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Leetcode 题解 - 搜索.md
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Leetcode 题解 - 搜索.md
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<!-- GFM-TOC -->
* [BFS](#bfs)
* [1. 计算在网格中从原点到特定点的最短路径长度](#1-计算在网格中从原点到特定点的最短路径长度)
* [2. 组成整数的最小平方数数量](#2-组成整数的最小平方数数量)
* [3. 最短单词路径](#3-最短单词路径)
* [DFS](#dfs)
* [1. 查找最大的连通面积](#1-查找最大的连通面积)
* [2. 矩阵中的连通分量数目](#2-矩阵中的连通分量数目)
* [3. 好友关系的连通分量数目](#3-好友关系的连通分量数目)
* [4. 填充封闭区域](#4-填充封闭区域)
* [5. 能到达的太平洋和大西洋的区域](#5-能到达的太平洋和大西洋的区域)
* [Backtracking](#backtracking)
* [1. 数字键盘组合](#1-数字键盘组合)
* [2. IP 地址划分](#2-ip-地址划分)
* [3. 在矩阵中寻找字符串](#3-在矩阵中寻找字符串)
* [4. 输出二叉树中所有从根到叶子的路径](#4-输出二叉树中所有从根到叶子的路径)
* [5. 排列](#5-排列)
* [6. 含有相同元素求排列](#6-含有相同元素求排列)
* [7. 组合](#7-组合)
* [8. 组合求和](#8-组合求和)
* [9. 含有相同元素的组合求和](#9-含有相同元素的组合求和)
* [10. 1-9 数字的组合求和](#10-1-9-数字的组合求和)
* [11. 子集](#11-子集)
* [12. 含有相同元素求子集](#12-含有相同元素求子集)
* [13. 分割字符串使得每个部分都是回文数](#13-分割字符串使得每个部分都是回文数)
* [14. 数独](#14-数独)
* [15. N 皇后](#15-n-皇后)
<!-- GFM-TOC -->
深度优先搜索和广度优先搜索广泛运用于树和图中,但是它们的应用远远不止如此。
# BFS
<div align="center"> <img src="pics/95903878-725b-4ed9-bded-bc4aae0792a9.jpg"/> </div><br>
广度优先搜索一层一层地进行遍历,每层遍历都以上一层遍历的结果作为起点,遍历一个距离能访问到的所有节点。需要注意的是,遍历过的节点不能再次被遍历。
第一层:
- 0 -> {6,2,1,5}
第二层:
- 6 -> {4}
- 2 -> {}
- 1 -> {}
- 5 -> {3}
第三层:
- 4 -> {}
- 3 -> {}
每一层遍历的节点都与根节点距离相同。设 d<sub>i</sub> 表示第 i 个节点与根节点的距离,推导出一个结论:对于先遍历的节点 i 与后遍历的节点 j,有 d<sub>i</sub> <= d<sub>j</sub>。利用这个结论,可以求解最短路径等 **最优解** 问题:第一次遍历到目的节点,其所经过的路径为最短路径。应该注意的是,使用 BFS 只能求解无权图的最短路径,无权图是指从一个节点到另一个节点的代价都记为 1。
在程序实现 BFS 时需要考虑以下问题:
- 队列:用来存储每一轮遍历得到的节点;
- 标记:对于遍历过的节点,应该将它标记,防止重复遍历。
## 1. 计算在网格中从原点到特定点的最短路径长度
```html
[[1,1,0,1],
[1,0,1,0],
[1,1,1,1],
[1,0,1,1]]
```
题目描述:1 表示可以经过某个位置,求解从 (0, 0) 位置到 (tr, tc) 位置的最短路径长度。
```java
public int minPathLength(int[][] grids, int tr, int tc) {
final int[][] direction = {{1, 0}, {-1, 0}, {0, 1}, {0, -1}};
final int m = grids.length, n = grids[0].length;
Queue<Pair<Integer, Integer>> queue = new LinkedList<>();
queue.add(new Pair<>(0, 0));
int pathLength = 0;
while (!queue.isEmpty()) {
int size = queue.size();
pathLength++;
while (size-- > 0) {
Pair<Integer, Integer> cur = queue.poll();
int cr = cur.getKey(), cc = cur.getValue();
grids[cr][cc] = 0; // 标记
for (int[] d : direction) {
int nr = cr + d[0], nc = cc + d[1];
if (nr < 0 || nr >= m || nc < 0 || nc >= n || grids[nr][nc] == 0) {
continue;
}
if (nr == tr && nc == tc) {
return pathLength;
}
queue.add(new Pair<>(nr, nc));
}
}
}
return -1;
}
```
## 2. 组成整数的最小平方数数量
[279. Perfect Squares (Medium)](https://leetcode.com/problems/perfect-squares/description/)
```html
For example, given n = 12, return 3 because 12 = 4 + 4 + 4; given n = 13, return 2 because 13 = 4 + 9.
