Hello, and welcome, code explorer! Today's journey takes us through the intricate paths within a 2-dimensional array, often likened to a game board. Our mission is to identify ideal spots for game piece placement. Sounds like an adventure, doesn't it? Let's embark!
Visualize a chessboard in the form of a 2D array, where each cell could be marked E
for empty or P
for a piece. Our quest involves summoning a Java function named findPositions()
. Upon examining this 2D array, this function identifies all the spots where a new piece could be placed so that it can move to another empty cell in one move. The catch is that a piece can move only to an immediately neighboring cell directly above, below, to the left, or right, but not diagonally.
Consider this 4x4 board, for instance:
1P E E P 2E P E P 3P E P P 4P E P E
The function should output the following pairs representing positions: (0, 1), (0, 2), (1, 2), (2, 1), (3, 1)
. This output represents the positions where a new piece can fit perfectly and then be able to move in the next turn.
Stepping right into action, we start with an empty positions
list to help us log the sought positions. Understanding the dimensions of our "board" paves the way for defining boundaries in our exploration mission. Now, how does one determine the size of a Java 2D array? The answer lies in the .length
property.
Using a list is crucial here because we don't know beforehand how many positions will be found. A list in Java is dynamic and can resize itself to accommodate any number of elements, making it a perfect choice for storing an unknown number of positions.
Java1import java.util.ArrayList; 2import java.util.List; 3 4class Solution { 5 public static List<int[]> findPositions(char[][] board) { 6 List<int[]> positions = new ArrayList<>(); 7 8 int rows = board.length; 9 int cols = board[0].length; 10 // Further exploration follows
With our boundary map, we begin our expedition across the board. We use two nested for
loops to do this, traversing the entire board one cell at a time.
Java1import java.util.ArrayList; 2import java.util.List; 3 4class Solution { 5 public static List<int[]> findPositions(char[][] board) { 6 List<int[]> positions = new ArrayList<>(); 7 8 int rows = board.length; 9 int cols = board[0].length; 10 11 for (int i = 0; i < rows; i++) { 12 for (int j = 0; j < cols; j++) { 13 // ensuing exploration
What's the plan for each cell, you ask? While exploring each cell, our trusty Java code inspects if the cell is empty. If confirmed, it then peeks into the neighbors in the up, down, left, and right directions. If another vacant cell (E
) is spotted, we jot down the main cell's position in our positions
list.
Java1import java.util.ArrayList; 2import java.util.List; 3 4class Solution { 5 public static List<int[]> findPositions(char[][] board) { 6 List<int[]> positions = new ArrayList<>(); 7 8 int rows = board.length; 9 int cols = board[0].length; 10 11 for (int i = 0; i < rows; i++) { 12 for (int j = 0; j < cols; j++) { 13 if (board[i][j] == 'E') { 14 if ((i > 0 && board[i - 1][j] == 'E') || 15 (i < rows - 1 && board[i + 1][j] == 'E') || 16 (j > 0 && board[i][j - 1] == 'E') || 17 (j < cols - 1 && board[i][j + 1] == 'E')) { 18 positions.add(new int[]{i, j}); 19 } 20 } 21 } 22 } 23 return positions; 24 } 25 26 public static void main(String[] args) { 27 char[][] board = { 28 {'P', 'E', 'E', 'P'}, 29 {'E', 'P', 'E', 'P'}, 30 {'P', 'E', 'P', 'P'}, 31 {'P', 'E', 'P', 'E'} 32 }; 33 34 List<int[]> positions = findPositions(board); 35 36 for (int[] pos : positions) { 37 System.out.println("(" + pos[0] + ", " + pos[1] + ")"); 38 } 39 } 40} 41 42// The output will be: 43// (0, 1) 44// (0, 2) 45// (1, 2) 46// (2, 1) 47// (3, 1)
Neatly wrapped up, haven't we? Today we engaged in a thrilling treasure hunt and emerged victorious with the positions
list. This journey revealed the importance of understanding 2D arrays and effectively maneuvering through them using Java. Striking a balance between precision and caution, we cleverly avoided unwanted recursion and harnessed the power of conditional statements to devise an efficient blueprint for our code.
Now that we've mastered the theory, we step into the realm of application — the practice field. Venture forth and make your mark by solving correlated challenges. And remember, persistence is the best companion for a coder. Happy coding!