Leetcode算法解析51-100

<center>#51 N-Queens</center>

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  • Description:
    • The n-queens puzzle is the problem of placing n queens on an n×n chessboard such that no two queens attack each other.
    • avator
  • Input: 4
  • Output: [[".Q..", // Solution 1 "...Q", "Q...", "..Q."], ["..Q.", // Solution 2 "Q...", "...Q", ".Q.."]]
  • Solution:
    • dfs尋找組合的問題, 注意保存每一點(diǎn)的坐標(biāo)信息
    • 規(guī)則是不能在同一行或者同一列或者對(duì)角線上
    • 可以通過二元組存坐標(biāo)信息,也可以直接通過數(shù)組,數(shù)組索引做x, 值做y
  • Code:
    # code block
    public List<List<String>> solveNQueens(int n) {
        List<List<String>> result = new ArrayList<>();
        if (n <= 0) {
            return result;
        }
        dfsHelper(n, 0, new ArrayList<Integer>(), result);
        return result;
    }
    
    private void dfsHelper(int n, int x, List<Integer> state, List<List<String>> result) {
        if (n == x) {
            generateSolution(state, n, result);
            return;
        }
        for (int i = 0; i < n; i++) {
            if (valid(x, i, state)) {
                state.add(i);
                dfsHelper(n, x + 1, state, result);
                state.remove(state.size() - 1);
            }
        }
    }
    
    private boolean valid(int x, int y, List<Integer> state) {
        for (int i = 0; i < state.size(); i++) {
            if (y == state.get(i)) {
                return false;
            }
            if (Math.abs(y - state.get(i)) == Math.abs(x - i)) {
                return false;
            }
        }
        return true;
    }
    
    private void generateSolution(List<Integer> state, int n, List<List<String>> result) {
        List<String> solution = new ArrayList<>();
        for (Integer x : state) {
            StringBuilder sb = new StringBuilder();
            for (int i = 0; i < x; i++) {
                sb.append(".");
            }
            sb.append("Q");
            for (int i = x + 1; i < n; i++) {
                sb.append(".");
            }
            solution.add(sb.toString());
        }
        result.add(solution);
    }
    

<center>#52 N-Queens II</center>

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  • Description:
    • Follow up for N-Queens problem.
    • Now, instead outputting board configurations, return the total number of distinct solutions.
  • Input: 5
  • Output: 10
  • Solution:
    • N Queens 的follow up, 用一個(gè)全局的計(jì)數(shù)器計(jì)算組合就行
  • Code:
    # code block
    class Solution {
        public int totalNQueens(int n) {
            if (n <= 0) {
                return 0;
            }
            dfsHelper(n, 0, new ArrayList<Integer>());
            return result;
        }
    
        private void dfsHelper(int n, int x, List<Integer> state) {
            if (n == x) {
                result++;
                return;
            }
            for (int i = 0; i < n; i++) {
                if (valid(x, i, state)) {
                    state.add(i);
                    dfsHelper(n, x + 1, state);
                    state.remove(state.size() - 1);
                }
            }
        }
    
        private boolean valid(int x, int y, List<Integer> state) {
            for (int i = 0; i < state.size(); i++) {
                if (y == state.get(i)) {
                    return false;
                }
                if (Math.abs(y - state.get(i)) == Math.abs(x - i)) {
                    return false;
                }
            }
            return true;
        }
    
        private int result = 0;
    }
    

<center>#53 Maximum Subarray</center>

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  • Description:

    • Find the contiguous subarray within an array (containing at least one number) which has the largest sum.
  • Input: [-2,1,-3,4,-1,2,1,-5,4]

  • Output: 6

  • Assumptions:

    • containing at least one number
  • Solution:

    • 使用preSum的典型題。Sum(i, j) = Sum(0, j) - Sum(0, i - 1);
    • 邊界情況的處理, max 初始值設(shè)為最小int肯定會(huì)被更新, preMin設(shè)為0確保了最少包含一個(gè)值,刻意應(yīng)付全部都是負(fù)數(shù)的corner case。
  • Code:

