How to avoid infinite loop in BFS? - java

Here 's the LeetCode problem 542. 01 Matrix
My code will create an infinite loop because it will push every directions into the queue, even if that node has already been visited.
I can't think of a way to solve this problem. Could anyone help?
class Solution {
int[][] dirs = { {0,1},{0,-1},{1,0},{-1,0} };
public int[][] updateMatrix(int[][] matrix) {
for(int i=0;i < matrix.length;i++){
for(int j=0; j < matrix[i].length;j++){
if(matrix[i][j] == 1)
matrix[i][j] = Integer.MAX_VALUE;
BFS(new int[]{i,j},matrix);
}
}
return matrix;
}
public void BFS(int[] node,int[][] matrix){
if(matrix[node[0]][node[1]] == 0)
return;
LinkedList<int[]> queue = new LinkedList<>();
queue.push(node);
int step = 1;
while(!queue.isEmpty()){
int[] temp = queue.poll();
if(temp == null){
step++;
continue;
}
for(int[] dir:dirs){
int r = temp[0] + dir[0];
int c = temp[1] + dir[1];
if(r < 0 || c < 0 || r >= matrix.length || c >= matrix[r].length)
continue;
queue.push(new int[] {r,c});
if(matrix[r][c] == 0){
matrix[temp[0]][temp[1]] = Math.min(step,matrix[temp[0]][temp[1]]);
}
}
queue.push(null);
}
return;
}
}

You must keep track of the nodes that were already visited. You can either keep the nodes in the list, or move them to a separate Set.
The problem you have here is that the nodes are arrays, and you cannot use them in a HashSet. I would start by declaring a class Coordinates:
public class Coordinates {
public final int row;
public final int col;
public Coordinates(int r, int c) {
this.row = r;
this.col = c;
}
#Override
public int hashCode() {
return (row + 37*col) & 0x7FFFFFFF;
}
#Override
public boolean equals(Object other) {
if (other == null || other.getClass() != getClass()) {
return false;
}
Coordinates o = (Coordinates)other;
return row == o.row && col == o.col;
}
}
Option 1: keeping the nodes in the queue
I didn't understand the purpose of adding nulls into the queue; I just removed this.
public void BFS(Coordinates node,int[][] matrix){
if(matrix[node.row][node.col] == 0)
return;
List<Coordinates> queue = new ArrayList<>();
queue.add(node);
for (int i = 0; i < queue.size(); ++i) {
Coordinates temp = queue.get(i);
for(int[] dir:dirs){
int r = temp.row + dir.row;
int c = temp.col + dir.col;
if(r < 0 || c < 0 || r >= matrix.length || c >= matrix[r].length)
continue;
Coordinates newCoord = new Coordinates(r, c);
if (!queue.contains(newCoord)) {
queue.add(newCoord);
}
if(matrix[r][c] == 0){
matrix[temp.row][temp.col] = Math.min(step,matrix[temp.row][temp.col]);
}
}
}
return;
}
Option 2: use a separate Set
Now that we have a hashCodeand an equals method, why not use a HashSet?
I will leave this as an exercise though.

Encapsulate the node address in a class that can implement hashcode and equals, as proposed in this answer. Node class can be as simple as :
class Node {
private final int[] address;
Node(int[] address){
this.address = address;
}
#Override
public boolean equals(Object other) {
if(other == null ||!(other instanceof Node)) return false;
return Arrays.equals(address, ((Node)other).getAddress());
}
#Override
public int hashCode() {
return Arrays.hashCode(address);
}
public int[] getAddress() {
return address;
}
}
It allows you to maintain a collection of visited nodes : Set<Node> visited = new HashSet<>();
When visited.add(node) returns false, you know that visited already contains node

Related

Why would you use Trie data structure in WordSearch problem given below?

