CT Neal-Herman
Friday, January 16, 2026
Clean Code Chapter 5: Formatting
Wednesday, January 7, 2026
Clean Code Chapter 4: Comments, or The Art of Saying Nothing
Clean Code Chapter 4: Comments, or The Art of Saying Nothing
One of the most counterintuitive lessons in Robert Martin's Clean Code appears in Chapter 4: the best comment is often no comment at all. As Martin puts it, "the proper use of comments is to compensate for our failure to express ourselves in code."
This doesn't mean comments are evil. It means they're a last resort. When you feel the urge to write a comment, your first instinct should be to ask: Can I refactor this code so the comment becomes unnecessary?
Why Comments Lie
Comments have a fundamental problem: they rot. Code changes, deadlines loom, and comments get left behind. Unlike code, comments don't throw errors when they become inaccurate. A misleading comment is worse than no comment at all because it actively deceives the reader.
Martin argues that we should spend our energy making code self-documenting rather than explaining unclear code with comments.
Good Comments vs. Bad Comments
Not all comments are bad. Martin identifies several legitimate uses:
Acceptable comments:
- Legal notices (copyright, licensing)
- Explanation of intent when the why isn't obvious from code
- Clarification of obscure arguments or return values from external libraries
- Warnings of consequences
- TODO markers (used sparingly)
Comments to avoid:
- Redundant comments that repeat what the code says
- Commented-out code (that's what version control is for)
- Position markers and banners
- Attributions (again, version control)
- Closing brace comments
Rails Example: Let the Code Speak
Here's a common pattern I see in Rails applications with over-commenting:
# Bad: Comments that add noise
class OrderProcessor
# Process the order
def process(order)
# Check if order is valid
return unless order.valid?
# Calculate the total price of all items
total = order.line_items.sum do |item|
# Multiply quantity by unit price
item.quantity * item.unit_price
end
# Apply discount if customer has one
if order.customer.discount_percentage.present?
# Calculate discount amount
discount = total * (order.customer.discount_percentage / 100.0)
# Subtract discount from total
total = total - discount
end
# Save the total to the order
order.update(total_amount: total)
# Send confirmation email to customer
OrderMailer.confirmation(order).deliver_later
end
end
Every comment here restates what the code already says. The method name process is vague, forcing us to read comments to understand what's happening. Let's refactor:
# Good: Self-documenting code
class OrderProcessor
def finalize_and_confirm(order)
return unless order.valid?
order.update(total_amount: calculate_discounted_total(order))
OrderMailer.confirmation(order).deliver_later
end
private
def calculate_discounted_total(order)
subtotal = order.line_items.sum(&:total_price)
apply_customer_discount(subtotal, order.customer)
end
def apply_customer_discount(amount, customer)
return amount unless customer.discount_percentage.present?
amount * (1 - customer.discount_percentage / 100.0)
end
end
The refactored version uses method names that explain intent. finalize_and_confirm tells you exactly what the public method does. calculate_discounted_total and apply_customer_discount make the business logic readable without a single comment.
Notice how extracting total_price to the LineItem model (implied by sum(&:total_price)) moves that logic where it belongs. The code reads like a sentence describing the business process.
React Example: When Comments Help and When They Hurt
Frontend code often accumulates comments explaining complex UI logic. Here's a React component drowning in unnecessary comments:
// Bad: Comment noise obscuring the code
interface CartProps {
items: CartItem[];
onCheckout: () => void;
}
function ShoppingCart({ items, onCheckout }: CartProps) {
// State for showing the discount input
const [showDiscount, setShowDiscount] = useState(false);
// State for the discount code value
const [discountCode, setDiscountCode] = useState('');
// State for discount validation error
const [error, setError] = useState<string | null>(null);
// Calculate the total price
const total = items.reduce((sum, item) => {
// Add item price times quantity to sum
return sum + item.price * item.quantity;
}, 0); // Start with 0
// Handle applying the discount code
const handleApplyDiscount = () => {
// Check if code is valid
if (discountCode.length < 5) {
// Set error message
setError('Invalid discount code');
return;
}
// Clear error and apply
setError(null);
// TODO: Actually apply discount
};
// Render the component
return (
<div className="cart">
{/* Map through items and display them */}
{items.map((item) => (
// Use item id as key
<CartItemRow key={item.id} item={item} />
))}
{/* Show total */}
<div className="total">Total: ${total.toFixed(2)}</div>
{/* Checkout button */}
<button onClick={onCheckout}>Checkout</button>
</div>
);
}
The comments here are pure noise. // Calculate the total price before a variable called total adds nothing. // Render the component before a return statement is almost comical. Let's clean this up:
// Good: Clear code with one meaningful comment
interface CartProps {
items: CartItem[];
onCheckout: () => void;
}
function ShoppingCart({ items, onCheckout }: CartProps) {
const [discountForm, setDiscountForm] = useState({
isVisible: false,
code: '',
error: null as string | null,
});
const cartTotal = items.reduce(
(sum, item) => sum + item.price * item.quantity,
0
);
const applyDiscountCode = () => {
const MIN_CODE_LENGTH = 5;
if (discountForm.code.length < MIN_CODE_LENGTH) {
setDiscountForm((prev) => ({ ...prev, error: 'Invalid discount code' }));
return;
}
setDiscountForm((prev) => ({ ...prev, error: null }));
// TODO: Integrate with discount API once pricing service is deployed
};
return (
<div className="cart">
{items.map((item) => (
<CartItemRow key={item.id} item={item} />
))}
<div className="total">Total: ${cartTotal.toFixed(2)}</div>
<button onClick={onCheckout}>Checkout</button>
</div>
);
}
The refactored version groups related state into a single object with descriptive property names. cartTotal is more specific than total. The magic number 5 becomes a named constant MIN_CODE_LENGTH.
