Code Review Best Practices

This skill activates when reviewing code for quality, correctness, security, and maintainability.

When to Use This Skill

Activate when:

Reviewing pull requests
Conducting code audits
Providing feedback on code quality
Identifying security vulnerabilities
Suggesting refactoring improvements
Checking adherence to coding standards

Code Review Checklist

1. Correctness and Functionality

Does the code do what it's supposed to do?

Logic is correct and handles all cases
Edge cases are considered
Error handling is appropriate
No obvious bugs or logical errors
Assertions and validations are present
Return values are correct

Questions to ask:

What happens if this receives null/nil?
What if the list is empty?
What if the number is negative/zero?
Are there off-by-one errors?
Are comparisons correct (>, >=, <, <=)?

2. Security

Is the code secure?

No SQL injection vulnerabilities
No XSS (Cross-Site Scripting) vulnerabilities
No CSRF vulnerabilities (CSRF protection in place)
User input is validated and sanitized
Sensitive data is not logged
Authentication and authorization are properly implemented
No hardcoded secrets or credentials
File uploads are validated (type, size, content)
External URLs are validated
Rate limiting is in place for APIs

Common security issues:

# BAD: SQL injection vulnerability
query = "SELECT * FROM users WHERE id = #{user_id}"

# GOOD: Use parameterized queries
query = from u in User, where: u.id == ^user_id

# BAD: XSS vulnerability
raw("<div>#{user_input}</div>")

# GOOD: Escape user input
<div><%= user_input %></div>

# BAD: Hardcoded secrets
api_key = "sk_live_123456789"

# GOOD: Use environment variables
api_key = System.get_env("API_KEY")

# BAD: Mass assignment vulnerability
User.changeset(%User{}, params)

# GOOD: Whitelist allowed fields
User.changeset(%User{}, params)
# Where changeset only casts allowed fields:
# cast(user, attrs, [:name, :email])

3. Performance

Is the code efficient?

No N+1 query problems
Appropriate data structures chosen
Algorithms are efficient
Database indexes are used
Caching is implemented where appropriate
Large datasets are paginated or streamed
Unnecessary computations are avoided
Resources are cleaned up properly

Common performance issues:

# BAD: N+1 query
posts = Repo.all(Post)
Enum.map(posts, fn post ->
  author = Repo.get(User, post.author_id)  # Query for each post!
  {post, author}
end)

# GOOD: Preload associations
posts = Post |> preload(:author) |> Repo.all()

# BAD: Loading entire dataset
users = Repo.all(User)  # Loads all millions of users
Enum.filter(users, & &1.active)

# GOOD: Query in database
users = User |> where(active: true) |> Repo.all()

# BAD: Inefficient data structure
list = [1, 2, 3, 4, 5]
if 3 in list do  # O(n) lookup in list
  # ...
end

# GOOD: Use set/map for lookups
set = MapSet.new([1, 2, 3, 4, 5])
if MapSet.member?(set, 3) do  # O(1) lookup
  # ...
end

4. Code Quality and Maintainability

Is the code readable and maintainable?

Clear, descriptive variable and function names
Functions are small and focused (single responsibility)
No code duplication (DRY principle)
Comments explain "why", not "what"
Code follows project conventions and style guide
Magic numbers are replaced with named constants
Complexity is minimized
Code is self-documenting

Code quality issues:

# BAD: Unclear names
def calc(x, y, z) do
  r = x * y / z
  r * 1.2
end

# GOOD: Clear names
def calculate_discounted_price(quantity, unit_price, discount_percentage) do
  subtotal = quantity * unit_price
  discount_amount = subtotal * (discount_percentage / 100)
  subtotal - discount_amount
end

# BAD: Long function with multiple responsibilities
def process_order(order) do
  # Validate order (responsibility 1)
  # Calculate totals (responsibility 2)
  # Update inventory (responsibility 3)
  # Send email (responsibility 4)
  # Log analytics (responsibility 5)
end

# GOOD: Single responsibility functions
def process_order(order) do
  with {:ok, order} <- validate_order(order),
       {:ok, order} <- calculate_totals(order),
       {:ok, order} <- update_inventory(order),
       :ok <- send_confirmation_email(order),
       :ok <- log_order_analytics(order) do
    {:ok, order}
  end
end

# BAD: Magic numbers
if user.age >= 13 do
  # ...
end

# GOOD: Named constants
@minimum_age_coppa 13

if user.age >= @minimum_age_coppa do
  # ...
end

5. Error Handling

Are errors handled properly?