```
可以将每个整数看成图中的一个节点,如果两个整数之差为一个平方数,那么这两个整数所在的节点就有一条边。
要求解最小的平方数数量,就是求解从节点 n 到节点 0 的最短路径。
本题也可以用动态规划求解,在之后动态规划部分中会再次出现。
```java
public int numSquares(int n) {
List<Integer> squares = generateSquares(n);
Queue<Integer> queue = new LinkedList<>();
boolean[] marked = new boolean[n + 1];
queue.add(n);
marked[n] = true;
int level = 0;
while (!queue.isEmpty()) {
int size = queue.size();
level++;
while (size-- > 0) {
int cur = queue.poll();
for (int s : squares) {
int next = cur - s;
if (next < 0) {
break;
}
if (next == 0) {
return level;
}
if (marked[next]) {
continue;
}
marked[next] = true;
queue.add(next);
}
}
}
return n;
}
/**
* 生成小于 n 的平方数序列
* @return 1,4,9,...
*/
private List<Integer> generateSquares(int n) {
List<Integer> squares = new ArrayList<>();
int square = 1;
int diff = 3;
while (square <= n) {
squares.add(square);
square += diff;
diff += 2;
}
return squares;
}
```
## 3. 最短单词路径
[127. Word Ladder (Medium)](https://leetcode.com/problems/word-ladder/description/)
```html
Input:
beginWord = "hit",
endWord = "cog",
wordList = ["hot","dot","dog","lot","log","cog"]
Output: 5
Explanation: As one shortest transformation is "hit" -> "hot" -> "dot" -> "dog" -> "cog",
return its length 5.
```
```html
Input:
beginWord = "hit"
endWord = "cog"
wordList = ["hot","dot","dog","lot","log"]
Output: 0
Explanation: The endWord "cog" is not in wordList, therefore no possible transformation.
```
题目描述:找出一条从 beginWord 到 endWord 的最短路径,每次移动规定为改变一个字符,并且改变之后的字符串必须在 wordList 中。
```java
public int ladderLength(String beginWord, String endWord, List<String> wordList) {
wordList.add(beginWord);
int N = wordList.size();
int start = N - 1;
int end = 0;
while (end < N && !wordList.get(end).equals(endWord)) {
end++;
}
if (end == N) {
return 0;
}
List<Integer>[] graphic = buildGraphic(wordList);
return getShortestPath(graphic, start, end);
}
private List<Integer>[] buildGraphic(List<String> wordList) {
int N = wordList.size();
List<Integer>[] graphic = new List[N];
for (int i = 0; i < N; i++) {
graphic[i] = new ArrayList<>();
for (int j = 0; j < N; j++) {
if (isConnect(wordList.get(i), wordList.get(j))) {
graphic[i].add(j);
}
}
}
return graphic;
}
private boolean isConnect(String s1, String s2) {
int diffCnt = 0;
for (int i = 0; i < s1.length() && diffCnt <= 1; i++) {
if (s1.charAt(i) != s2.charAt(i)) {
diffCnt++;
}
}
return diffCnt == 1;
}
private int getShortestPath(List<Integer>[] graphic, int start, int end) {
Queue<Integer> queue = new LinkedList<>();
boolean[] marked = new boolean[graphic.length];
queue.add(start);
marked[start] = true;
int path = 1;
while (!queue.isEmpty()) {
int size = queue.size();
path++;
while (size-- > 0) {