One comment remains: the TODO. This is a legitimate use because it explains why the code is incomplete (waiting on an external dependency) rather than restating what the code does.
The Litmus Test
Before writing a comment, ask yourself these questions:
- Can I rename this variable or function to eliminate the need for this comment?
- Can I extract this logic into a well-named method?
- Am I explaining what the code does (bad) or why it does something non-obvious (potentially acceptable)?
- Will this comment stay accurate as the code evolves?
If you can refactor instead of comment, do it. Your future self (and your teammates) will thank you.
The Takeaway
Comments aren't inherently bad, but they should make you pause. Each comment is an admission that your code couldn't speak for itself. Sometimes that's unavoidable. More often, it's an invitation to write clearer code.
As Martin writes: "The only truly good comment is the comment you found a way not to write."
Tuesday, December 30, 2025
Clean Code Chapter 3: Functions
Clean Code Chapter 3: Functions
Writing Functions That Tell a Story
In Chapter 3 of Clean Code, Robert C. Martin lays out a compelling vision: functions should be small, do one thing, and read like well-written prose. This chapter transformed how I think about structuring code, and the principles apply beautifully to both Rails backends and React frontends.
Let's explore the key ideas with practical examples.
Small!
Martin's first rule of functions is that they should be small. His second rule? They should be smaller than that.
Functions should rarely be more than 20 lines. Ideally, they should be 5-10 lines. This isn't arbitrary. Small functions are easier to understand, test, and maintain.
Rails Example
Before: A bloated controller action
def create
@user = User.new(user_params)
if @user.save
if params[:subscribe_to_newsletter]
newsletter = Newsletter.find_by(name: 'weekly')
if newsletter
Subscription.create(user: @user, newsletter: newsletter)
NewsletterMailer.welcome_email(@user).deliver_later
end
end
if @user.referral_code.present?
referrer = User.find_by(referral_code: @user.referral_code)
if referrer
Credit.create(user: referrer, amount: 10, reason: 'referral')
Credit.create(user: @user, amount: 5, reason: 'referred')
ReferralMailer.successful_referral(referrer, @user).deliver_later
end
end
redirect_to dashboard_path, notice: 'Welcome!'
else
render :new
end
end
After: Small, focused functions
def create
@user = User.new(user_params)
if @user.save
handle_newsletter_subscription
process_referral
redirect_to dashboard_path, notice: 'Welcome!'
else
render :new
end
end
private
def handle_newsletter_subscription
return unless params[:subscribe_to_newsletter]
NewsletterSubscriptionService.subscribe(@user, 'weekly')
end
def process_referral
return unless @user.referral_code.present?
ReferralService.process(@user, @user.referral_code)
end
React Example
Before: A component doing too much
function UserDashboard({ userId }: { userId: string }) {
const [user, setUser] = useState<User | null>(null);
const [orders, setOrders] = useState<Order[]>([]);
const [notifications, setNotifications] = useState<Notification[]>([]);
const [loading, setLoading] = useState(true);
useEffect(() => {
setLoading(true);
fetch(`/api/users/${userId}`)
.then(res => res.json())
.then(data => {
setUser(data);
return fetch(`/api/users/${userId}/orders`);
})
.then(res => res.json())
.then(data => {
setOrders(data);
return fetch(`/api/users/${userId}/notifications`);
})
.then(res => res.json())
.then(data => {
setNotifications(data);
setLoading(false);
});
}, [userId]);
if (loading) return <Spinner />;
return (
<div>
<h1>Welcome, {user?.name}</h1>
<div className="stats">
<div>Orders: {orders.length}</div>
<div>Unread: {notifications.filter(n => !n.read).length}</div>
</div>
<ul>
{orders.map(order => (
<li key={order.id}>
Order #{order.id} - ${order.total} - {order.status}
</li>
))}
</ul>
</div>
);
}
After: Composed from smaller pieces
function UserDashboard({ userId }: { userId: string }) {
const { user, orders, notifications, loading } = useDashboardData(userId);
if (loading) return <Spinner />;
return (
<div>
<WelcomeHeader userName={user?.name} />
<DashboardStats orderCount={orders.length} notifications={notifications} />
<OrderList orders={orders} />
</div>
);
}
function DashboardStats({
orderCount,
notifications
}: {
orderCount: number;
notifications: Notification[];
}) {
const unreadCount = notifications.filter(n => !n.read).length;
return (
<div className="stats">
<div>Orders: {orderCount}</div>
<div>Unread: {unreadCount}</div>
</div>
);
}
Do One Thing
Functions should do one thing. They should do it well. They should do it only.