Given an m x n board of characters and a list of strings words, return all words on the board.
Each word must be constructed from letters of sequentially adjacent cells, where adjacent cells are horizontally or vertically neighboring. The same letter cell may not be used more than once in a word.
Word Search Problem
Brute Force Approach : Time Complexity will be O(num. of words * M * 4 * 3^L-1)
M = number of cells in the 2D matrix
L = length ofmaximum length of
words.
public class WordSearchII {
int flag = 0;
public List<String> findWords(char[][] b, String[] words) {
List<String> result = new ArrayList<>();
for (int k = 0; k < words.length; k++) {
flag = 0;
/*
* Find word's first letter. Then call method to check it's surroundings
*/
for (int r = 0; r < b.length; r++) {
for (int c = 0; c < b[0].length; c++) {
if (b[r][c] == words[k].charAt(0) && dfs(b, words[k], 0, r, c)) {
if (flag == 1) {
result.add(words[k]);
break;
}
}
}
if (flag == 1) {
break;
}
}
}
return result;
// return new ArrayList<>(new HashSet<>(result));
}
public boolean dfs(char[][] b, String word, int start, int r, int c) {
/* once we get past word.length, we are done. */
if (word.length() <= start) {
flag = 1;
return true;
}
/*
* if off bounds, letter is seen, letter is unequal to word.charAt(start)
* return false
*/
if (r < 0 || c < 0 || r >= b.length || c >= b[0].length || b[r][c] == '0' || b[r][c] != word.charAt(start))
return false;
/* set this board position to seen. (Because we can use this postion) */
char tmp = b[r][c];
b[r][c] = '0';
/* recursion on all 4 sides for next letter, if works: return true */
if (dfs(b, word, start + 1, r + 1, c) || dfs(b, word, start + 1, r - 1, c) || dfs(b, word, start + 1, r, c + 1)
|| dfs(b, word, start + 1, r, c - 1)) {
// Set back to unseen
b[r][c] = tmp;
return true;
}
// Set back to unseen
b[r][c] = tmp;
return false;
}
}
Trie-based approach
Time Complexity reduces to O(M * 4 * 3^L-1)
Introduces need for space O(2N); in case of worst case when Trie would have as many nodes as the letters of all words, where N is the total number of letters. Because we also store strings to be searched N becomes 2N
public class WordSearchIIWithTwist {
char[][] _board = null;
ArrayList<String> _result = new ArrayList<String>();
TrieNode root = new TrieNode();
public List<String> findWords(char[][] board, String[] words) {
// Step 1). Construct the Trie
for (int i = 0; i < words.length; i++) {
char[] arr = words[i].toCharArray();
TrieNode current = root;
for (int j = 0; j < arr.length; j++) {
if (!current.children.containsKey(arr[j])) {
current.children.put(arr[j], new TrieNode());
}
current = current.children.get(arr[j]);
}
current.word = words[i];
}
this._board = board;
// Step 2). Backtracking starting for each cell in the board
for (int i = 0; i < board.length; i++) {
for (int j = 0; j < board[0].length; j++) {
if (root.children.containsKey(board[i][j])) {
dfs(i, j, root);
}
}
}
return _result;
}
private void dfs(int row, int col, TrieNode parent) {
if (row < 0 || col < 0 || row >= _board.length || col >= _board[0].length || _board[row][col] == '#') {
return;
}
char letter = this._board[row][col];
if (!parent.children.containsKey(letter)) {
return;
}
TrieNode nextNode = parent.children.get(letter);
// check if there is any match
if (nextNode.word != null) {
_result.add(nextNode.word);
nextNode.word = null;
}
// mark the current letter before the EXPLORATION
this._board[row][col] = '#';
// explore neighbor cells in 4 directions: up, down, left, right
dfs(row + 1, col, nextNode);
dfs(row - 1, col, nextNode);
dfs(row, col - 1, nextNode);
dfs(row, col + 1, nextNode);
this._board[row][col] = letter;
}
public static void main(String[] args) {
WordSearchIIWithTwist a = new WordSearchIIWithTwist();
System.out.println(a.findWords(new char[][] { { 'a' } }, new String[] { "a" }));
}
}
class TrieNode {
Map<Character, TrieNode> children = new HashMap<>();
String word = null;
public TrieNode() {
};
}
Here is an alternative solution with an enhanced Node structure which makes the code simpler.
I'll leave it up to you to decide which is better for your needs:
import java.util.*;
public class Solution {
private char[][] board = null;
private boolean[][] visited = null;
private final Set<String> result = new HashSet<>();
int[][]directions = {{0,1},{1,0},{0,-1},{-1,0}};
public List<String> findWords(char[][] board, String[] words) {
List<Node> wordsAsNodes = new ArrayList<>();
for (String word : words) {
wordsAsNodes.add(new Node(word));
}
this.board = board;
for (int i = 0; i < board.length; i++) {
for (int j = 0; j < board[0].length; j++) {
final int ii=i, jj=j;
wordsAsNodes.forEach(node->{
if(node.c == board[ii][jj]){
visited = initializeVisited();
dfs(ii, jj, node);
}
});
}
}
return new ArrayList<>(result);
}
private boolean[][] initializeVisited() {
visited = new boolean[board.length][board[0].length];
for(boolean[] row : visited){
Arrays.fill(row, false);
}
return visited;
}
private void dfs(int row, int col, Node node) {
if (node == null || row < 0 || col < 0 || row >= board.length ||
col >= board[0].length || visited[row][col]) return;
char letter = board[row][col];
if (node.c != letter) return;
visited[row][col] = true;
Node nextNode = node.getNext();
// check if there is any match
if (nextNode == null) {
result.add(node.word);
return;
}
// explore neighbor cells in 4 directions
for(int[] dir : directions){
dfs(row + dir[0], col + dir[1], nextNode);
}
//if no solution found mark as unvisited for following attempts
visited[row][col] = false;
}
public static void main(String[] args) {
Solution a = new Solution();
char[][] board1 ={
{'o','a','a','n'},
{'e','t','a','e'},
{'i','h','k','r'},
{'i','f','l','v'}
};
String [] words1 = {"oath","pea","eat","rain"};
System.out.println(a.findWords(board1, words1));
}
}
class Node {
final String word;
private final int index;
private Node parent, next;
char c;
public Node(String word) {
this(word,0);
}
private Node(String word, int index) {
this.word = Objects.requireNonNull(word, "word should not be null");
this.index = index;
c = word.charAt(index);
}
private Node next() {
return index +1 < word.length() ? new Node(word, index+1) : null;
}
private Node parent() {
return index -1 >= 0 ? new Node(word, index-1) : null;
}
Node getParent() {
return parent == null ? parent = parent(): parent;
}
Node getNext() {
return next == null ? next = next(): next;
}
#Override
public String toString() {
return c +" index "+ index + " in " + word ;
}
}
The reason you might want to use a Trie is that you can use a TRIE to index the entire board (though creating this trie is not trivial) after you created the trie you can find any word in it in O(1) time
board = { T H
M E}
trieBeforeDict =
-root-
|------------------------------\--------------\--\
T H M E
|------ | ..etc..
|-------\---\ \--\--\
H M E T M E
|--\ ..etc.. ..etc..
M E
| |
E M
traverse with dictionary
* marks isWord attribute
trieAfterDict =
-root-
|--\--\
T H M
| | |
| E* E*
H |
| M*
|
E*
|
M*
After initialization you can discard the board and dictionary and any future lookups will be very fast and the memory overhead is low.
A reason to want this could be that you want to minimize overhead in a game and have the option of precompiling the 'game' in development, and ship the 'compiled' trie to production