    # code block
    public int maxSubArray(int[] nums) {
        if (nums == null || nums.length == 0) {
            return -1;
        }
        int max = Integer.MIN_VALUE;
        int preSum = 0;
        int preMin = 0;
        for (int i = 0; i < nums.length; i++) {
            preSum += nums[i];
            max = Math.max(max, preSum - preMin);
            preMin = Math.min(preMin, preSum);
        }
        return max;
    }
    
    
  • Time Complexity: O(n)

  • Space Complexity: O(1)

<center>#55 Jump Game</center>

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  • Description:
    • Given an array of non-negative integers, you are initially positioned at the first index of the array.
    • Each element in the array represents your maximum jump length at that position.
    • Determine if you are able to reach the last index.
  • Input: [2,3,1,1,4]
  • Output: true
  • Assumptions:
    • non-negative integers
  • Solution:
    • 貪心法。 每到達(dá)一個(gè)能到達(dá)的點(diǎn),都去刷新所能到的最遠(yuǎn)距離,最后比較能到的最遠(yuǎn)距離和最后一個(gè)元素的索引。
  • Code:
    # code block
    public boolean canJump(int[] nums) {
        if (nums == null || nums.length == 0) {
            return true;
        }
        int reach = 0;
        for (int i = 0; i < nums.length; i++) {
            if (i <= reach) {
                reach = Math.max(reach, i + nums[i]);
            }
        }
        return reach >= nums.length - 1 ? true : false;
    }
    
    
  • Time Complexity: O(n)
  • Space Complexity: O(1)

<center>#58 Length of Last Word</center>

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  • Description:
    • Given a string s consists of upper/lower-case alphabets and empty space characters ' ', return the length of last word in the string.
  • Input: s = "Hello World"
  • Output: 5
  • Assumptions:
    • If the last word does not exist, return 0.
  • Solution:
    • 模擬題,注意處理boundary case
  • Code:
    # code block
    public int lengthOfLastWord(String s) {
        if (s == null || s.length() == 0) {
            return 0;
        }
        String tmp = s.trim();
        int length = 0;
        char[] tc = tmp.toCharArray();
        for (int i = tc.length - 1; i >= 0; i--) {
            if (Character.isLetter(tc[i])) {
                length++;
            } else {
                break;
            }
        }
        return length;
    }
    
  • Time Complexity: O(n)

<center>#60 Permutation Sequence</center>

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  • Description:
    • The set [1,2,3,…,n] contains a total of n! unique permutations.
    • By listing and labeling all of the permutations in order,
    • We get the following sequence (ie, for n = 3):
      "123"
      "132"
      "213"
      "231"
      "312"
      "321"
    
    • Given n and k, return the kth permutation sequence.
  • Input: 3, 2
  • Output: 132
  • Assumptions:
    • Given n will be between 1 and 9 inclusive.
  • Solution:
    • 暴力的解法是使用DFS遍歷并計(jì)數(shù),時(shí)間復(fù)雜度過高
    • 遇到permutation的題第一件事先把圖畫出來
    • 可以找到規(guī)律,每一層節(jié)點(diǎn)為根的樹有m!個(gè)叉,根據(jù)這個(gè)可以判斷每層分別是哪個(gè)數(shù)
  • Code:
    # code block
    public String getPermutation(int n, int k) {
        if (n == 1) {
            return "1";
        }
        int[] factor = new int[n + 1];
        factor[0] = 1;
        for (int i = 1; i <= n; i++) {
            factor[i] = factor[i - 1] * i;
        }
        k = (k - 1) % factor[n];
        StringBuilder sb = new StringBuilder();
        boolean[] flag = new boolean[n];
        for (int i = n - 1; i >= 0; i--) {
            int idx = k / factor[i];
            sb.append(getNth(idx, flag));
            k -= factor[i] * idx;
        }
        return sb.toString();
    }
    
    private int getNth(int idx, boolean[] flag) {
        int count = idx;
        int i = 0;
        while (i < flag.length) {
            if (flag[i]) {
                i++;
                continue;
            }
            if (count == 0) {
                flag[i] = true;
                return i + 1;
            }
            i++;
            count--;
        }
        return -1;
    }
    
  • Time Complexity: O(n ^ 2)
  • Space Complexity: O(n)