But how do you know if a function does "one thing"? Martin offers a useful test: if you can extract another function from it with a name that isn't merely a restatement of its implementation, it's doing more than one thing.
Rails Example
Before: A method doing multiple things
def process_order(order)
# Validate inventory
order.line_items.each do |item|
product = item.product
if product.inventory_count < item.quantity
raise InsufficientInventoryError, "Not enough #{product.name}"
end
end
# Calculate totals
subtotal = order.line_items.sum { |item| item.price * item.quantity }
tax = subtotal * order.tax_rate
shipping = calculate_shipping(order)
total = subtotal + tax + shipping
# Update order
order.update!(
subtotal: subtotal,
tax: tax,
shipping: shipping,
total: total,
status: 'confirmed'
)
# Send notifications
OrderMailer.confirmation(order).deliver_later
InventoryService.reserve_items(order)
end
After: Each function does one thing
def process_order(order)
validate_inventory(order)
finalize_totals(order)
confirm_order(order)
send_notifications(order)
end
private
def validate_inventory(order)
InventoryValidator.validate!(order)
end
def finalize_totals(order)
OrderTotalCalculator.calculate!(order)
end
def confirm_order(order)
order.update!(status: 'confirmed')
end
def send_notifications(order)
OrderNotifier.send_confirmation(order)
InventoryService.reserve_items(order)
end
React Example
Before: A handler doing multiple things
function handleSubmit(event: FormEvent) {
event.preventDefault();
// Validation
const errors: string[] = [];
if (!formData.email.includes('@')) {
errors.push('Invalid email');
}
if (formData.password.length < 8) {
errors.push('Password too short');
}
if (formData.password !== formData.confirmPassword) {
errors.push('Passwords do not match');
}
if (errors.length > 0) {
setErrors(errors);
return;
}
// Transform data
const payload = {
email: formData.email.toLowerCase().trim(),
password: formData.password,
marketingOptIn: formData.newsletter,
};
// Submit
setSubmitting(true);
fetch('/api/register', {
method: 'POST',
body: JSON.stringify(payload),
})
.then(res => res.json())
.then(data => {
localStorage.setItem('token', data.token);
navigate('/dashboard');
})
.catch(err => setErrors([err.message]))
.finally(() => setSubmitting(false));
}
After: Separated concerns
function handleSubmit(event: FormEvent) {
event.preventDefault();
const validationErrors = validateRegistrationForm(formData);
if (validationErrors.length > 0) {
setErrors(validationErrors);
return;
}
submitRegistration(formData);
}
function validateRegistrationForm(data: RegistrationFormData): string[] {
const errors: string[] = [];
if (!isValidEmail(data.email)) errors.push('Invalid email');
if (!isValidPassword(data.password)) errors.push('Password too short');
if (!passwordsMatch(data.password, data.confirmPassword)) {
errors.push('Passwords do not match');
}
return errors;
}
async function submitRegistration(data: RegistrationFormData) {
setSubmitting(true);
try {
const payload = buildRegistrationPayload(data);
const response = await registerUser(payload);
handleSuccessfulRegistration(response);
} catch (err) {
setErrors([err.message]);
} finally {
setSubmitting(false);
}
}
One Level of Abstraction per Function
Functions should maintain a consistent level of abstraction. Mixing high-level concepts with low-level details creates cognitive dissonance.