int cur = queue.poll();
for (int next : graphic[cur]) {
if (next == end) {
return path;
}
if (marked[next]) {
continue;
}
marked[next] = true;
queue.add(next);
}
}
}
return 0;
}
```
# DFS
<div align="center"> <img src="pics/74dc31eb-6baa-47ea-ab1c-d27a0ca35093.png"/> </div><br>
广度优先搜索一层一层遍历,每一层得到的所有新节点,要用队列存储起来以备下一层遍历的时候再遍历。
而深度优先搜索在得到一个新节点时立即对新节点进行遍历:从节点 0 出发开始遍历,得到到新节点 6 时,立马对新节点 6 进行遍历,得到新节点 4;如此反复以这种方式遍历新节点,直到没有新节点了,此时返回。返回到根节点 0 的情况是,继续对根节点 0 进行遍历,得到新节点 2,然后继续以上步骤。
从一个节点出发,使用 DFS 对一个图进行遍历时,能够遍历到的节点都是从初始节点可达的,DFS 常用来求解这种 **可达性** 问题。
在程序实现 DFS 时需要考虑以下问题:
- 栈:用栈来保存当前节点信息,当遍历新节点返回时能够继续遍历当前节点。可以使用递归栈。
- 标记:和 BFS 一样同样需要对已经遍历过的节点进行标记。
## 1. 查找最大的连通面积
[695. Max Area of Island (Medium)](https://leetcode.com/problems/max-area-of-island/description/)
```html
[[0,0,1,0,0,0,0,1,0,0,0,0,0],
[0,0,0,0,0,0,0,1,1,1,0,0,0],
[0,1,1,0,1,0,0,0,0,0,0,0,0],
[0,1,0,0,1,1,0,0,1,0,1,0,0],
[0,1,0,0,1,1,0,0,1,1,1,0,0],
[0,0,0,0,0,0,0,0,0,0,1,0,0],
[0,0,0,0,0,0,0,1,1,1,0,0,0],
[0,0,0,0,0,0,0,1,1,0,0,0,0]]
```
```java
private int m, n;
private int[][] direction = {{0, 1}, {0, -1}, {1, 0}, {-1, 0}};
public int maxAreaOfIsland(int[][] grid) {
if (grid == null || grid.length == 0) {
return 0;
}
m = grid.length;
n = grid[0].length;
int maxArea = 0;
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
maxArea = Math.max(maxArea, dfs(grid, i, j));
}
}
return maxArea;
}
private int dfs(int[][] grid, int r, int c) {
if (r < 0 || r >= m || c < 0 || c >= n || grid[r][c] == 0) {
return 0;
}
grid[r][c] = 0;
int area = 1;
for (int[] d : direction) {
area += dfs(grid, r + d[0], c + d[1]);
}
return area;
}
```
## 2. 矩阵中的连通分量数目
[200. Number of Islands (Medium)](https://leetcode.com/problems/number-of-islands/description/)
```html
Input:
11000
11000
00100
00011
Output: 3
```
可以将矩阵表示看成一张有向图。
```java
private int m, n;
private int[][] direction = {{0, 1}, {0, -1}, {1, 0}, {-1, 0}};
public int numIslands(char[][] grid) {
if (grid == null || grid.length == 0) {
return 0;
}
m = grid.length;
n = grid[0].length;
int islandsNum = 0;
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
if (grid[i][j] != '0') {
dfs(grid, i, j);
islandsNum++;
}
}
}
return islandsNum;
}
private void dfs(char[][] grid, int i, int j) {
if (i < 0 || i >= m || j < 0 || j >= n || grid[i][j] == '0') {
return;
}
grid[i][j] = '0';
for (int[] d : direction) {
dfs(grid, i + d[0], j + d[1]);
}
}
```
## 3. 好友关系的连通分量数目
[547. Friend Circles (Medium)](https://leetcode.com/problems/friend-circles/description/)
```html
Input:
[[1,1,0],
[1,1,0],
[0,0,1]]
Output: 2
Explanation:The 0th and 1st students are direct friends, so they are in a friend circle.
The 2nd student himself is in a friend circle. So return 2.