find the shortest path in a number maze, Java

In a number maze, a player always starts from the square at the upper left and makes a certain number of moves which will take him/her to the square marked Goal if a solution exist. The value in each cell in the maze indicates how far a player must move horizontally or vertically from its current position.
My task is to find out if the shortest path to the cell labeled “Goal” and print it.
Input
the maze is in the form of square 2D array. The goal square is indicated by the number -1 in the maze description.
Output
For the maze, output the solution of the maze or the phrase “No Solution Possible.” Solutions should be output as a list of square coordinates in the format “(Row, Column)”, in the order in which they are visited from the start to the goal, including the starting cell. You will need to report the shortest solution from start to the goal. The shortest solution will be unique.
I have tried some solution, but I think there is problem that is the solution is always the first path I found not the shortest..
public class findShoretstPath
{
private static Stack<Node> stack = new Stack<>();
private static class Node
{
private int[] coordinate = new int[2];
private int data;
private Node Right, Left, Top, Bottom;
public Node(){}
}
public static boolean isValid(int[][] a, int x, int y)
{
if(x >= 0 && x < a.length && y >= 0 && y < a.length)
return true;
return false;
}
public static Node[][] nodeArray(int[][] a)
{
Node[][] nodeA = new Node[a.length][a.length];
for(int i = 0; i<nodeA.length; i++)
for(int j = 0; j<nodeA[i].length; j++)
{
nodeA[i][j] = new Node();
nodeA[i][j].coordinate[0] = i;
nodeA[i][j].coordinate[1] = j;
nodeA[i][j].data = a[i][j];
}
for(int i = 0; i<nodeA.length; i++)
for(int j = 0; j<nodeA[i].length; j++)
{
if(isValid(a, i, j+nodeA[i][j].data))
nodeA[i][j].Right = nodeA[i][j+nodeA[i][j].data];
if(isValid(a, i, j-nodeA[i][j].data))
nodeA[i][j].Left = nodeA[i][j-nodeA[i][j].data];
if(isValid(a, i+nodeA[i][j].data, j))
nodeA[i][j].Bottom = nodeA[i+nodeA[i][j].data][j];
if(isValid(a, i-nodeA[i][j].data, j))
nodeA[i][j].Top = nodeA[i-nodeA[i][j].data][j];
}
return nodeA;
}
public static boolean findPath(Node[][] s, int[][] t, int x, int y)
{
boolean b = false;
if(t[x][y] == 0)
{
t[x][y] = 1;
if(s[x][y].data == -1) b = true;
else
{
if(s[x][y].Right != null) b = findPath(s, t, x, y+s[x][y].data);
if(!b && s[x][y].Bottom != null) b = findPath(s, t, x+s[x][y].data, y);
if(!b && s[x][y].Left != null) b = findPath(s, t, x, y-s[x][y].data);
if(!b && s[x][y].Top != null) b = findPath(s, t, x-s[x][y].data, y);
}
if(b) stack.add(s[x][y]);
}
return b;
}
public static void main(String[] args)
{
int[][] maze = {{1,1,1,1,1},
{1,1,1,1,1},
{1,1,1,1,1},
{1,1,1,1,3},
{4,1,1,3,-1}};
Node[][] net = nodeArray(maze);
int[][] path = new int[maze.length][maze[0].lenght];
if(findPath(net, path, 0, 0))
{
Node temp;
while(!stack.isEmpty())
{
temp = stack.pop();
System.out.print("("+temp.coordinate[0]+" "+temp.coordinate[1]+") ");
}
}
else System.out.println("No Solution Possible.");
}
}
for this example the output should be:
(0 0) (1 0) (2 0) (3 0) (4 0) (4 4)
but I have this output:
(0 0) (0 1) (0 2) (0 3) (0 4) (1 4) (2 4) (3 4) (3 1) (3 2) (3 3) (4 3) (4 0) (4 4)
Please, any help how to fix the code so the solution will be the shortest path?!
After searching about BFS, now I know the difference between DFS and BFS.
DFS algorithm travels a path from the source to the last node, if the goal is found stop, else try another path again from the source to the last node, and so until the goal is reached. While BFS algorithm travels from the source to the level below, if the goal is found stop, else go to the next level and so on..
