System Design (LLD): Build Snake and Ladder Game

Comprehensive Low-Level Design (LLD) study notes for architecting a scalable, extensible Snake and Ladder game using object-oriented principles, design patterns (Strategy, Factory, Observer), and top-down UML modeling.

1. Problem Statement & Functional Requirements

Before diving into class structures and UML diagrams, we must establish clear requirements. Designing a game like Snake and Ladder requires scalability, adherence to standard game rules, and high extensibility for future rule changes or custom board configurations.

• Scalable Board Size: The board must not be hardcoded to a standard $10^2$ grid. It should support customizable dimensions ($N \times M$ or $N \times N$).
• Standard & Extensible Rules: The game must support standard rules out-of-the-box, while allowing developers to plug in custom rule strategies.
• Configurable Game Setup Strategies:
  • Standard Setup: Uses classic, predefined snake and ladder positions.
  • Random Setup: Dynamically populates snakes and ladders based on configurable difficulty levels (Easy, Medium, Hard).
  • Custom Setup: Allows players or clients to specify exact counts, or fully customize the start and end coordinates of every snake and ladder.
• In-App Notifications: Support asynchronous notifications (e.g., Console Notifier) to alert players of moves, dice rolls, snake bites, ladder climbs, and win conditions.

2. Core Mental Model & The 1D vs 2D Reality

Real-Life Analogy: The Flattened Board

Note: Although a Snake and Ladder board is visually rendered on a 2D grid (e.g., $10 \times 10$ matrix zigzagging from cell 1 to 100), backend memory does not require a 2D matrix.

A 2D array or matrix representation introduces unnecessary spatial complexity. Instead, the board can be modeled as a 1D sequence of cells from $1$ to $N$. Going one step further, we don't even need a full 1D array allocated in memory.

To optimize space:

1. We only store an integer representing the board size (e.g., 100).
2. We maintain a hash map (Map<Integer, BoardEntity>) to instantly look up whether a specific cell houses a snake head or a ladder bottom in $O(1)$ time.
3. Each Player object simply holds an integer representing their current cell position.

3. Top-Down Design Approach & Architectural Overview

Following premier system design practices, we adopt a Top-Down Approach:

1. Identify the largest orchestration object (Game).
2. Deconstruct it into primary subsystems (Board, Dice, Player, RuleStrategy, Observer).
3. Deconstruct those subsystems into smaller domain entities (BoardEntity, Snake, Ladder, SetupStrategy).

4. Board & Entity Hierarchy (BoardEntity, Snake, Ladder)

Snakes and ladders perform inverse actions, but they share the exact same structural behavior: they move a player from a starting cell to an ending cell. Therefore, we group them under a common parent abstraction called BoardEntity.

Realistic Code Evolution: Decoupling Board Entities

Naive Approach (Tight Coupling)

// Bad: Hardcoding snake and ladder logic directly inside the Board class
class Board {
    vector<int> snakeHeads;
    vector<int> snakeTails;
    vector<int> ladderBottoms;
    vector<int> ladderTops;
    // Messy validation checks mixed into board management
};

Production-Ready Approach (Open-Closed Principle)

// Clean: Abstract base entity with validated subclasses
class BoardEntity {
protected:
    int start;
    int end;
public:
    BoardEntity(int s, int e) : start(s), end(e) {}
    virtual ~BoardEntity() {}
    int getStart() const { return start; }
    int getEnd() const { return end; }
    virtual string getName() const = 0;
};

class Snake : public BoardEntity {
public:
    Snake(int head, int tail) : BoardEntity(head, tail) {
        if (tail >= head) {
            throw invalid_argument("Invalid Snake: Tail must be below head.");
        }
    }
    string getName() const override { return "Snake"; }
};

class Ladder : public BoardEntity {
public:
    Ladder(int bottom, int top) : BoardEntity(bottom, top) {
        if (top <= bottom) {
            throw invalid_argument("Invalid Ladder: Top must be above bottom.");
        }
    }
    string getName() const override { return "Ladder"; }
};

5. Board Setup Strategies (SetupStrategy Pattern)

Different games require different board setups. To adhere to the Strategy Design Pattern, we extract board generation algorithms into distinct strategy classes.

Strategy Comparison Table

6. Rules & Validation Engine (RuleStrategy)

The Board is a "dumb object"—its sole responsibility is managing cells, entities, and sizes. It knows nothing about winning conditions, turn validity, or dice mechanics. Game rules are isolated inside a dedicated RuleStrategy interface.

class RuleStrategy {
public:
    virtual ~RuleStrategy() {}
    virtual bool isValidMove(int currentPos, int diceValue, int boardSize) = 0;
    virtual int calculateNewPosition(int currentPos, int diceValue, Board* board) = 0;
    virtual bool checkWinCondition(int currentPos, int boardSize) = 0;
};

class StandardSnakeAndLadderRules : public RuleStrategy {
public:
    bool isValidMove(int currentPos, int diceValue, int boardSize) override {
        // Player cannot exceed the exact winning cell
        return (currentPos + diceValue) <= boardSize;
    }

    int calculateNewPosition(int currentPos, int diceValue, Board* board) override {
        int intermediatePos = currentPos + diceValue;
        BoardEntity* entity = board->getEntity(intermediatePos);
        
        if (entity != nullptr) {
            // Landed on a Snake head or Ladder bottom -> transition to end
            return entity->getEnd();
        }
        return intermediatePos;
    }

    bool checkWinCondition(int currentPos, int boardSize) override {
        return currentPos == boardSize;
    }
};

7. Game Factory Pattern (GameFactory)

To encapsulate complex instantiation logic (initializing board sizes, rules, dice, and setup strategies), we implement the Factory Design Pattern.

class GameFactory {
public:
    static Game* createStandardGame() {
        Board* board = new Board(100);
        BoardSetupStrategy* strategy = new StandardBoardSetupStrategy();
        board->setupBoard(strategy);
        Dice* dice = new Dice(6);
        return new Game(board, dice);
    }

    static Game* createRandomGame(int boardSize, Difficulty diff) {
        Board* board = new Board(boardSize);
        BoardSetupStrategy* strategy = new RandomBoardSetupStrategy(diff);
        board->setupBoard(strategy);
        Dice* dice = new Dice(6);
        return new Game(board, dice);
    }
};

8. Complete Game Loop & Execution Flow

The orchestration flow runs inside the Game::play() method, looping continuously through player turns until a winner is determined.

9. Summary and Key Takeaways

• Top-Down Modeling: Always start by designing top-level orchestrators (Game, Board) before drilling down into granular components (BoardEntity, Dice, Player).
• Separation of Concerns (SoC): Keep the Board class dumb (data management only) and delegate game physics and logic to RuleStrategy.
• Strategy Pattern Flexibility: Use BoardSetupStrategy to effortlessly switch between standard, random (difficulty-based), and custom board configurations without modifying core classes.
• 1D Map Optimization: Avoid unnecessary 2D grid allocations in backend memory; represent the board as a 1D range with an $O(1)$ hash map lookup for snakes and ladders.
• Observer Pattern for Notifications: Decouple print/logging mechanisms from game logic by broadcasting state changes through an IObserver interface.
• Extensibility: Adding new game variants (e.g., multiple dice, custom win constraints) requires zero modifications to existing classes thanks to interface-driven design.