```
题目描述:好友关系可以看成是一个无向图,例如第 0 个人与第 1 个人是好友,那么 M[0][1] 和 M[1][0] 的值都为 1。
```java
private int n;
public int findCircleNum(int[][] M) {
n = M.length;
int circleNum = 0;
boolean[] hasVisited = new boolean[n];
for (int i = 0; i < n; i++) {
if (!hasVisited[i]) {
dfs(M, i, hasVisited);
circleNum++;
}
}
return circleNum;
}
private void dfs(int[][] M, int i, boolean[] hasVisited) {
hasVisited[i] = true;
for (int k = 0; k < n; k++) {
if (M[i][k] == 1 && !hasVisited[k]) {
dfs(M, k, hasVisited);
}
}
}
```
## 4. 填充封闭区域
[130. Surrounded Regions (Medium)](https://leetcode.com/problems/surrounded-regions/description/)
```html
For example,
X X X X
X O O X
X X O X
X O X X
After running your function, the board should be:
X X X X
X X X X
X X X X
X O X X
```
题目描述:使被 'X' 包围的 'O' 转换为 'X'。
先填充最外侧,剩下的就是里侧了。
```java
private int[][] direction = {{0, 1}, {0, -1}, {1, 0}, {-1, 0}};
private int m, n;
public void solve(char[][] board) {
if (board == null || board.length == 0) {
return;
}
m = board.length;
n = board[0].length;
for (int i = 0; i < m; i++) {
dfs(board, i, 0);
dfs(board, i, n - 1);
}
for (int i = 0; i < n; i++) {
dfs(board, 0, i);
dfs(board, m - 1, i);
}
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
if (board[i][j] == 'T') {
board[i][j] = 'O';
} else if (board[i][j] == 'O') {
board[i][j] = 'X';
}
}
}
}
private void dfs(char[][] board, int r, int c) {
if (r < 0 || r >= m || c < 0 || c >= n || board[r][c] != 'O') {
return;
}
board[r][c] = 'T';
for (int[] d : direction) {
dfs(board, r + d[0], c + d[1]);
}
}
```
## 5. 能到达的太平洋和大西洋的区域
[417. Pacific Atlantic Water Flow (Medium)](https://leetcode.com/problems/pacific-atlantic-water-flow/description/)
```html
Given the following 5x5 matrix:
Pacific ~ ~ ~ ~ ~
~ 1 2 2 3 (5) *
~ 3 2 3 (4) (4) *
~ 2 4 (5) 3 1 *
~ (6) (7) 1 4 5 *
~ (5) 1 1 2 4 *
* * * * * Atlantic
Return:
[[0, 4], [1, 3], [1, 4], [2, 2], [3, 0], [3, 1], [4, 0]] (positions with parentheses in above matrix).
```
左边和上边是太平洋,右边和下边是大西洋,内部的数字代表海拔,海拔高的地方的水能够流到低的地方,求解水能够流到太平洋和大西洋的所有位置。
```java
private int m, n;
private int[][] matrix;
private int[][] direction = {{0, 1}, {0, -1}, {1, 0}, {-1, 0}};
public List<int[]> pacificAtlantic(int[][] matrix) {
List<int[]> ret = new ArrayList<>();
if (matrix == null || matrix.length == 0) {
return ret;
}
m = matrix.length;
n = matrix[0].length;
this.matrix = matrix;
boolean[][] canReachP = new boolean[m][n];
boolean[][] canReachA = new boolean[m][n];
for (int i = 0; i < m; i++) {
dfs(i, 0, canReachP);
dfs(i, n - 1, canReachA);
}
for (int i = 0; i < n; i++) {
dfs(0, i, canReachP);
dfs(m - 1, i, canReachA);
}
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
if (canReachP[i][j] && canReachA[i][j]) {
ret.add(new int[]{i, j});
}
}
}
return ret;
}
private void dfs(int r, int c, boolean[][] canReach) {
if (canReach[r][c]) {
return;
}
canReach[r][c] = true;
for (int[] d : direction) {
int nextR = d[0] + r;
int nextC = d[1] + c;
if (nextR < 0 || nextR >= m || nextC < 0 || nextC >= n
