Challenges When Designing Reusable Classes

“Code reuse” is often framed as just subclass and override. In practice, reuse fails when classes are tightly coupled to concrete implementations, hidden assumptions, or a single workflow. The GoF patterns offer proven ways to separate roles from implementations and to compose behavior flexibly in languages like Java and C++.

Why Reuse Is Hard (and Common Failure Modes)

• Context coupling: Classes hard-wire environment details (I/O, threads, clock, DB) instead of accepting them as dependencies.
• Inheritance overuse: Deep hierarchies encode variability in type trees; small requirement shifts ripple through many subclasses.
• Leaky abstractions: Public APIs expose internal state/format, preventing safe changes.
• Rigid construction: Callers can’t swap strategies, policies, or collaborators at runtime.
• Insufficient contracts: No clear pre/postconditions or invariants; reuse breaks on edge cases.
• Portability and versioning: Platform/compiler differences and API changes without clear deprecation paths.
• Concurrency surprises: Shared mutable state without thread-safety guidance or immutability.

How Design Patterns Help

Patterns make variation explicit and localize change:

• Strategy / State: Encapsulate algorithms or modes behind interfaces; switch behavior without subclass explosion.
• Factory Method / Abstract Factory: Create families of related objects without binding to concrete classes.
• Adapter / Facade: Decouple your API from legacy or complex subsystems while keeping a clean surface.
• Decorator / Composite: Compose behavior and structure at runtime instead of hardcoding cases.
• Iterator / Observer: Separate traversal and notification from the subjects they operate on.

A Practical OO Workflow for Reusable Designs

1. Capture use cases and variability: Identify actors, responsibilities, and where behavior must vary.
2. Define interfaces first: Model roles and contracts (preconditions, postconditions, invariants) before picking classes.
3. Prefer composition: Inject collaborators (strategies, policies, data sources) via constructors or setters.
4. Prototype, then refactor with patterns: Build a simple, working slice; refactor hotspots into patterns as variability emerges.
5. Stabilize APIs: Add tests, examples, and deprecation notes; document thread-safety and error semantics.

Abstract Data Types, Interfaces, and Contracts

An Abstract Data Type (ADT) defines what you can do-its operations and guarantees-without exposing how it’s implemented. Classes (Java/C++) are a common way to implement ADTs: keep representation private, expose a minimal, coherent set of operations, and enforce invariants through method contracts.

Mini Examples: ADT + Contracts

Java - a minimal Stack ADT (composition-friendly, no leaks of representation):

// Pre: element != null
// Post: size() == oldSize + 1
public interface Stack<T> {
  void push(T element);
  // Pre: !isEmpty()
  // Post: returns last pushed element; size() == oldSize - 1
  T pop();
  T peek();      // Pre: !isEmpty()
  boolean isEmpty();
  int size();
}

C++ - strong RAII and clear ownership (no exposure of internals):

class IntStack {
public:
  void push(int v);              // pre: true; post: size == old_size + 1
  int  pop();                    // pre: size > 0; post: size == old_size - 1
  int  top() const;              // pre: size > 0
  bool empty() const noexcept;
  std::size_t size() const noexcept;

private:
  std::vector<int> data_;       // representation hidden (ADT boundary)
};

Checklist: Making a Class Reusable

• Small, coherent API: Names reflect behavior; no representation leaks.
• Composition first: Inject policies/strategies; avoid subclass-only extension.
• Clear contracts: Pre/postconditions, invariants, error semantics, and edge cases.
• Thread-safety notes: Immutable by default or documented synchronization policy.
• Dependency boundaries: Abstract I/O, time, and external services behind interfaces.
• Tests and examples: Unit tests cover behavior; provide minimal usage snippets.
• Versioning: Semantic versioning, deprecations, and migration notes.
• Docs that scale: One-page overview + reference; link to relevant GoF patterns.