Rails Example
Before: Mixed abstraction levels
def onboard_new_customer(customer_params)
# High level: create customer
customer = Customer.create!(customer_params)
# Low level: SQL for finding default plan
default_plan = Plan.where(active: true)
.where('price_cents > 0')
.order(:price_cents)
.first
# High level: create subscription
subscription = customer.subscriptions.create!(plan: default_plan)
# Low level: date calculation
trial_end = Time.current + 14.days
trial_end = trial_end.end_of_day
trial_end = trial_end.in_time_zone(customer.timezone)
subscription.update!(trial_ends_at: trial_end)
# High level: send welcome
CustomerMailer.welcome(customer).deliver_later
end
After: Consistent abstraction
def onboard_new_customer(customer_params)
customer = create_customer(customer_params)
start_trial_subscription(customer)
send_welcome_email(customer)
customer
end
private
def create_customer(params)
Customer.create!(params)
end
def start_trial_subscription(customer)
plan = Plan.default_starter_plan
trial_end = TrialPeriod.calculate_end_date(customer.timezone)
customer.subscriptions.create!(
plan: plan,
trial_ends_at: trial_end
)
end
def send_welcome_email(customer)
CustomerMailer.welcome(customer).deliver_later
end
React Example
Before: Mixed abstractions in a component
function CheckoutPage() {
const cart = useCart();
// High level
const handleCheckout = async () => {
// Low level: manual localStorage manipulation
const savedAddress = localStorage.getItem('shipping_address');
const address = savedAddress ? JSON.parse(savedAddress) : null;
// Low level: manual API construction
const response = await fetch('/api/orders', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'Authorization': `Bearer ${localStorage.getItem('auth_token')}`,
},
body: JSON.stringify({
items: cart.items.map(i => ({ id: i.productId, qty: i.quantity })),
shipping: address,
}),
});
// High level
if (response.ok) {
cart.clear();
navigate('/confirmation');
}
};
return <CheckoutForm onSubmit={handleCheckout} />;
}
After: Consistent high-level abstraction
function CheckoutPage() {
const cart = useCart();
const { createOrder } = useOrders();
const { shippingAddress } = useShippingAddress();
const handleCheckout = async () => {
const order = await createOrder({
items: cart.items,
shippingAddress,
});
if (order) {
cart.clear();
navigate('/confirmation');
}
};
return <CheckoutForm onSubmit={handleCheckout} />;
}
Use Descriptive Names
Don't be afraid to make a name long. A long descriptive name is better than a short enigmatic name.
The name should describe what the function does. If you struggle to name it, that's a sign it might be doing too much.
Rails Example
Before: Vague names
def process(user)
# What does this process?
end
def handle_data(params)
# Handle how?
end
def do_stuff(order)
# Very helpful...
end
def check(item)
# Check what exactly?
end
After: Names that explain intent
def send_password_reset_email(user)
end
def normalize_address_params(params)
end
def apply_promotional_discount(order)
end
def inventory_sufficient_for?(item)
end
React Example
Before: Unclear names
function handle(e) { }
function update(data) { }
function process(items) { }
function getData() { }
function Component1() { }
After: Self-documenting names
function handleEmailChange(event: ChangeEvent<HTMLInputElement>) { }
function updateUserProfile(profileData: ProfileUpdate) { }
function calculateCartSubtotal(lineItems: CartItem[]) { }
function fetchActiveSubscriptions() { }
function SubscriptionPlanSelector() { }
Function Arguments
The ideal number of arguments is zero. Next comes one, then two. Three arguments should be avoided where possible. More than three requires special justification.
Rails Example
Before: Too many arguments
def create_shipment(order_id, carrier, service_level, weight, dimensions,
signature_required, insurance_amount, saturday_delivery)
# ...
end
# Calling code
create_shipment(
order.id, 'fedex', 'overnight', 2.5, [10, 8, 4],
true, 500.00, false
)
After: Using an argument object
def create_shipment(shipment_request)
carrier = shipment_request.carrier
# ...
end
# With a value object or struct
shipment_request = ShipmentRequest.new(
order: order,
carrier: 'fedex',
service_level: 'overnight',
package: Package.new(weight: 2.5, dimensions: [10, 8, 4]),
options: ShippingOptions.new(
signature_required: true,
insurance_amount: 500.00,
saturday_delivery: false
)
)
create_shipment(shipment_request)
React Example
Before: Props explosion
function ProductCard({
name,
price,
originalPrice,
imageUrl,
rating,
reviewCount,
inStock,
onAddToCart,
onAddToWishlist,
onQuickView,
showRating,
showWishlist,
variant,
}: ProductCardProps) {
// 13 props!
}
After: Grouped into logical objects
interface ProductCardProps {
product: Product;
actions: ProductActions;
display?: DisplayOptions;
}
function ProductCard({ product, actions, display = defaultDisplay }: ProductCardProps) {
const { name, price, imageUrl } = product;
const { onAddToCart, onAddToWishlist } = actions;
const { showRating, variant } = display;
// Much cleaner
}
// Usage
<ProductCard
product={product}
actions={{ onAddToCart, onAddToWishlist, onQuickView }}
display={{ showRating: true, variant: 'compact' }}
/>
Have No Side Effects
Side effects are lies. Your function promises to do one thing, but it also does other hidden things.
Rails Example
Before: Hidden side effect
def authenticate(username, password)
user = User.find_by(username: username)
return false unless user
if user.valid_password?(password)
# Hidden side effect! The method name suggests it only authenticates
session[:user_id] = user.id
user.update!(last_login_at: Time.current)
true
else
false
end
end
After: Explicit about what it does
def authenticate(username, password)
user = User.find_by(username: username)
return nil unless user&.valid_password?(password)
user
end
def sign_in(user)
session[:user_id] = user.id
record_login(user)
end
def record_login(user)
user.update!(last_login_at: Time.current)
end
# Usage is now explicit
if user = authenticate(username, password)
sign_in(user)
redirect_to dashboard_path
end
React Example
Before: Sneaky side effects
function formatCurrency(amount: number): string {
// Side effect: logging
console.log(`Formatting: ${amount}`);
// Side effect: analytics
analytics.track('currency_formatted', { amount });
// Side effect: caching in global state
window.__lastFormattedAmount = amount;
return `$${amount.toFixed(2)}`;
}
After: Pure function
function formatCurrency(amount: number): string {
return `$${amount.toFixed(2)}`;
}
// If you need tracking, make it explicit
function formatAndTrackCurrency(amount: number): string {
analytics.track('currency_formatted', { amount });
return formatCurrency(amount);
}
Command Query Separation
Functions should either do something (command) or answer something (query), but not both.