|| matrix[r][c] > matrix[nextR][nextC]) {
continue;
}
dfs(nextR, nextC, canReach);
}
}
```
# Backtracking
Backtracking(回溯)属于 DFS。
- 普通 DFS 主要用在 **可达性问题** ,这种问题只需要执行到特点的位置然后返回即可。
- 而 Backtracking 主要用于求解 **排列组合** 问题,例如有 { 'a','b','c' } 三个字符,求解所有由这三个字符排列得到的字符串,这种问题在执行到特定的位置返回之后还会继续执行求解过程。
因为 Backtracking 不是立即返回,而要继续求解,因此在程序实现时,需要注意对元素的标记问题:
- 在访问一个新元素进入新的递归调用时,需要将新元素标记为已经访问,这样才能在继续递归调用时不用重复访问该元素;
- 但是在递归返回时,需要将元素标记为未访问,因为只需要保证在一个递归链中不同时访问一个元素,可以访问已经访问过但是不在当前递归链中的元素。
## 1. 数字键盘组合
[17. Letter Combinations of a Phone Number (Medium)](https://leetcode.com/problems/letter-combinations-of-a-phone-number/description/)
<div align="center"> <img src="pics/9823768c-212b-4b1a-b69a-b3f59e07b977.jpg"/> </div><br>
```html
Input:Digit string "23"
Output: ["ad", "ae", "af", "bd", "be", "bf", "cd", "ce", "cf"].
```
```java
private static final String[] KEYS = {"", "", "abc", "def", "ghi", "jkl", "mno", "pqrs", "tuv", "wxyz"};
public List<String> letterCombinations(String digits) {
List<String> combinations = new ArrayList<>();
if (digits == null || digits.length() == 0) {
return combinations;
}
doCombination(new StringBuilder(), combinations, digits);
return combinations;
}
private void doCombination(StringBuilder prefix, List<String> combinations, final String digits) {
if (prefix.length() == digits.length()) {
combinations.add(prefix.toString());
return;
}
int curDigits = digits.charAt(prefix.length()) - '0';
String letters = KEYS[curDigits];
for (char c : letters.toCharArray()) {
prefix.append(c); // 添加
doCombination(prefix, combinations, digits);
prefix.deleteCharAt(prefix.length() - 1); // 删除
}
}
```
## 2. IP 地址划分
[93. Restore IP Addresses(Medium)](https://leetcode.com/problems/restore-ip-addresses/description/)
```html
Given "25525511135",
return ["255.255.11.135", "255.255.111.35"].
```
```java
public List<String> restoreIpAddresses(String s) {
List<String> addresses = new ArrayList<>();
StringBuilder tempAddress = new StringBuilder();
doRestore(0, tempAddress, addresses, s);
return addresses;
}
private void doRestore(int k, StringBuilder tempAddress, List<String> addresses, String s) {
if (k == 4 || s.length() == 0) {
if (k == 4 && s.length() == 0) {
addresses.add(tempAddress.toString());
}
return;
}
for (int i = 0; i < s.length() && i <= 2; i++) {
if (i != 0 && s.charAt(0) == '0') {
break;
}
String part = s.substring(0, i + 1);
if (Integer.valueOf(part) <= 255) {
if (tempAddress.length() != 0) {
part = "." + part;
}
tempAddress.append(part);
doRestore(k + 1, tempAddress, addresses, s.substring(i + 1));
tempAddress.delete(tempAddress.length() - part.length(), tempAddress.length());
}
}
}
```
## 3. 在矩阵中寻找字符串
[79. Word Search (Medium)](https://leetcode.com/problems/word-search/description/)
```html
For example,
Given board =
[
['A','B','C','E'],
['S','F','C','S'],
['A','D','E','E']
]
word = "ABCCED", -> returns true,
word = "SEE", -> returns true,
word = "ABCB", -> returns false.