For my problem, BFS is a suitable algorithm to find the shortest path.
The code after some modifications:
public class findShoretstPath
{
private static class Node
{
private int[] coordinate = new int[2];
private int data;
private Node Right, Left, Top, Bottom;
public Node(){}
}
public static boolean isLinked(Node s, Node d) //method to determine if the node d is linked to the node s
{
if(d.Right == s) return true;
if(d.Bottom == s) return true;
if(d.Left == s) return true;
if(d.Top == s) return true;
return false;
}
public static boolean isValid(int[][] a, int x, int y)
{
if(x >= 0 && x < a.length && y >= 0 && y < a.length)
return true;
return false;
}
public static Node[][] nodeArray(int[][] a)
{
Node[][] nodeA = new Node[a.length][a.length];
for(int i = 0; i<nodeA.length; i++)
for(int j = 0; j<nodeA[i].length; j++)
{
nodeA[i][j] = new Node();
nodeA[i][j].coordinate[0] = i;
nodeA[i][j].coordinate[1] = j;
nodeA[i][j].data = a[i][j];
}
for(int i = 0; i<nodeA.length; i++)
for(int j = 0; j<nodeA[i].length; j++)
{
if(isValid(a, i, j+nodeA[i][j].data))
nodeA[i][j].Right = nodeA[i][j+nodeA[i][j].data];
if(isValid(a, i, j-nodeA[i][j].data))
nodeA[i][j].Left = nodeA[i][j-nodeA[i][j].data];
if(isValid(a, i+nodeA[i][j].data, j))
nodeA[i][j].Bottom = nodeA[i+nodeA[i][j].data][j];
if(isValid(a, i-nodeA[i][j].data, j))
nodeA[i][j].Top = nodeA[i-nodeA[i][j].data][j];
}
return nodeA;
}
public static void shortestPath(Node[][] nodes, int x, int y)
{
Stack<Node> stack = new Stack<>();
Queue<Node> queue = new LinkedList<>();
int[][] path = new int[nodes.length][nodes[0].length];
boolean b = false;
int level = 1;//to keep tracking each level viseted
queue.add(nodes[x][y]);
path[x][y] = level;
while(!queue.isEmpty())
{
Node temp;
level++;
int size = queue.size();
for(int i = 0; i<size; i++)
{
temp = queue.remove();
if(temp.data == -1) {b = true; break;}
if(temp.Right != null && path[temp.Right.coordinate[0]][temp.Right.coordinate[1]] == 0)
{
queue.add(temp.Right);
path[temp.Right.coordinate[0]][temp.Right.coordinate[1]] = level;
}
if(temp.Bottom != null && path[temp.Bottom.coordinate[0]][temp.Bottom.coordinate[1]] == 0)
{
queue.add(temp.Bottom);
path[temp.Bottom.coordinate[0]][temp.Bottom.coordinate[1]] = level;
}
if(temp.Left != null && path[temp.Left.coordinate[0]][temp.Left.coordinate[1]] == 0)
{
queue.add(temp.Left);
path[temp.Left.coordinate[0]][temp.Left.coordinate[1]] = level;
}
if(temp.Top != null && path[temp.Top.coordinate[0]][temp.Top.coordinate[1]] == 0)
{
queue.add(temp.Top);
path[temp.Top.coordinate[0]][temp.Top.coordinate[1]] = level;
}
}
if(b) break;
}
if(b)
{
int x1 = 0, y1 = 0;
for(int i = 0; i<nodes.length; i++)// to locate the position of the goal
for(int j = 0; j<nodes.length; j++)
if(nodes[i][j].data == -1)
{
x1 = i; y1 = j;
}
stack.add(nodes[x1][y1]);
int d = path[x1][y1];
while(d > 0)//go back from the goal to the source
{
for(int i = 0; i<path.length; i++)
{
if(path[x1][i] == d-1 && isLinked(nodes[x1][y1], nodes[x1][i]))
{
stack.add(nodes[x1][i]);
y1 = i;
break;
}
else if(path[i][y1] == d-1 && isLinked(nodes[x1][y1], nodes[i][y1]))
{
stack.add(nodes[i][y1]);
x1 = i;
break;
}
}
d--;
}
Node temp;
int stackSize = stack.size();
for(int i = 0; i<stackSize; i++)// print the final result
{
temp = stack.pop();
System.out.print("("+temp.coordinate[0]+" "+temp.coordinate[1]+") ");
}
}
else System.out.print("No Solution Possible.");
}
public static void main(String[] args)
{
int[][] maze = {{1,1,1,1,1},
{1,1,1,1,1},
{1,1,1,1,1},
{1,1,1,1,3},
{4,1,1,3,-1}};
Node[][] net = nodeArray(maze);
shortestPath(net, 0, 0));
System.out.println("");
}
}
and the output now is:
(0 0) (1 0) (2 0) (3 0) (4 0) (4 4)