Rails Example
Before: Mixed command and query
def set_and_return_status(order, new_status)
order.update!(status: new_status)
order.status # Returns something
end
# Confusing usage
if set_and_return_status(order, 'shipped') == 'shipped'
# Did it change? Was it already shipped?
end
After: Separate command and query
# Command: changes state, returns nothing meaningful
def update_status(order, new_status)
order.update!(status: new_status)
end
# Query: returns information, changes nothing
def current_status(order)
order.status
end
# Clear usage
update_status(order, 'shipped')
if current_status(order) == 'shipped'
notify_customer(order)
end
React Example
Before: Mutation returns value
function toggleAndGetVisibility(): boolean {
setIsVisible(prev => !prev);
return !isVisible; // This might not be what you expect due to async state
}
After: Separated
// Command
function toggleVisibility(): void {
setIsVisible(prev => !prev);
}
// Query (derived state)
const isCurrentlyVisible = isVisible;
// Or use a callback pattern if you need the new value
function toggleVisibility(onToggled?: (newValue: boolean) => void): void {
setIsVisible(prev => {
const newValue = !prev;
onToggled?.(newValue);
return newValue;
});
}
Prefer Exceptions to Returning Error Codes
Returning error codes means the caller must deal with the error immediately. Exceptions let you separate the happy path from error handling.
Rails Example
Before: Error codes
def create_account(params)
return :invalid_email unless valid_email?(params[:email])
return :email_taken if User.exists?(email: params[:email])
return :weak_password unless strong_password?(params[:password])
user = User.create!(params)
:success
end
# Calling code becomes a mess
result = create_account(params)
case result
when :success then redirect_to dashboard_path
when :invalid_email then flash[:error] = "Invalid email"
when :email_taken then flash[:error] = "Email already registered"
when :weak_password then flash[:error] = "Password too weak"
end
After: Exceptions
def create_account(params)
validate_email!(params[:email])
ensure_email_available!(params[:email])
validate_password_strength!(params[:password])
User.create!(params)
end
# Clean calling code
begin
create_account(params)
redirect_to dashboard_path
rescue InvalidEmailError => e
flash[:error] = e.message
render :new
rescue EmailTakenError => e
flash[:error] = "Email already registered"
render :new
rescue WeakPasswordError => e
flash[:error] = e.message
render :new
end
React/TypeScript Example
Before: Error returns
type Result = { success: true; data: User } | { success: false; error: string };
async function fetchUser(id: string): Promise<Result> {
try {
const response = await api.get(`/users/${id}`);
return { success: true, data: response.data };
} catch {
return { success: false, error: 'Failed to fetch user' };
}
}
// Awkward usage
const result = await fetchUser(id);
if (result.success) {
setUser(result.data);
} else {
setError(result.error);
}
After: Let exceptions flow (with proper boundaries)
async function fetchUser(id: string): Promise<User> {
const response = await api.get(`/users/${id}`);
return response.data;
}
// With an error boundary or try/catch at the appropriate level
function UserProfile({ userId }: { userId: string }) {
const { data: user, error, isLoading } = useQuery(
['user', userId],
() => fetchUser(userId)
);
if (error) return <ErrorDisplay error={error} />;
if (isLoading) return <Spinner />;
return <ProfileCard user={user} />;
}
Don't Repeat Yourself (DRY)
Duplication is the root of all evil in software. Every piece of knowledge should have a single, unambiguous representation in the system.
Rails Example
Before: Duplicated logic
class OrdersController < ApplicationController
def create
@order = Order.new(order_params)
# Calculate total
subtotal = @order.line_items.sum { |i| i.price * i.quantity }
discount = @order.coupon&.calculate_discount(subtotal) || 0
tax = (subtotal - discount) * 0.08
@order.total = subtotal - discount + tax
@order.save!
end
end
class Order < ApplicationRecord
def recalculate_total
# Same logic repeated!
subtotal = line_items.sum { |i| i.price * i.quantity }
discount = coupon&.calculate_discount(subtotal) || 0
tax = (subtotal - discount) * 0.08
self.total = subtotal - discount + tax
save!
end
end
After: Single source of truth
class OrderTotalCalculator
def initialize(order)
@order = order
end
def calculate
subtotal - discount + tax
end
def subtotal
@order.line_items.sum { |i| i.price * i.quantity }
end
def discount
@order.coupon&.calculate_discount(subtotal) || 0
end
def tax
(subtotal - discount) * TAX_RATE
end
private
TAX_RATE = 0.08
end
# Used everywhere
@order.total = OrderTotalCalculator.new(@order).calculate
React Example
Before: Copy-pasted validation
function RegistrationForm() {
const validateEmail = (email: string) => {
const regex = /^[^\s@]+@[^\s@]+\.[^\s@]+$/;
return regex.test(email);
};
// ...
