GOF Strategy Pattern

GOF Strategy Pattern

Encapsulate interchangeable algorithms behind a common interface for runtime selection.

When to Use

• You have multiple algorithms that do the same job but differently (sorting, pricing, routing, formatting)
• You want to switch algorithms at runtime without changing the client
• You're eliminating large if/else chains where each branch implements a different algorithm
• You want algorithms to be testable in isolation from the context that uses them

Instructions

Interface + concrete strategies:

// Strategy interface
interface PricingStrategy {
  calculate(basePrice: number, quantity: number, customer: Customer): number;
}

// Concrete strategies
class StandardPricing implements PricingStrategy {
  calculate(basePrice: number, quantity: number): number {
    return basePrice * quantity;
  }
}

class BulkDiscountPricing implements PricingStrategy {
  constructor(
    private readonly threshold: number,
    private readonly discount: number
  ) {}

  calculate(basePrice: number, quantity: number): number {
    if (quantity >= this.threshold) {
      return basePrice * quantity * (1 - this.discount);
    }
    return basePrice * quantity;
  }
}

class MemberPricing implements PricingStrategy {
  calculate(basePrice: number, quantity: number, customer: Customer): number {
    const rate = customer.memberTier === 'gold' ? 0.8 : 0.9;
    return basePrice * quantity * rate;
  }
}

// Context — uses a strategy
class ShoppingCart {
  private strategy: PricingStrategy = new StandardPricing();
  private items: { name: string; price: number; qty: number }[] = [];

  setStrategy(strategy: PricingStrategy): void {
    this.strategy = strategy;
  }

  addItem(name: string, price: number, qty: number): void {
    this.items.push({ name, price, qty });
  }

  calculateTotal(customer: Customer): number {
    return this.items.reduce((total, item) => {
      return total + this.strategy.calculate(item.price, item.qty, customer);
    }, 0);
  }
}

// Runtime selection
const cart = new ShoppingCart();
cart.addItem('Widget', 10.0, 5);

const customer: Customer = { id: 'u1', memberTier: 'gold' };

// Default
console.log(cart.calculateTotal(customer)); // 50.00

// Switch to member pricing
cart.setStrategy(new MemberPricing());
console.log(cart.calculateTotal(customer)); // 40.00

// Switch to bulk discount (20% off 10+)
cart.setStrategy(new BulkDiscountPricing(10, 0.2));
cart.addItem('Widget', 10.0, 6); // now 11 total
console.log(cart.calculateTotal(customer)); // 88.00 (20% off all)

Function-based strategies (TypeScript idiomatic — skip the class):

type SortStrategy<T> = (a: T, b: T) => number;

const sortByName: SortStrategy<{ name: string }> = (a, b) => a.name.localeCompare(b.name);

const sortByDate: SortStrategy<{ createdAt: Date }> = (a, b) =>
  a.createdAt.getTime() - b.createdAt.getTime();

const sortByScore: SortStrategy<{ score: number }> = (a, b) => b.score - a.score; // descending

function sortItems<T>(items: T[], strategy: SortStrategy<T>): T[] {
  return [...items].sort(strategy);
}

// No strategy objects needed — functions are the strategies
const sortedByName = sortItems(users, sortByName);
const sortedByDate = sortItems(users, sortByDate);

Strategy map for configuration-driven selection:

type CompressionType = 'gzip' | 'brotli' | 'zstd' | 'none';

interface Compressor {
  compress(data: Buffer): Promise<Buffer>;
  decompress(data: Buffer): Promise<Buffer>;
}

const compressionStrategies: Record<CompressionType, Compressor> = {
  gzip: new GzipCompressor(),
  brotli: new BrotliCompressor(),
  zstd: new ZstdCompressor(),
  none: new NoopCompressor(),
};

function getCompressor(type: CompressionType): Compressor {
  return compressionStrategies[type];
}

const compressor = getCompressor((process.env.COMPRESSION_TYPE as CompressionType) ?? 'gzip');
const compressed = await compressor.compress(data);

Details

Strategy vs. State: Both use polymorphism to replace conditionals. Strategy: the algorithm is chosen externally and remains stable during execution. State: the context transitions between states internally. Ask "who decides when to switch?" — external caller → Strategy, object itself → State.

Strategy vs. Template Method: Template Method uses inheritance — the base class defines the algorithm skeleton and subclasses fill in steps. Strategy uses composition — the algorithm is injected. Prefer Strategy (composition) over Template Method (inheritance) in modern TypeScript.

Anti-patterns:

• Strategy that needs to access private context state — if it needs too much context data, consider making it a method on the context instead
• Context that exposes its internals specifically for strategies — the strategy interface should only receive what it needs to do its job
• One-off strategies that are never swapped — if you'll never switch the algorithm, don't introduce the indirection

Testing strategies: Each strategy can be tested in isolation without a context:

describe('BulkDiscountPricing', () => {
  const strategy = new BulkDiscountPricing(10, 0.2);
  it('applies discount when quantity >= threshold', () => {
    expect(strategy.calculate(10, 10, mockCustomer)).toBe(80);
  });
  it('does not apply discount below threshold', () => {
    expect(strategy.calculate(10, 9, mockCustomer)).toBe(90);
  });
});

Source

refactoring.guru/design-patterns/strategy

Process

1. Read the instructions and examples in this document.
2. Apply the patterns to your implementation, adapting to your specific context.
3. Verify your implementation against the details and edge cases listed above.

Harness Integration

• Type: knowledge — this skill is a reference document, not a procedural workflow.
• No tools or state — consumed as context by other skills and agents.

Success Criteria

• The patterns described in this document are applied correctly in the implementation.
• Edge cases and anti-patterns listed in this document are avoided.