EmptyStackException - Java Depth First Search algorithm on 2D array

I have looked at this question here I tried most of the code samples from there but when i use it in my code it just skips the algorithm.
I have this DFS algorithm that uses stack, I am getting a EmptyStackException, I have debugged the algorithm and after first recursive search the stack is empty, the first search works but then the size of stack is set to 0, What am I missing here? github
How can I make sure that the stack is not empty after the first search?
The line that I get the exception on is while(true){AddBridges state = gameTree.peek(); ...
I am using a 2d Array to generate the nodes at random from 0 to 4 0 = null 1-4 = island The array generates Random Integers every time the user starts the game, could that cause the Algorithm to brake,
After a weekend of debugging I found that the algorithm sometimes brakes after 4-6 searches, and sometimes breaks after the first search.
public int[][] debug_board_state_easy = new int[4][4];
//This Generates random 2d array
private void InitializeEasy() {
Random rand = new Random();
setCurrentState(new State(WIDTH_EASY));
for (int row = 0; row < debug_board_state_easy.length; row++) {
for (int column = 0; column < debug_board_state_easy[row].length; column++) {
debug_board_state_easy[row][column] = Integer.valueOf(rand.nextInt(5));
}
}
for (int row = 0; row < debug_board_state_easy.length; row++) {
for (int column = 0; column < debug_board_state_easy[row].length; column++) {
System.out.print(debug_board_state_easy[row][column] + " ");
}
System.out.println(debug_board_state_easy);
}
//I am applying the search algorithm here...
this.search();
for (int row = 0; row < WIDTH_EASY; ++row) {
for (int column = 0; column < WIDTH_EASY; ++column) {
getCurrentState().board_elements[row][column] = new BoardElement();
getCurrentState().board_elements[row][column].max_connecting_bridges = Integer.valueOf(debug_board_state_easy[row][column]);
getCurrentState().board_elements[row][column].row = row;
getCurrentState().board_elements[row][column].col = column;
if (getCurrentState().board_elements[row][column].max_connecting_bridges > 0) {
getCurrentState().board_elements[row][column].is_island = true;
}
}
}
}
void search() {
Map<Point, List<Direction>> remainingOptions = new HashMap<>();
Stack<Land> gameTree = new Stack<>();
gameTree.push(new AddBridges(debug_board_state_easy));
while(true) {
AddBridges state = gameTree.peek();
int[] p = state.lowestTodo();
if (p == null)
System.out.println("solution found");
// move to next game state
int row = p[0];
int column = p[1];
System.out.println("expanding game state for node at (" + row + ", " + column + ")");
List<Direction> ds = null;
if(remainingOptions.containsKey(new Point(row,column)))
ds = remainingOptions.get(new Point(row,column));
else{
ds = new ArrayList<>();
for(Direction dir : Direction.values()) {
int[] tmp = state.nextIsland(row, column, dir);
if(tmp == null)
continue;
if(state.canBuildBridge(row,column,tmp[0], tmp[1]))
ds.add(dir);
}
remainingOptions.put(new Point(row,column), ds);
}
// if the node can no longer be expanded, and backtracking is not possible we quit
if(ds.isEmpty() && gameTree.isEmpty()){
System.out.println("no valid configuration found");
return;
}
// if the node can no longer be expanded, we need to backtrack
if(ds.isEmpty()){
gameTree.pop();
remainingOptions.remove(new Point(row,column));
System.out.println("going back to previous decision");
continue;
}
Direction dir = ds.remove(0);
System.out.println("connecting " + dir.name());
remainingOptions.put(new Point(row,column), ds);
AddBridgesnextState = new AddBridges(state);
int[] tmp = state.nextIsland(row,column,dir);
nextState.connect(row,column, tmp[0], tmp[1]);
gameTree.push(nextState);
}
}
}
Add bridges class
public class AddBridges {
private int[][] BRIDGES_TO_BUILD;
private boolean[][] IS_ISLAND;
private Direction[][] BRIDGES_ALREADY_BUILT;
public Land(int[][] bridgesToDo){
BRIDGES_TO_BUILD = copy(bridgesToDo);
int numberRows = bridgesToDo.length;
int numberColumns = bridgesToDo[0].length;
BRIDGES_ALREADY_BUILT = new Direction[numberRows][numberColumns];
IS_ISLAND = new boolean[numberRows][numberColumns];
for(int i=0;i<numberRows;i++) {
for (int j = 0; j < numberColumns; j++) {
BRIDGES_ALREADY_BUILT[i][j] = null;
IS_ISLAND[i][j] = bridgesToDo[i][j] > 0;
}
}
}
public AddBridges (AddBridges other){
BRIDGES_TO_BUILD = copy(other.BRIDGES_TO_BUILD);
int numberRows = BRIDGES_TO_BUILD.length;
int numberColumns = BRIDGES_TO_BUILD[0].length;
BRIDGES_ALREADY_BUILT = new Direction[numberRows][numberColumns];
IS_ISLAND = new boolean[numberRows][numberColumns];
for(int i=0;i<numberRows;i++) {
for (int j = 0; j < numberColumns; j++) {
BRIDGES_ALREADY_BUILT[i][j] = other.BRIDGES_ALREADY_BUILT[i][j];
IS_ISLAND[i][j] = other.IS_ISLAND[i][j];
}
}
}
public int[] next(int r, int c, Direction dir){
int numberRows = BRIDGES_TO_BUILD.length;
int numberColumns = BRIDGES_TO_BUILD[0].length;
// out of bounds
if(r < 0 || r >=numberRows || c < 0 || c >= numberColumns)
return null;
// motion vectors
int[][] motionVector = {{-1, 0},{0,1},{1,0},{0,-1}};
int i = Arrays.asList(Direction.values()).indexOf(dir);
// calculate next
int[] out = new int[]{r + motionVector[i][0], c + motionVector[i][1]};
r = out[0];
c = out[1];
// out of bounds
if(r < 0 || r >=numberRows || c < 0 || c >= numberColumns)
return null;
// return
return out;
}
public int[] nextIsland(int row, int column, Direction dir){
int[] tmp = next(row,column,dir);
if(tmp == null)