}
function ProfileForm() {
const validateEmail = (email: string) => {
const regex = /^[^\s@]+@[^\s@]+\.[^\s@]+$/;
return regex.test(email);
};
// ...
}
function InviteForm() {
const validateEmail = (email: string) => {
const regex = /^[^\s@]+@[^\s@]+\.[^\s@]+$/;
return regex.test(email);
};
// ...
}
After: Shared utility
// utils/validation.ts
export function isValidEmail(email: string): boolean {
const EMAIL_REGEX = /^[^\s@]+@[^\s@]+\.[^\s@]+$/;
return EMAIL_REGEX.test(email);
}
// Or as a custom hook for form integration
export function useEmailValidation() {
const validate = useCallback((email: string) => {
if (!email) return 'Email is required';
if (!isValidEmail(email)) return 'Invalid email format';
return undefined;
}, []);
return { validate };
}
Conclusion
Martin's principles for writing clean functions are timeless. Whether you're building Rails APIs or React interfaces, the rules remain the same:
- Keep functions small and focused
- Make them do one thing well
- Maintain consistent abstraction levels
- Choose names that reveal intent
- Minimize arguments
- Avoid side effects
- Separate commands from queries
- Use exceptions over error codes
- Eliminate duplication
The goal isn't to follow these rules dogmatically, but to write code that communicates clearly. When your functions are small, well-named, and focused, your codebase becomes a joy to work in rather than a chore to maintain.
This is part of a series on Clean Code principles with Rails and React examples. See also: Chapter 1: Clean Code and Chapter 2: Meaningful Names.
Friday, December 26, 2025
The Five Dysfunctions of Software Teams, Part 1: Absence of Trust
The Five Dysfunctions of Software Teams, Part 1: Absence of Trust
This is the first post in a six-part series exploring The Five Dysfunctions of a Team through the lens of modern software engineering.
I recently read The Five Dysfunctions of a Team because a company I interviewed with said they base their culture on it. I was curious whether it would feel like generic leadership advice or something that actually mapped to real work.
It resonated with me more than I expected, especially as an individual contributor.
Not because the ideas were flashy or new, but because they described patterns I have seen repeatedly in engineering organizations that otherwise look healthy. Smart people. Reasonable processes. Solid intentions. And still, things quietly break down.
The first dysfunction, absence of trust, sits at the base of Lencioni’s model. If it is present, everything above it struggles. In software teams, it often shows up in subtle, normalized ways.
What lack of trust looks like in engineering
On software teams, lack of trust rarely looks like open hostility. It looks like:
-
Engineers avoiding areas of the codebase they do not “own”
-
Over-reliance on one or two people who “know how it works”
-
Pull requests that get approved without meaningful review
-
Bugs fixed in isolation instead of discussed in the open
-
Retrospectives that stay shallow and polite
None of this feels dramatic. That is why it is so dangerous.
How this breaks agile in practice
Agile assumes trust. Not as a nice-to-have, but as a prerequisite.
Consider what agile asks teams to do:
-
Share unfinished work early
-
Inspect and adapt frequently
-
Surface blockers quickly
-
Learn from failure without blame
Without trust, those practices turn into rituals instead of tools.
Daily standups become status reporting instead of problem solving.
Sprint reviews show only safe, polished work.
Retrospectives avoid the real issues because no one wants to look incompetent or difficult.
The process keeps running, but the learning stops.
The myth of the “strong IC”
As individual contributors, many of us learned that being good means being self-sufficient. You debug alone. You figure it out. You do not slow others down with questions.
That mindset feels professional, but it creates brittle teams.
When trust is low:
-
Knowledge stays siloed
-
Onboarding takes forever
-
Bus factor drops to one or two people
-
The team cannot respond well to change
Ironically, the more everyone tries to look strong individually, the weaker the team becomes.
Trust is built through small, visible behaviors
Trust on engineering teams is not built through offsites or trust exercises. It is built in the work.
From an IC perspective, that looks like:
-
Asking questions early, especially basic ones
-
Narrating your thinking in pull requests
-
Admitting when you broke something, quickly and publicly
-
Pairing or mobbing on risky changes
-
Writing down what you learn instead of keeping it in your head
These actions feel vulnerable, especially in cultures that reward speed and certainty. But they are exactly what allow agile practices to work as intended.
Blamelessness is not about being nice
Blameless postmortems are often misunderstood as being soft. They are not.
They are about shifting focus from “who messed up” to “how did the system allow this to happen.”