```
```java
private final static int[][] direction = {{1, 0}, {-1, 0}, {0, 1}, {0, -1}};
private int m;
private int n;
public boolean exist(char[][] board, String word) {
if (word == null || word.length() == 0) {
return true;
}
if (board == null || board.length == 0 || board[0].length == 0) {
return false;
}
m = board.length;
n = board[0].length;
boolean[][] hasVisited = new boolean[m][n];
for (int r = 0; r < m; r++) {
for (int c = 0; c < n; c++) {
if (backtracking(0, r, c, hasVisited, board, word)) {
return true;
}
}
}
return false;
}
private boolean backtracking(int curLen, int r, int c, boolean[][] visited, final char[][] board, final String word) {
if (curLen == word.length()) {
return true;
}
if (r < 0 || r >= m || c < 0 || c >= n
|| board[r][c] != word.charAt(curLen) || visited[r][c]) {
return false;
}
visited[r][c] = true;
for (int[] d : direction) {
if (backtracking(curLen + 1, r + d[0], c + d[1], visited, board, word)) {
return true;
}
}
visited[r][c] = false;
return false;
}
```
## 4. 输出二叉树中所有从根到叶子的路径
[257. Binary Tree Paths (Easy)](https://leetcode.com/problems/binary-tree-paths/description/)
```html
1
/ \
2 3
\
5
```
```html
["1->2->5", "1->3"]
```
```java
public List<String> binaryTreePaths(TreeNode root) {
List<String> paths = new ArrayList<>();
if (root == null) {
return paths;
}
List<Integer> values = new ArrayList<>();
backtracking(root, values, paths);
return paths;
}
private void backtracking(TreeNode node, List<Integer> values, List<String> paths) {
if (node == null) {
return;
}
values.add(node.val);
if (isLeaf(node)) {
paths.add(buildPath(values));
} else {
backtracking(node.left, values, paths);
backtracking(node.right, values, paths);
}
values.remove(values.size() - 1);
}
private boolean isLeaf(TreeNode node) {
return node.left == null && node.right == null;
}
private String buildPath(List<Integer> values) {
StringBuilder str = new StringBuilder();
for (int i = 0; i < values.size(); i++) {
str.append(values.get(i));
if (i != values.size() - 1) {
str.append("->");
}
}
return str.toString();
}
```
## 5. 排列
[46. Permutations (Medium)](https://leetcode.com/problems/permutations/description/)
```html
[1,2,3] have the following permutations:
[
[1,2,3],
[1,3,2],
[2,1,3],
[2,3,1],
[3,1,2],
[3,2,1]
]
```
```java
public List<List<Integer>> permute(int[] nums) {
List<List<Integer>> permutes = new ArrayList<>();
List<Integer> permuteList = new ArrayList<>();
boolean[] hasVisited = new boolean[nums.length];
backtracking(permuteList, permutes, hasVisited, nums);
return permutes;
}
private void backtracking(List<Integer> permuteList, List<List<Integer>> permutes, boolean[] visited, final int[] nums) {
if (permuteList.size() == nums.length) {
permutes.add(new ArrayList<>(permuteList)); // 重新构造一个 List
return;
}
for (int i = 0; i < visited.length; i++) {
if (visited[i]) {
continue;
}
visited[i] = true;
permuteList.add(nums[i]);
backtracking(permuteList, permutes, visited, nums);
permuteList.remove(permuteList.size() - 1);
visited[i] = false;
}
}
```
## 6. 含有相同元素求排列
[47. Permutations II (Medium)](https://leetcode.com/problems/permutations-ii/description/)
```html
[1,1,2] have the following unique permutations:
[[1,1,2], [1,2,1], [2,1,1]]
```
数组元素可能含有相同的元素,进行排列时就有可能出现重复的排列,要求重复的排列只返回一个。
在实现上,和 Permutations 不同的是要先排序,然后在添加一个元素时,判断这个元素是否等于前一个元素,如果等于,并且前一个元素还未访问,那么就跳过这个元素。
```java
public List<List<Integer>> permuteUnique(int[] nums) {
List<List<Integer>> permutes = new ArrayList<>();
List<Integer> permuteList = new ArrayList<>();
Arrays.sort(nums); // 排序
boolean[] hasVisited = new boolean[nums.length];
backtracking(permuteList, permutes, hasVisited, nums);
return permutes;
}
private void backtracking(List<Integer> permuteList, List<List<Integer>> permutes, boolean[] visited, final int[] nums) {
