const errors = validationResult(req);
  if (!errors.isEmpty()) {
    throw new ValidationError(errors.array());
  }
  return req.body;
};

module.exports = validateLoginRequest;

// tokenUtil.js
const jwt = require('jsonwebtoken');

const generateAuthToken = (user) => {
  return jwt.sign(
    { userId: user.id, email: user.email },
    process.env.JWT_SECRET,
    { expiresIn: process.env.JWT_EXPIRES_IN || '24h' }
  );
};

module.exports = generateAuthToken;

• routes/auth.js — lightweight orchestrator: validate -> authService -> tokenUtil -> response
• services/authService.js — user lookup, password verification, and business logic
• utils/tokenUtil.js — JWT creation
• utils/errorMapper.js — map DB and infra errors into HTTP-friendly errors

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Priority refactor list

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Refactoring implementation plan (phased)

• Phase 1: Add small utilities (validation helper, token util, error mapper). Keep changes backward-compatible.
• Phase 2: Move DB queries into authService and inject the DB client (improves testability).
• Phase 3: Replace the monolithic route handler with a slim orchestrator that composes services and returns standardized responses.
• Phase 4: Add unit tests for each service and integration tests for the route layer.

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Metrics summary

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Concluding remarks

• The codebase has a solid module-level structure, but the authentication route handler concentrates unnecessary complexity.
• Breaking the handler into smaller functions/services (validation, service layer, token util, error mapper) will reduce cyclomatic and cognitive complexity and make the code easier to test and maintain.
• After refactors, re-run complexity analysis and add unit tests to validate improvements.

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Next steps

• Implement the Phase 1 refactors (validation helper, token util, error mapper) and run tests.
• Re-run static complexity checks (e.g., ESLint plugins that compute complexity) and compare metrics.
• Address any code duplication and follow DRY principles across services.

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Links and references

• Repository of audit prompts: https://github.com/JeremyMorgan/Claude-Code-Reviewing-Prompts
• express-validator: https://express-validator.github.io/docs/
• jsonwebtoken (JWT): https://github.com/auth0/node-jsonwebtoken
• Cyclomatic complexity overview: https://en.wikipedia.org/wiki/Cyclomatic_complexity
• Cognitive complexity concept (SonarSource): https://www.sonarsource.com/resources/what-is-cognitive-complexity/