When teams trust each other:
-
Incidents become learning opportunities
-
Engineers speak honestly about near-misses
-
Fixes address root causes, not just symptoms
Without trust, postmortems become performative or avoided entirely. The same failures repeat under new names.
A practical takeaway for ICs
You do not need to be a manager to improve trust on your team.
Pick one behavior and practice it consistently:
-
Ask the question you think you should already know
-
Say “I do not understand this yet” in a design discussion
-
Call out uncertainty instead of masking it with confidence
Agile is not about moving fast. It is about learning fast.
Learning fast requires trust.
And trust starts with individual contributors being willing to be seen as human.
Up next: Part 2 will look at Fear of Conflict, and how avoiding disagreement in design reviews and architectural discussions quietly erodes software quality.
Series note:
This post is part of a six-part series applying The Five Dysfunctions of a Team to software engineering, with a focus on how these patterns show up in day-to-day work for individual contributors.
If this resonated, the next post explores Fear of Conflict and how avoiding disagreement in design reviews, pull requests, and architectural decisions quietly degrades code quality and team health.
You do not need to be a manager to influence any of this. You just need to notice the patterns and decide how you want to show up in them.
Thursday, December 25, 2025
The Art of Naming: Chapter 2 of Clean Code
The Art of Naming: Chapter 2 of Clean Code
After establishing why clean code matters in Chapter 1, Robert C. Martin dives into one of the most fundamental skills in programming: choosing good names. Chapter 2, "Meaningful Names," might seem simple at first, but it contains wisdom that separates amateur code from professional craftsmanship.
Names Are Everywhere
Before we get into the rules, consider this: names are everywhere in software. We name variables, functions, arguments, classes, packages, source files, and directories. We name and rename constantly. Given how much naming we do, we might as well do it well.
Use Intention-Revealing Names
The name of a variable, function, or class should answer three big questions: why it exists, what it does, and how it's used. If a name requires a comment to explain it, the name doesn't reveal its intent.
Consider this example in Ruby:
d = 10 # elapsed time in daysVersus:
elapsed_time_in_days = 10Or in TypeScript:
const d: number = 10; // elapsed time in daysVersus:
const elapsedTimeInDays: number = 10;The difference seems trivial, but it compounds across thousands of lines of code. Good names make code self-documenting.
Avoid Disinformation
Programmers must avoid leaving false clues that obscure the meaning of code. Don't refer to a grouping of accounts as account_list unless it's actually a List or Array. If it's not, account_group or just accounts would be better.
# Misleading - not actually an array
account_list = Account.where(active: true)
# Better - accurately describes what it is
accounts = Account.where(active: true)// Misleading - this is a Set, not an Array
const accountList: Set<Account> = new Set(activeAccounts);
// Better
const accountSet: Set<Account> = new Set(activeAccounts);Beware of names that vary in small ways. How quickly can you spot the difference between XYZControllerForEfficientHandlingOfStrings and XYZControllerForEfficientStorageOfStrings? These similar names create cognitive load and opportunities for bugs.
Make Meaningful Distinctions
If you have two things that need different names, make sure the names actually convey different meanings. Number-series naming (a1, a2, a3) is the opposite of intentional naming. So is noise words.
What's the difference between ProductInfo and ProductData? Between Customer and CustomerObject? These distinctions are meaningless. Noise words like Info, Data, Object, Manager, Processor don't add clarity, they just add clutter.
# Meaningless distinction
class ProductInfo
end
class ProductData
end
# Better - use one clear name
class Product
end// Noise words that add no meaning
interface CustomerObject {
name: string;
}
class CustomerManager {
// What does "Manager" actually do here?
}
// Better - clear and direct
interface Customer {
name: string;
}
class CustomerRepository {
// "Repository" is a known pattern
}Use Pronounceable Names
This might seem obvious, but it makes a huge difference. If you can't pronounce a name, you can't discuss it without sounding like an idiot.
Compare:
genymdhms = Time.nowWith:
generation_timestamp = Time.nowOr in TypeScript:
const genymdhms: Date = new Date();Versus:
const generationTimestamp: Date = new Date();Which one can you actually say out loud to a teammate?
Use Searchable Names
Single-letter names and numeric constants have a particular problem: they're nearly impossible to search for. If you're using e as a variable name, try searching for it in a large codebase. Good luck.
# Hard to search for
users.select { |u| u.age > 5 }
# Better - searchable and meaningful
MIN_ADULT_AGE = 18
users.select { |user| user.age > MIN_ADULT_AGE }// Hard to search for
const filtered = users.filter(u => u.age > 5);
// Better
const MIN_ADULT_AGE = 18;
const adultUsers = users.filter(user => user.age > MIN_ADULT_AGE);Martin suggests that the length of a name should correspond to the size of its scope. If a variable is only used in a small loop, i might be fine. But if it has a larger scope, it needs a more descriptive name.