<center>#61 Rotate List</center>

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  • Description:
    • Given a list, rotate the list to the right by k places, where k is non-negative.
  • Input: 1->2->3->4->5->NULL k=2
  • Output: 4->5->1->2->3->NULL
  • Solution:
    • 注意各種corner case 的處理
  • Code:
    # code block
    public ListNode rotateRight(ListNode head, int k) {
        if (head == null || head.next == null) {
            return head;
        }
        ListNode last = head;
        int length = 1;
        while (last.next != null) {
            length++;
            last = last.next;
        }
        k = k % length;
        if (k == 0) {
            return head;
        }
        int cut = length - k;
        ListNode prev = head;
        for (int i = 0; i < cut - 1; i++) {
            prev = prev.next;
        }
        ListNode next = prev.next;
        // n1->...->prev->next->...->nLast
        // next->...->nLast->n1->...->prev
        prev.next = null;
        last.next = head;
        return next;
    }
    
  • Time Complexity: O(n)
  • Space Complexity: O(1)

<center>#66 Plus One</center>

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  • Description:
    • Given a non-negative integer represented as a non-empty array of digits, plus one to the integer.
  • Input: [9,9,9]
  • Output: [1,0,0,0]
  • Assumptions:
    • assume the integer do not contain any leading zero, except the number 0 itself.
      • The digits are stored such that the most significant digit is at the head of the list.
  • Solution:
    • 本題最重要的是考慮到各種corner case的處理。比如加完之后大于10的進(jìn)位, 比如999加一會(huì)答案位數(shù)會(huì)發(fā)生改變。
  • Code:
    # code block
    public int[] plusOne(int[] digits) {
        if (digits == null || digits.length == 0) {
            return digits;
        }
        int carrier = 1;
        for (int i = digits.length - 1; i >= 0; i--) {
            int val = digits[i] + carrier;
            digits[i] = val % 10;
            carrier = val / 10;
        }
        if (carrier == 0) {
            return digits;
        }
        // one more digit than digits array
        int[] result = new int[digits.length + 1];
        result[0] = 1;
        for (int i = 0; i < digits.length; i++) {
            result[i + 1] = digits[i];
        }
        return result;
    }
    
  • Time Complexity: O(n)
  • Space Complexity: O(1)

<center>#67 Add Binary</center>

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  • Description:
    • Given two binary strings, return their sum (also a binary string).
  • Input: a = "11" b = "1"
  • Output: "100"
  • Solution:
    • 注意邊界條件判斷
    • 思路很簡(jiǎn)單,注意進(jìn)位不要忽略
  • Code:
    # code block
    public String addBinary(String a, String b) {
        if (a == null || a.length() == 0) {
            return b;
        }
        if (b == null || b.length() == 0) {
            return a;
        }
        StringBuilder sb = new StringBuilder();
        int idx_a = a.length() - 1, idx_b = b.length() - 1;
        int carrier = 0;
        while (idx_a >= 0 && idx_b >= 0) {
            int val = a.charAt(idx_a) - '0' + b.charAt(idx_b) - '0' + carrier;
            sb.append(val % 2);
            carrier = val / 2;
            idx_a--;
            idx_b--;
        }
        while (idx_a >= 0) {
            int val = a.charAt(idx_a) - '0' + carrier;
            sb.append(val % 2);
            carrier = val / 2;
            idx_a--;
        }
        while (idx_b >= 0) {
            int val = b.charAt(idx_b) - '0' + carrier;
            sb.append(val % 2);
            carrier = val / 2;
            idx_b--;
        }
        if (carrier != 0) {
            sb.append(carrier);
        }
        return sb.reverse().toString();
    }
    
  • Time Complexity: O(m + n)
  • Space Complexity: O(1)

<center>#69 Sqrt(x)</center>

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  • Description:
    • Implement int sqrt(int x).
  • Input: 2147483647
  • Output: 46340
  • Solution:
    • 這是一道二分法求答案的題,二分的范圍不是很直接
    • 這題最重要的是考慮了overflow的情況
  • Code:
    # code block
    public int mySqrt(int x) {
        if (x <= 0) {
            return 0;
        }
        long start = 1, end = x;
        while (start < end - 1) {
            long mid = start + (end - start) / 2;
            if (mid * mid == x) {
                return (int)mid;
            } else if (mid * mid > x) {
                end = mid;
            } else {
                start = mid;
            }
        }
        if (end * end <= x) {
            return (int)end;
        }
        return (int)start;
    }
    