Errors don't crash the system unexpectedly
Error messages are helpful
Errors are logged appropriately
Happy path and error paths are both tested
No swallowed errors (empty catch blocks)
Proper error types are used

Error handling patterns:

# BAD: Silent failure
try do
  dangerous_operation()
rescue
  _ -> nil  # Error is swallowed!
end

# GOOD: Handle errors explicitly
case dangerous_operation() do
  {:ok, result} -> result
  {:error, reason} ->
    Logger.error("Operation failed: #{inspect(reason)}")
    {:error, reason}
end

# BAD: Generic error message
{:error, "failed"}

# GOOD: Specific error
{:error, :invalid_email_format}
{:error, {:validation_failed, errors}}

# BAD: Let it crash when shouldn't
def parse_config(path) do
  File.read!(path)  # Crashes if file missing
  |> Jason.decode!()  # Crashes if invalid JSON
end

# GOOD: Handle expected errors
def parse_config(path) do
  with {:ok, content} <- File.read(path),
       {:ok, config} <- Jason.decode(content) do
    {:ok, config}
  else
    {:error, :enoent} -> {:error, :config_file_not_found}
    {:error, %Jason.DecodeError{}} -> {:error, :invalid_config_format}
  end
end

6. Testing

Is the code properly tested?

New functionality has tests
Edge cases are tested
Error conditions are tested
Tests are clear and focused
Tests are deterministic (no flaky tests)
Test names describe what they test
Mocks are used appropriately
Test coverage is adequate

Testing concerns:

# BAD: Unclear test name
test "test1" do
  # ...
end

# GOOD: Descriptive test name
test "create_user/1 returns error when email is invalid" do
  # ...
end

# BAD: Testing too much at once
test "user workflow" do
  # Creates user
  # Updates user
  # Deletes user
  # All in one test!
end

# GOOD: Focused tests
test "create_user/1 creates user with valid attributes" do
  # ...
end

test "update_user/2 updates user name" do
  # ...
end

test "delete_user/1 removes user from database" do
  # ...
end

# BAD: Non-deterministic test
test "async operation completes" do
  start_async_operation()
  Process.sleep(100)  # Race condition!
  assert operation_completed?()
end

# GOOD: Deterministic test
test "async operation completes" do
  start_async_operation()
  assert_receive {:completed, _result}, 1000
end

7. Documentation

Is the code documented?

Public APIs have documentation
Complex logic has explanatory comments
README is updated if needed
Changelog is updated for user-facing changes
API documentation is accurate
Examples are provided

8. Dependencies

Are dependencies handled properly?

New dependencies are justified
Dependencies are up-to-date and maintained
Licenses are compatible with project
Security vulnerabilities are checked
Dependency versions are pinned or bounded

Review Process

Before Reviewing

Understand the context
- Read the PR description
- Understand the problem being solved
- Check related issues
Build and test locally
- Pull the branch
- Run tests
- Test the functionality manually

During Review

Start with the big picture
- Is the approach sound?
- Does it fit the architecture?
- Is there a better way?
Review for correctness
- Does it work as intended?
- Are edge cases handled?
- Is error handling appropriate?
Check security and performance
- Are there security vulnerabilities?
- Will it perform well at scale?
Review code quality
- Is it readable and maintainable?
- Does it follow conventions?
- Is it well-tested?

Providing Feedback

Be constructive and specific:

# BAD: Vague criticism
"This function is bad."

# GOOD: Specific, actionable feedback
"This function has three responsibilities: validation, database update, and email sending. Consider splitting it into separate functions for better testability and maintainability:

```elixir
def update_user(user, attrs) do
  with {:ok, changeset} <- validate_user_update(user, attrs),
       {:ok, user} <- save_user(changeset),
       :ok <- send_update_notification(user) do
    {:ok, user}
  end
end

BAD: Demanding

"You must change this."

GOOD: Collaborative

"What do you think about extracting this into a separate function? It would make the code easier to test."

BAD: Nitpicking without context

"Use single quotes instead of double quotes."

GOOD: Explain reasoning

"Our style guide prefers single quotes for consistency (see CONTRIBUTING.md section 3.2)."


**Use labels to categorize feedback:**

- **[blocking]**: Must be fixed before merging
- **[suggestion]**: Optional improvement
- **[question]**: Asking for clarification
- **[nit]**: Very minor, cosmetic issue
- **[security]**: Security concern
- **[performance]**: Performance concern

**Example:**

