Yes, it's possible to generate guaranteed solvable Minesweeper boards. This is an important feature for ensuring a fair and enjoyable player experience. Let's explore how we can modify our current implementation to achieve this.
The main challenge in generating a solvable Minesweeper board is ensuring that the player never has to guess. Every move should be logically deducible from the information available on the board.
To generate a solvable board, we can use a combination of techniques:
Let's implement a simple version of this approach:
#include <algorithm>
#include <iostream>
#include <random>
#include <vector>
class MinesweeperBoard {
public:
MinesweeperBoard(int rows, int cols,
int mines) :
rows{rows},
cols{cols}, mineCount{mines},
board(rows, std::vector<int>(cols, 0)) {}
void generateSolvableBoard(int startRow,
int startCol) {
// Clear the 3x3 area around the first click
for (int i = std::max(0, startRow - 1);
i <= std::min(rows - 1, startRow + 1);
++i) {
for (int j = std::max(0, startCol - 1);
j <=
std::min(cols - 1, startCol + 1);
++j) {
board[i][j] = -1; // Mark as safe
}
}
// Place mines randomly on the remaining
// cells
std::vector<std::pair<int, int>>
availableCells;
for (int i = 0; i < rows; ++i) {
for (int j = 0; j < cols; ++j) {
if (board[i][j] != -1) {
availableCells.emplace_back(i, j);
}
}
}
std::random_device rd;
std::mt19937 g(rd());
std::shuffle(availableCells.begin(),
availableCells.end(), g);
for (int i = 0; i < mineCount &&
i < availableCells.size();
++i) {
auto [row, col] = availableCells[i];
board[row][col] =
9; // 9 represents a mine
}
// Calculate adjacent mine counts
for (int i = 0; i < rows; ++i) {
for (int j = 0; j < cols; ++j) {
if (board[i][j] != 9) {
board[i][j] =
countAdjacentMines(i, j);
}
}
}
}
void printBoard() {
for (const auto &row : board) {
for (int cell : row) {
if (cell == 9) {
std::cout << "* ";
} else {
std::cout << cell << " ";
}
}
std::cout << "\n";
}
}
private:
int rows, cols, mineCount;
std::vector<std::vector<int>> board;
int countAdjacentMines(int row, int col) {
int count = 0;
for (int i = std::max(0, row - 1);
i <= std::min(rows - 1, row + 1);
++i) {
for (int j = std::max(0, col - 1);
j <= std::min(cols - 1, col + 1);
++j) {
if (board[i][j] == 9) { ++count; }
}
}
return count;
}
};
int main() {
MinesweeperBoard board(8, 8, 10);
// Assume first click at (3,3)
board.generateSolvableBoard(3, 3);
board.printBoard();
}
This implementation ensures that the first click and its surrounding cells are safe, which gives the player a good starting point. However, this doesn't guarantee full solvability for complex boards.
For a more robust solution, you'd need to implement a solver algorithm and regenerate the board if it's not solvable.
Remember, generating perfectly solvable boards can be computationally expensive, especially for larger grids. You might need to balance between generation time and perfect solvability based on your game's requirements.
Answers to questions are automatically generated and may not have been reviewed.
Implement the techniques for detecting nearby bombs and clearing empty cells automatically.