if (permuteList.size() == nums.length) {
permutes.add(new ArrayList<>(permuteList));
return;
}
for (int i = 0; i < visited.length; i++) {
if (i != 0 && nums[i] == nums[i - 1] && !visited[i - 1]) {
continue; // 防止重复
}
if (visited[i]){
continue;
}
visited[i] = true;
permuteList.add(nums[i]);
backtracking(permuteList, permutes, visited, nums);
permuteList.remove(permuteList.size() - 1);
visited[i] = false;
}
}
```
## 7. 组合
[77. Combinations (Medium)](https://leetcode.com/problems/combinations/description/)
```html
If n = 4 and k = 2, a solution is:
[
[2,4],
[3,4],
[2,3],
[1,2],
[1,3],
[1,4],
]
```
```java
public List<List<Integer>> combine(int n, int k) {
List<List<Integer>> combinations = new ArrayList<>();
List<Integer> combineList = new ArrayList<>();
backtracking(combineList, combinations, 1, k, n);
return combinations;
}
private void backtracking(List<Integer> combineList, List<List<Integer>> combinations, int start, int k, final int n) {
if (k == 0) {
combinations.add(new ArrayList<>(combineList));
return;
}
for (int i = start; i <= n - k + 1; i++) { // 剪枝
combineList.add(i);
backtracking(combineList, combinations, i + 1, k - 1, n);
combineList.remove(combineList.size() - 1);
}
}
```
## 8. 组合求和
[39. Combination Sum (Medium)](https://leetcode.com/problems/combination-sum/description/)
```html
given candidate set [2, 3, 6, 7] and target 7,
A solution set is:
[[7],[2, 2, 3]]
```
```java
public List<List<Integer>> combinationSum(int[] candidates, int target) {
List<List<Integer>> combinations = new ArrayList<>();
backtracking(new ArrayList<>(), combinations, 0, target, candidates);
return combinations;
}
private void backtracking(List<Integer> tempCombination, List<List<Integer>> combinations,
int start, int target, final int[] candidates) {
if (target == 0) {
combinations.add(new ArrayList<>(tempCombination));
return;
}
for (int i = start; i < candidates.length; i++) {
if (candidates[i] <= target) {
tempCombination.add(candidates[i]);
backtracking(tempCombination, combinations, i, target - candidates[i], candidates);
tempCombination.remove(tempCombination.size() - 1);
}
}
}
```
## 9. 含有相同元素的组合求和
[40. Combination Sum II (Medium)](https://leetcode.com/problems/combination-sum-ii/description/)
```html
For example, given candidate set [10, 1, 2, 7, 6, 1, 5] and target 8,
A solution set is:
[
[1, 7],
[1, 2, 5],
[2, 6],
[1, 1, 6]
]
```
```java
public List<List<Integer>> combinationSum2(int[] candidates, int target) {
List<List<Integer>> combinations = new ArrayList<>();
Arrays.sort(candidates);
backtracking(new ArrayList<>(), combinations, new boolean[candidates.length], 0, target, candidates);
return combinations;
}
private void backtracking(List<Integer> tempCombination, List<List<Integer>> combinations,
boolean[] hasVisited, int start, int target, final int[] candidates) {
if (target == 0) {
combinations.add(new ArrayList<>(tempCombination));
return;
}
for (int i = start; i < candidates.length; i++) {
if (i != 0 && candidates[i] == candidates[i - 1] && !hasVisited[i - 1]) {
continue;
}
if (candidates[i] <= target) {
tempCombination.add(candidates[i]);
hasVisited[i] = true;
backtracking(tempCombination, combinations, hasVisited, i + 1, target - candidates[i], candidates);
hasVisited[i] = false;
tempCombination.remove(tempCombination.size() - 1);
}
}
}
```
## 10. 1-9 数字的组合求和
[216. Combination Sum III (Medium)](https://leetcode.com/problems/combination-sum-iii/description/)
```html
Input: k = 3, n = 9
Output:
[[1,2,6], [1,3,5], [2,3,4]]
```
从 1-9 数字中选出 k 个数不重复的数,使得它们的和为 n。
```java
public List<List<Integer>> combinationSum3(int k, int n) {
List<List<Integer>> combinations = new ArrayList<>();
List<Integer> path = new ArrayList<>();
backtracking(k, n, 1, path, combinations);
return combinations;