```markdown
[blocking] This creates a SQL injection vulnerability. Use parameterized queries:

```elixir
# Instead of:
query = "SELECT * FROM users WHERE name = '#{name}'"

# Use:
from(u in User, where: u.name == ^name)

[suggestion] Consider extracting this logic into a separate function for reusability.

[question] Why are we using a map here instead of a struct?

[nit] Extra blank line here.


### After Review

1. **Respond to author's questions**
2. **Re-review after changes**
3. **Approve when satisfied**
4. **Celebrate good code**

## Language-Specific Considerations

### Elixir

- Pattern matching is used effectively
- Functions leverage pipe operator for readability
- Atoms aren't created dynamically from untrusted input
- `with` statements handle errors properly
- Changesets validate all input
- No direct database queries in controllers/LiveViews (use contexts)

### JavaScript/TypeScript

- Types are properly defined (TypeScript)
- Promises are handled with .catch() or try/catch
- == vs === is used correctly
- Arrays/objects aren't mutated unexpectedly
- this binding is correct
- Async operations are properly awaited

### Python

- Type hints are used
- List comprehensions aren't overly complex
- Exceptions are specific (not bare except:)
- Resources are closed (use with statements)
- Code follows PEP 8

### Rust

- Ownership and borrowing are correct
- Error handling uses Result/Option properly
- Unsafe blocks are justified and minimal
- Clone/copy is used appropriately
- Lifetimes are correctly specified

## Common Code Smells

### Complexity Smells

- **Long functions** - Function does too much
- **Long parameter list** - Too many parameters
- **Deep nesting** - Too many levels of indentation
- **Complex conditionals** - Hard to understand if statements

### Duplication Smells

- **Copy-paste code** - Same code in multiple places
- **Similar functions** - Functions that do almost the same thing
- **Magic numbers** - Repeated literal values

### Naming Smells

- **Unclear names** - Variables like x, tmp, data
- **Misleading names** - Name doesn't match behavior
- **Inconsistent names** - Same concept called different things

### Design Smells

- **God object** - Class/module doing everything
- **Feature envy** - Function using another object's data more than its own
- **Inappropriate intimacy** - Too much coupling between modules

## Anti-Patterns to Watch For

### Premature Optimization

```elixir
# BAD: Optimizing before measuring
def calculate(data) do
  # Complex, hard-to-read optimization
  # that saves 0.1ms
end

# GOOD: Start simple, optimize if needed
def calculate(data) do
  # Clear, simple code
  # Optimize later if profiling shows bottleneck
end

Premature Abstraction

# BAD: Abstract after one use
defmodule AbstractDataProcessorFactoryBuilder do
  # Complex abstraction for single use case
end

# GOOD: Wait for second use case
def process_user_data(data) do
  # Simple, direct implementation
  # Abstract when pattern emerges
end

Error Swallowing

# BAD: Hiding errors
try do
  risky_operation()
rescue
  _ -> :ok  # What went wrong?
end

# GOOD: Handle explicitly
case risky_operation() do
  {:ok, result} -> {:ok, result}
  {:error, reason} ->
    Logger.error("Operation failed: #{inspect(reason)}")
    {:error, reason}
end

Review Etiquette

DO:

Be respectful and constructive
Assume good intent
Ask questions instead of making demands
Praise good code
Explain the "why" behind suggestions
Offer to pair program on complex issues
Respond promptly to author's replies

DON'T:

Be sarcastic or condescending
Bike-shed on minor style issues
Block on personal preferences
Review your own code without another reviewer
Approve code you don't understand
Nitpick excessively

Self-Review Checklist

Before submitting code for review:

Key Principles

Correctness first: Code must work correctly
Security matters: Always consider security implications
Be specific: Provide actionable, concrete feedback
Be respectful: Kind, constructive communication
Focus on important issues: Don't bike-shed
Explain reasoning: Help author learn, don't just dictate
Approve good code: Don't let perfect be enemy of good
Collaborate: You're on the same team

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