  • Time Complexity: O(lg n)
  • Space Complexity: O(1)

<center>#70 Climbing Stairs</center>

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  • Description:
    • You are climbing a stair case. It takes n steps to reach to the top.
    • Each time you can either climb 1 or 2 steps. In how many distinct ways can you climb to the top?
    • Given n will be a positive integer.
  • Input: 6
  • Output: 13
  • Solution:
    • 動(dòng)態(tài)規(guī)劃的入門題
    • 暴力解法使用搜索,會(huì)有大量重復(fù)計(jì)算
    • 每一步只與前兩步有關(guān),所以初始化一二步,之后不斷更新前兩步的值
  • Code:
    # code block
    public int climbStairs(int n) {
        if (n == 0 || n == 1) {
            return 1;
        }
        int n_prev = 1;
        int n_curr = 1;
        for (int i = 2; i <= n; i++) {
            int n_next = n_prev + n_curr;
            n_prev = n_curr;
            n_curr = n_next;
        }
        return n_curr;
    }
    
  • Time Complexity: O(n)
  • Space Complexity: O(1)

<center>#75 Sort Colors</center>

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  • Description:

    • Given an array with n objects colored red, white or blue, sort them so that objects of the same color are adjacent, with the colors in the order red, white and blue.
    • Here, we will use the integers 0, 1, and 2 to represent the color red, white, and blue respectively
  • Input: [1,2,2,1,1,0]

  • Output:[0,1,1,1,2,2]

  • Assumptions:

    • You are not suppose to use the library's sort function for this problem.
  • Solution:

    • 典型的Partition題, 最簡(jiǎn)單的思路是先對(duì)0 和 大于 0 做一次partition, 對(duì)1和2做一次partition。這樣雖然時(shí)間復(fù)雜度依然是O(n), 但是還有一次遍歷的更優(yōu)方法。
    • 以下方法(Rainbow sort)中,區(qū)間[0, l)都是0, 區(qū)間(r, end]都是2. 根據(jù)該算法可以確定, [l, r)這個(gè)區(qū)間內(nèi)全是1. 當(dāng)跳出循環(huán)的時(shí)候i = r + 1, 可以確保[0, l) 是0, [l, i) 是1, [i, end]是2.
      因?yàn)橹槐闅v了一次,所以時(shí)間復(fù)雜度還是O(n), 空間復(fù)雜度O(1)。
  • Code:

    # code block
    public void sortColors(int[] nums) {
        if (nums == null || nums.length == 0) {
            return;
        }
        int l = 0, r = nums.length - 1;
        int i = 0;
        while (i <= r) {
            if (nums[i] == 0) {
                swap(nums, i, l);
                l++;
                i++;
            } else if (nums[i] == 1) {
                i++;
            } else {
                swap(nums, i, r);
                r--;
            }
        }
    }
    
    private void swap(int[] nums, int a, int b) {
        int tmp = nums[a];
        nums[a] = nums[b];
        nums[b] = tmp;
    }
    
    
  • Time Complexity: O(n)

  • Space Complexity: O(1)

<center>#77 Combinations</center>

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  • Description:
    • Given two integers n and k, return all possible combinations of k numbers out of 1 ... n.
  • Input: n = 4 and k = 2
  • Output: [[2,4],[3,4],[2,3],[1,2],[1,3],[1,4],]
  • Solution:
    • 注意邊界條件判斷
    • combination的變形
    • 因?yàn)殚L(zhǎng)度限定,所以可以剪枝優(yōu)化,優(yōu)化的地方用pluning注釋了
  • Code:
    # code block
    public List<List<Integer>> combine(int n, int k) {
        List<List<Integer>> result = new ArrayList<>();
        if (n < 1 || k > n) {
            return result;
        }
        dfsHelper(n, k, 1, new ArrayList<Integer>(), result);
        return result;
    }
    
    private void dfsHelper(int n, int k, int start, List<Integer> state, List<List<Integer>> result) {
        if (k == 0) {
            result.add(new ArrayList<Integer>(state));
            return;
        }
    
        for (int i = start; i <= n - k + 1; i++) {
            state.add(i);
            dfsHelper(n, k - 1, i + 1, state, result);
            state.remove(state.size() - 1);
        }
    }
    