return null;
while(!IS_ISLAND[tmp[0]][tmp[1]]){
tmp = next(tmp[0], tmp[1], dir);
if(tmp == null)
return null;
}
return tmp;
}
public boolean canBuildBridge(int row0, int column0, int row1, int column1){
if(row0 == row1 && column0 > column1){
return canBuildBridge(row0, column1, row1, column0);
}
if(column0 == column1 && row0 > row1){
return canBuildBridge(row1, column0, row0, column1);
}
if(row0 == row1){
int[] tmp = nextIsland(row0, column0, Direction.EAST);
if(tmp == null)
return false;
if(tmp[0] != row1 || tmp[1] != column1)
return false;
if(BRIDGES_TO_BUILD[row0][column0] == 0)
return false;
if(BRIDGES_TO_BUILD[row1][column1] == 0)
return false;
for (int i = column0; i <= column1 ; i++) {
if(IS_ISLAND[row0][i])
continue;
if(BRIDGES_ALREADY_BUILT[row0][i] == Direction.NORTH)
return false;
}
}
if(column0 == column1){
int[] tmp = nextIsland(row0, column0, Direction.SOUTH);
if(tmp == null)
return false;
if(tmp[0] != row1 || tmp[1] != column1)
return false;
if(BRIDGES_TO_BUILD[row0][column0] == 0 || BRIDGES_TO_BUILD[row1][column1] == 0)
return false;
for (int i = row0; i <= row1 ; i++) {
if(IS_ISLAND[i][column0])
continue;
if(BRIDGES_ALREADY_BUILT[i][column0] == Direction.EAST)
return false;
}
}
// default
return true;
}
public int[] lowestTodo(){
int R = BRIDGES_TO_BUILD.length;
int C = BRIDGES_TO_BUILD[0].length;
int[] out = {0, 0};
for (int i=0;i<R;i++) {
for (int j = 0; j < C; j++) {
if(BRIDGES_TO_BUILD[i][j] == 0)
continue;
if (BRIDGES_TO_BUILD[out[0]][out[1]] == 0)
out = new int[]{i, j};
if (BRIDGES_TO_BUILD[i][j] < BRIDGES_TO_BUILD[out[0]][out[1]])
out = new int[]{i, j};
}
}
if (BRIDGES_TO_BUILD[out[0]][out[1]] == 0) {
return null;
}
return out;
}
#TargetApi(Build.VERSION_CODES.GINGERBREAD)
private int[][] copy(int[][] other){
int[][] out = new int[other.length][other.length == 0 ? 0 : other[0].length];
for(int r=0;r<other.length;r++)
out[r] = Arrays.copyOf(other[r], other[r].length);
return out;
}
public void connect(int r0, int c0, int r1, int c1){
if(r0 == r1 && c0 > c1){
connect(r0, c1, r1, c0);
return;
}
if(c0 == c1 && r0 > r1){
connect(r1, c0, r0, c1);
return;
}
if(!canBuildBridge(r0, c0, r1, c1))
return;
BRIDGES_TO_BUILD[r0][c0]--;
BRIDGES_TO_BUILD[r1][c1]--;
if(r0 == r1){
for (int i = c0; i <= c1 ; i++) {
if(IS_ISLAND[r0][i])
continue;
BRIDGES_ALREADY_BUILT[r0][i] = Direction.EAST;
}
}
if(c0 == c1){
for (int i = r0; i <= r1 ; i++) {
if(IS_ISLAND[i][c0])
continue;
BRIDGES_ALREADY_BUILT[i][c0] = Direction.NORTH;
}
}
}
}
One part of your question stood out to me as the root of the problem: "What am I missing here"? Unit tests, unless I just didn't see them in your project.
Questions like "the array generates Random Integers every time the user starts the game, could that cause the Algorithm to brake?", are the reason unit tests exist, along with the following:
In the course of writing tests on sections of code that don't end up
being the problem, you'll prove definitively that they aren't the
problem.
If the code you're working with can't be tested as-is, or
is "too complex" to test, re-writing it will make you a better
designer and will often lead to "I can't believe I didn't see that"
moments.
When you refactor this program (reduce complexity, rename variables to make them easier to understand, etc), you'll be notified immediately if something breaks
and you won't have to spend another weekend trying to figure it out.
As an example, instead of randomizing the board within the method that searches it, randomize it elsewhere and then drop it into that method as an argument (or into the class' constructor). That way, you can initialize your own test board(s) with your own supplied values and see if some boards work better than others and why. Split up larger methods into smaller methods, each with their own parameters and tests. Aim to make a program out of smaller confirmed-working pieces, instead of making a huge thing and then wondering if the problem is the small part you think it is or something else.
You'll save so much time and frustration in the long run, and you'll end up leagues ahead of those who code for hours and then debug for hours.
There's a lot going on in the code, but the first thing I notice might help:
// if the node can no longer be expanded, we need to backtrack
if(ds.isEmpty()){
gameTree.pop();
remainingOptions.remove(new Point(row,column));
System.out.println("going back to previous decision");
continue;
}
you pop from the stack, and continue onto the next while(true) iteration, at that point, there may be nothing on the stack since you have not added anything else.
I agree with #Rosa -
The EmptyStackException should occur when removing or looking up empty Stack-
======Iteration/State in code ======
**if(ds.isEmpty()){** //HashMap isEmpty = true and gameTree.size() = 1
gameTree.pop(); // After removing element gameTree.size() = 0 (no elements in stack to peek or pop)
remainingOptions.remove(new Point(row,column));
System.out.println("going back to previous decision");
continue; //Skip all the instruction below this, continue to next iteration
}
========Next iteration========
while(true){
AddBridges state = gameTree.peek(); // gameTree.size() = 0 and a peek
operation shall fail and program will return EmptyStackException.
Required isEmpty check -
if(gameTree.isEmpty()){
System.out.println("no valid configuration found");
return;
}
AddBridges state = gameTree.peek();
As, no actions have been performed by function but while loop. In case other instcutions to be processed , a "break" is required.