Avoid Mental Mapping
Readers shouldn't have to mentally translate your names into other names they already know. A single-letter variable name is fine for a loop counter, but using r for the "lowercase version of a URL with the host and scheme removed" forces readers to keep a mental map.
# Forces mental mapping
r = url.downcase.gsub(/^https?:\/\/[^\/]+/, '')
# Clear and direct
normalized_path = url.downcase.gsub(/^https?:\/\/[^\/]+/, '')Smart programmers write code that others can understand. Professional programmers write clarity.
Class Names and Method Names
Martin provides clear guidance here:
Classes and objects should have noun or noun phrase names like Customer, WikiPage, Account, or AddressParser. Avoid words like Manager, Processor, Data, or Info in class names. A class name should not be a verb.
# Good class names
class Customer
end
class OrderProcessor # Sometimes "Processor" is acceptable if it truly processes
end
class PaymentGateway
end// Good class names
class Customer {
}
class InvoiceGenerator {
}
interface UserProfile {
}Methods should have verb or verb phrase names like post_payment, delete_page, or save. In Ruby, follow convention with snake_case for methods. In TypeScript, use camelCase.
# Good method names
def post_payment
end
def delete_page
end
def calculate_total
end
# Accessors and predicates
def active?
end
def total
end
def total=(value)
end// Good method names
function postPayment(): void {
}
function deletePage(): void {
}
function calculateTotal(): number {
}
// Accessors and predicates
function isActive(): boolean {
}
function getTotal(): number {
}
function setTotal(value: number): void {
}Pick One Word Per Concept
Pick one word for one abstract concept and stick with it. It's confusing to have fetch, retrieve, and get as equivalent methods in different classes. Choose one and use it consistently.
# Inconsistent - pick one!
class UserRepository
def fetch_by_id(id)
end
end
class OrderRepository
def retrieve_by_id(id)
end
end
class ProductRepository
def get_by_id(id)
end
end
# Better - consistent vocabulary
class UserRepository
def find_by_id(id)
end
end
class OrderRepository
def find_by_id(id)
end
end
class ProductRepository
def find_by_id(id)
end
endSimilarly, don't use the same word for two purposes. If you have add methods that create a new value by adding two values, don't use add for a method that puts a single value into a collection. Use append or push instead.
# Confusing - "add" used for different purposes
def add(a, b)
a + b
end
def add(item)
@items << item
end
# Better - distinct names for distinct operations
def sum(a, b)
a + b
end
def append(item)
@items << item
endUse Solution Domain Names
Remember that the people reading your code are programmers. Go ahead and use computer science terms, algorithm names, pattern names, math terms. The name AccountVisitor means something to a programmer familiar with the Visitor pattern. Use technical names when appropriate.
class OrderDecorator
# "Decorator" is a known pattern
end
class UserFactory
# "Factory" is a known pattern
end
class EventObserver
# "Observer" is a known pattern
endclass CacheStrategy {
// "Strategy" is a known pattern
}
class DatabaseAdapter {
// "Adapter" is a known pattern
}
class CommandQueue {
// "Queue" is a known data structure
}Use Problem Domain Names
When there's no programmer-ese for what you're doing, use the name from the problem domain. At least the programmer who maintains your code can ask a domain expert what it means.
# Healthcare domain
class PatientAdmission
end
class DiagnosisCode
end
# Financial domain
class LedgerEntry
end
class ReconciliationReport
endAdd Meaningful Context
Imagine you see variables named first_name, last_name, street, city, state, and zipcode. You can infer they're part of an address. But what if you just see the variable state in a method? Adding context helps: addr_state is better, but creating an Address class is best.
# Context through grouping
class Address
attr_accessor :street, :city, :state, :zipcode
end
# Now it's clear what "state" means
address = Address.new
address.state = "MN"// Context through typing
interface Address {
street: string;
city: string;
state: string;
zipcode: string;
}
// Clear context
const userAddress: Address = {
street: "123 Main St",
city: "Minneapolis",
state: "MN",
zipcode: "55401"
};Don't add gratuitous context though. If you're building a "Gas Station Deluxe" application, prefixing every class with GSD is overkill. Shorter names are generally better than longer ones, as long as they're clear.
The Hardest Thing in Programming
Phil Karlton famously said there are only two hard things in Computer Science: cache invalidation and naming things. Chapter 2 of Clean Code won't make naming easy, but it provides a framework for making better naming decisions.
Key Takeaways
- Choose names that reveal intent and make code self-documenting
- Avoid misleading names and meaningless distinctions
- Make names pronounceable and searchable
- Use consistent vocabulary throughout your codebase
- Class names should be nouns, method names should be verbs
- Pick one word per concept and stick with it
- Use technical terms when appropriate, domain terms when not
- Add context through class structure, not prefixes
Practical Application
The next time you write code, pause before naming something. Ask yourself: will another developer (or future you) understand what this is without reading the implementation? If the answer is no, take a moment to find a better name. It's an investment that pays dividends every time someone reads that code.
What naming conventions have you found most helpful in your projects? Share your thoughts below!
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