<center>#78 Subsets</center>

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  • Description:
    • Given a set of distinct integers, nums, return all possible subsets.
  • Input: [1,2,3]
  • Output: [[],[1],[1,2],[1,2,3],[1,3],[2],[2,3],[3]]
  • Assumptions:
    • The solution set must not contain duplicate subsets.
  • Solution:
    • 子集問題就是隱式圖的深度優(yōu)先搜索遍歷。因?yàn)槭莇istinct,所以不需要去重。
  • Code:
    # code block
    public List<List<Integer>> subsets(int[] nums) {
         List<List<Integer>> result = new ArrayList<>();
         if (nums == null || nums.length == 0) {
             result.add(new ArrayList<Integer>());
             return result;
         }
         dfsHelper(nums, 0, new ArrayList<Integer>(), result);
         return result;
     }
    
     private void dfsHelper(int[] nums, int start, List<Integer> state, List<List<Integer>> result) {
         result.add(new ArrayList<Integer>(state));
         for (int i = start; i < nums.length; i++) {
             state.add(nums[i]);
             dfsHelper(nums, i + 1, state, result);
             state.remove(state.size() - 1);
         }
     }
    
    
  • Time Complexity: O(2 ^ n)
  • Space Complexity: O(n)

<center>#79 Word Search</center>

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  • Description:
    • Given a 2D board and a word, find if the word exists in the grid.
    • The word can be constructed from letters of sequentially adjacent cell, where "adjacent" cells are those horizontally or vertically neighboring. The same letter cell may not be used more than once.
  • Input: board = [
    ['A','B','C','E'],
    ['S','F','C','S'],
    ['A','D','E','E']
    ] word = "ABCCED"
  • Output: true
  • Assumptions:
  • Solution:
    • 典型的圖上的搜索題,因?yàn)橐阉魉械慕M合, 所以推薦使用DFS, 利用回溯,只需要維持一個(gè)狀態(tài)
    • 注意點(diǎn)
      • 圖上的遍歷問題可以利用dx, dy數(shù)組來優(yōu)化代碼
      • 把判斷是否在邊界內(nèi)寫成一個(gè)私有函數(shù)來優(yōu)化代碼
      • 遞歸的出口的選擇
  • Code:
# code block
class Solution {
    public static final int[] dx = {1, 0, 0, -1};
    public static final int[] dy = {0, 1, -1, 0};
    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;
        }
        int m = board.length, n = board[0].length;
        char[] wc = word.toCharArray();
        for (int i = 0; i < m; i++) {
            for (int j = 0; j < n; j++) {
                boolean[][] visited = new boolean[m][n];
                if (board[i][j] != wc[0]) {
                    continue;
                }
                if (dfsHelper(board, wc, visited, i, j, 0)) {
                    return true;
                }
            }
        }
        return false;
    }

    private boolean dfsHelper(char[][] board, char[] wc, boolean[][] visited, int x, int y, int start) {
        if (visited[x][y]) {
            return false;
        }
        if (wc[start] != board[x][y]) {
            return false;
        }
        if (start == wc.length - 1) {
            // find the word
            return true;
        }
        visited[x][y] = true;
        for (int i = 0; i < 4; i++) {
            if (valid(x + dx[i], y + dy[i], board, visited) && dfsHelper(board, wc, visited, x + dx[i], y + dy[i], start + 1)) {
                return true;
            }
        }
        visited[x][y] = false;
        return false;
    }

    private boolean valid(int x, int y, char[][] board, boolean[][] visited) {
        return x >= 0 && x < board.length && y >= 0 && y < board[0].length && !visited[x][y];
    }
}
  • Time Complexity: O(m * n)
    • DFS的時(shí)間復(fù)雜度是邊的個(gè)數(shù)
  • Space Complexity: O(m ^ 2 * n ^ 2)
    • 判斷是否訪問過的boolean數(shù)組,worst case 可能有 n ^ 2個(gè)