Constructing Mazes in java using 2D array and stacks

I need to construct a maze using a 2D array and stacks. The array size is fixed. the starting point is (0,0). The array should be read from a file but in this example, I am assuming values just to make things clear.
I can't seem to find a proper algorithm that lets me go through the 2D array and saves my path to the stack. And that gets me back to the upper row if I am stuck in the current row. PS: 1 is a wall and 0 is a path. The question requires an array input by the user but I provided one for simplicity
Heres the array:
0 1 0 0 0
0 1 0 0 0
0 0 0 0 0
1 1 1 0 0
0 1 0 0 0
I need to start from position (0,0) and the exit should be in the last row. If I got stuck I need to go up and find another path; that is pop the stack.
Here's what I came up with:
public class Maze {
Maze currentPos = new Maze();
int position = maze[0][0];
public Maze()
{
}
public Maze(Maze currentPos)
{
this.currentPos = currentPos;
position = maze[0][0];
}
Stack stack = new Stack ();
public static int[][] maze = new int[][] {
{0,1,0,0,0},
{0,1,0,0,0},
{0,0,0,0,0},
{1,1,1,0,0},
{0,1,0,0,0}
};
public boolean UP (int i, int j)
{
if (maze [i-1][j] == 0)
return true;
return false;
}
public boolean DOWN (int i, int j)
{
if (maze [i+1][j] == 0)
return true;
return false;
}
public boolean RIGHT(int i,int j)
{
if (maze [i][j+1] == 0)
return true;
return false;
}
public boolean LEFT(int i,int j)
{
if (maze [i][j-1] == 0)
return true;
return false;
}
public boolean isExit (int i, int j)
{
if (j == 6)
return true;
return false;
}
public void setPosition(int i , int j)
{
position = maze[i][j];
}
public void solve()
{
for (int i=0; i<maze.length; i++)
{
for (int j=0; j<maze.length; j++)
{
while(! currentPos.isExit(i,j));
{
if ( currentPos.DOWN(i,j)) stack.push(i+1,j);
if ( currentPos.LEFT(i,j)) stack.push(i,j-1);
if ( currentPos.RIGHT(i,j)) stack.push(i,i+1);
if ( currentPos.UP(i,j)) stack.push(i-1,j);
}
}
}
}
}
The class stack is the same as the one in java.util.stack and with the same methods included (pop, push)
Here is something to get you started :
import java.util.ArrayList;
import java.util.List;
import java.util.Stack;
public class Maze {
//keep reference to start point
int startRow, startCol;
//keep reference to addresses (row, col) that has been checked
List<Integer[]> visited;
//a stack that represents the path (solution)
Stack<Integer[]> path;
public Maze(int startRow, int startCol) {
this.startRow = startRow; //add: check input validity
this.startCol = startCol;
visited = new ArrayList<>();
path = new Stack<>();
}
public static int[][] mazeValues = new int[][] {
{0,1,0,0,0},
{0,0,0,1,0},
{1,1,1,0,0},
{1,1,1,0,1},
{0,0,0,0,0}
};
void solve(){
boolean isSolved = solve(startRow, startCol);
if( isSolved ) {
pathFound();
} else {
noPathFound();
}
}
private boolean solve(int row, int col) {
//check if target found
if(isTargert(row,col)) {
//add target to path
path.push(new Integer[]{row,col});
return true;
}
//check if address is a wall
if(isWall(row,col)) {
return false;
}
//check if visited before
if(isVisited(row, col)) {
return false;
}
//mark as visited
visited.add(new Integer[]{row,col});
//add to path
path.push(new Integer[]{row,col});
//check all neighbors (allows diagonal move)
for (int rowIndex = row-1; rowIndex <= (row+1) ; rowIndex++ ) {
for (int colIndex = col-1; colIndex <= (col+1) ; colIndex++ ) {
if( (rowIndex == row) && (colIndex == col)) {//skip current address
continue;
}
if( ! withInMaze(rowIndex, colIndex)) {
continue;
}
if( solve(rowIndex, colIndex)) {
return true; //solution found
}
}
}
//solution not found after checking all neighbors
path.pop(); //remove last from stack;
return false;
}
//check if address is a target
private boolean isTargert(int row, int col) {
//target set to last row / col. Change taget as needed
return (row == (mazeValues.length-1))&& (col == (mazeValues[0].length -1)) ;
}
//check if address is a wall
private boolean isWall(int row, int col) {
return mazeValues[row][col] == 1;
}
private boolean isVisited(int row, int col) {
for (Integer[] address : visited ) {
if((address[0]==row) && (address[1]==col)) {
return true;
}
}
return false;
}
//return true if rowIndex, colIndex are with in mazeValues
private boolean withInMaze(int rowIndex, int colIndex) {
return (rowIndex < mazeValues.length)&& (rowIndex >= 0)
&&(colIndex < mazeValues[0].length) && (colIndex >=0);
}
private void noPathFound() {
System.out.println("No path found............");
}
private void pathFound() {
System.out.println("Path found");
for (Integer[] address : path) {
int row = address[0]; int col = address[1];
System.out.println("Address: "+ row +"-"+ col
+" value: "+ mazeValues[row][col]);
}
}
public static void main(String[] args) {
Maze maze = new Maze(0,0);
maze.solve();
}
}
For generic maze path finding algorithms I would suggest to start with Breadth-first search

Keeping track of Collisions per index in an array-based hash table, as well as which values resulted in a collision using OPEN ADDRESSING ONLY

Sorry for the wordy title but it explains my question pretty well.
I am working on an assignment in Java where I need to create my own Hash Table.
The specifications are such that I must use an Array, as well as open-addressing for collision handling (with both double hashing and quadratic hashing implementations).
My implementation works quite well, and using over 200,000 randomly generated Strings I end up with only ~1400 Collisions with both types of collision handling mentioned about (keeping my load factor at 0.6 and increasing my Array by 2.1 when it goes over).
Here is where I'm stumped, however... My assignment calls for 2 specifications that I cannot figure out.
1) Have an option which, when removing a value form the table, instead of using "AVAILABLE" (replacing the index in the array with a junk value that indicates it is empty), I must find another value that previously hashed to this index and resulted in a collision. For example, if value A hashed to index 2 and value B also hashed to index 2 (and was later re-hashed to index 5 using my collision handling hash function), then removing value A will actually replace it with Value B.
2) Keep track of the maximum number of collisions in a single array index. I currently keep track of all the collisions, but there's no way for me to keep track of the collisions at an individual cell.
I was able to solve this problem using Separate Chaining by having each Array Index hold a linked list of all values that have hashed to this index, so that only the first one is retrieved when I call my get(value) method, but upon removal I can easily replace it with the next value that hashed to this index. It's also an easy way to get the max number of collisions per index.
But we were specifically told not to use separate chaining... I'm actually wondering if this is even possible without completely ruining the complexity of the hash table.
Any advice would be appreciated.
edit:
Here are some examples to give you an idea of my class structure:
public class daveHash {
//Attributes
public String[] dTable;
private double loadFactor, rehashFactor;
private int size = 0;
private String emptyMarkerScheme;
private String collisionHandlingType;
private int collisionsTotal = 0;
private int collisionsCurrent = 0;
//Constructors
public daveHash()
{
dTable = new String[17];
rehashFactor = 2.1;
loadFactor = 0.6;
emptyMarkerScheme = "A";
collisionHandlingType = "D";
}
public daveHash(int size)
{
dTable = new String[size];
rehashFactor = 2.1;
loadFactor = 0.6;
emptyMarkerScheme = "A";
collisionHandlingType = "D";
}
My hashing functions:
public long getHashCode(String s, int index)
{
if (index > s.length() - 1)
return 0;
if (index == s.length()-1)
return (long)s.charAt(index);
if (s.length() >= 20)
return ((long)s.charAt(index) + 37 * getHashCode(s, index+3));
return ((long)s.charAt(index) + 37 * getHashCode(s, index+1));
}
public int compressHashCode(long hash, int arraySize)
{
int b = nextPrime(arraySize);
int index = ((int)((7*hash) % b) % arraySize);
if (index < 0)
return index*-1;
else
return index;
}
Collision handling:
private int collisionDoubleHash(int index, long hashCode, String value, String[] table)
{
int newIndex = 0;
int q = previousPrime(table.length);
int secondFunction = (q - (int)hashCode) % q;
if (secondFunction < 0)
secondFunction = secondFunction*-1;
for (int i = 0; i < table.length; i++)
{
newIndex = (index + i*secondFunction) % table.length;
//System.out.println(newIndex);
if (isAvailable(newIndex, table))
{
table[newIndex] = value;
return newIndex;
}
}
return -1;
}
private int collisionQuadraticHash(int index, long hashCode, String value, String[] table)
{
int newIndex = 0;
for (int i = 0; i < table.length; i ++)
{
newIndex = (index + i*i) % table.length;
if (isAvailable(newIndex, table))
{
table[newIndex] = value;
return newIndex;
}
}
return -1;
}
public int collisionHandling(int index, long hashCode, String value, String[] table)
{
collisionsTotal++;
collisionsCurrent++;
if (this.collisionHandlingType.equals("D"))
return collisionDoubleHash(index, hashCode, value, table);
else if (this.collisionHandlingType.equals("Q"))
return collisionQuadraticHash(index, hashCode, value, table);
else
return -1;
}
Get, Put and Remove:
private int getIndex(String k)
{
long hashCode = getHashCode(k, 0);
int index = compressHashCode(hashCode, dTable.length);
if (dTable[index] != null && dTable[index].equals(k))
return index;
else
{
if (this.collisionHandlingType.equals("D"))
{
int newIndex = 0;
int q = previousPrime(dTable.length);
int secondFunction = (q - (int)hashCode) % q;
if (secondFunction < 0)
secondFunction = secondFunction*-1;
for (int i = 0; i < dTable.length; i++)
{
newIndex = (index + i*secondFunction) % dTable.length;
if (dTable[index] != null && dTable[newIndex].equals(k))
{
return newIndex;
}
}
}
else if (this.collisionHandlingType.equals("Q"))
{
int newIndex = 0;
for (int i = 0; i < dTable.length; i ++)
{
newIndex = (index + i*i) % dTable.length;
if (dTable[index] != null && dTable[newIndex].equals(k))
{
return newIndex;
}
}
}
return -1;
}
}
public String get(String k)
{
long hashCode = getHashCode(k, 0);
int index = compressHashCode(hashCode, dTable.length);
if (dTable[index] != null && dTable[index].equals(k))
return dTable[index];
else
{
if (this.collisionHandlingType.equals("D"))
{
int newIndex = 0;
int q = previousPrime(dTable.length);
int secondFunction = (q - (int)hashCode) % q;
if (secondFunction < 0)
secondFunction = secondFunction*-1;
for (int i = 0; i < dTable.length; i++)
{
newIndex = (index + i*secondFunction) % dTable.length;
if (dTable[index] != null && dTable[newIndex].equals(k))
{
return dTable[newIndex];
}
}
}
else if (this.collisionHandlingType.equals("Q"))
{
int newIndex = 0;
for (int i = 0; i < dTable.length; i ++)
{
newIndex = (index + i*i) % dTable.length;
if (dTable[index] != null && dTable[newIndex].equals(k))
{
return dTable[newIndex];
}
}
}
return null;
}
}
public void put(String k, String v)
{
double fullFactor = (double)this.size / (double)dTable.length;
if (fullFactor >= loadFactor)
resizeTable();
long hashCode = getHashCode(k, 0);
int index = compressHashCode(hashCode, dTable.length);
if (isAvailable(index, dTable))
{
dTable[index] = v;
size++;
}
else
{
collisionHandling(index, hashCode, v, dTable);
size++;
}
}
public String remove(String k)
{
int index = getIndex(k);
if (dTable[index] == null || dTable[index].equals("AVAILABLE") || dTable[index].charAt(0) == '-')
return null;
else
{
if (this.emptyMarkerScheme.equals("A"))
{
String val = dTable[index];
dTable[index] = "AVAILABLE";
size--;
return val;
}
else if (this.emptyMarkerScheme.equals("N"))
{
String val = dTable[index];
dTable[index] = "-" + val;
size--;
return val;
}
}
return null;
}
Hopefully this can give you an idea of my approach. This does not include the Separate Chaining implementation I mentioned above. For this, I had the following inner classes:
private class hashList
{
private class hashNode
{
private String element;
private hashNode next;
public hashNode(String element, hashNode n)
{
this.element = element;
this.next = n;
}
}
private hashNode head;
private int length = 0;
public hashList()
{
head = null;
}
public void addToStart(String s)
{
head = new hashNode(s, head);
length++;
}
public int getLength()
{
return length;
}
}
And my methods were modified appropriate to access the element in the head node vs the element in the Array. I took this out, however, since we are not supposed to use Separate Chaining to solve the problem.
Thanks!!

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