<center>#80 Remove Duplicates from Sorted Array II</center>

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  • Description:
    • Follow up for "Remove Duplicates":
    • What if duplicates are allowed at most twice?
  • Input: [1,1,2,2,2,3,3,3]
  • Output: [1,1,2,2,3,3]
  • Solution:
    • 去重,但是每個(gè)元素可以保留兩個(gè),實(shí)現(xiàn)的方法不止一種,但是要考慮到改變了數(shù)組中的值是否會(huì)對(duì)后續(xù)判斷產(chǎn)生影響。
  • Code:
    # code block
    public int removeDuplicates(int[] nums) {
        if (nums == null || nums.length == 0) {
            return 0;
        }
        int idx = 0;
        int i = 0;
        while (i < nums.length) {
            int val = nums[i];
            int count = 0;
            while (i < nums.length && nums[i] == val) {
                i++;
                count++;
            }
            for (int j = 0; j < 2 && j < count; j++) {
                nums[idx++] = val;
            }
        }
        return idx;
    }
    
    
  • Time Complexity: O(n)
  • Space Complexity: O(1)

<center>#83 Remove Duplicates from Sorted List</center>

  • link
  • Description:
    • Given a sorted linked list, delete all duplicates such that each element appear only once.
  • Input: 1->1->2
  • Output: 1->2
  • Solution:
    • 基礎(chǔ)的鏈表去重題,注意指針的賦值
  • Code:
    # code block
    public ListNode deleteDuplicates(ListNode head) {
      if (head == null) {
          return head;
      }
      ListNode dummy = new ListNode(0);
      dummy.next = head;
      while (head.next != null) {
          if (head.next.val == head.val) {
              head.next = head.next.next;
          } else {
              head = head.next;
          }
      }
      return dummy.next;
    

}

* Time Complexity: O(n)
* Space Complexity: O(1)
### <center>#86 Partition List</center>
* [link](https://leetcode.com/problems/partition-list/description/)
* Description:
* Given a linked list and a value x, partition it such that all nodes less than x come before nodes greater than or equal to x.
* You should preserve the original relative order of the nodes in each of the two partitions.
* Input: 1->4->3->2->5->2 and x = 3
* Output: 1->2->2->4->3->5
* Solution:
* 簡(jiǎn)單鏈表題,注意使用dummynode和指針賦值的先后問題
* Code:

code block

public ListNode partition(ListNode head, int x) {
ListNode dummy1 = new ListNode(0);
ListNode dummy2 = new ListNode(0);
ListNode curr1 = dummy1;
ListNode curr2 = dummy2;
while (head != null) {
if (head.val < x) {
curr1.next = head;
head = head.next;
curr1 = curr1.next;
curr1.next = null;
} else {
curr2.next = head;
head = head.next;
curr2 = curr2.next;
curr2.next = null;
}
}
curr1.next = dummy2.next;
return dummy1.next;
}

* Time Complexity: O(n)
* Space Complexity: O(1)
### <center>#88 Merge Sorted Array</center>
* [link](https://leetcode.com/problems/merge-sorted-array/description/)
* Description:
* Given two sorted integer arrays nums1 and nums2, merge nums2 into nums1 as one sorted array.
* Input: [4,5,6,0,0,0] 3 [1,2,3] 3
* Output: [1,2,3,4,5,6]
* Assumptions:
* You may assume that nums1 has enough space (size that is greater or equal to m + n) to hold additional elements from nums2. The number of elements initialized in nums1 and nums2 are m and n respectively.

* Solution:
*  用歸并排序的merge方法。不適用額外空間的方法就是從尾巴開始?xì)w并, 先把大的數(shù)填進(jìn)去
* Code:

code block

public void merge(int[] nums1, int m, int[] nums2, int n) {
int length = m + n;
int ptM = m - 1;
int ptN = n - 1;
int pt = length - 1;
while (pt >= 0) {
if (ptN < 0) {
//nums2 merge complete, nums1 can left as it is
break;
} else if (ptM < 0) {
nums1[pt] = nums2[ptN--];
} else if (nums1[ptM] > nums2[ptN]) {
nums1[pt] = nums1[ptM--];
} else {
nums1[pt] = nums2[ptN--];
}
pt--;
}
}

* Time Complexity: O(n)
* Space Complexity: O(1)
### <center>#90 Subsets II</center>
* [link](https://leetcode.com/problems/subsets-ii/description/)
* Description:
* Given a collection of integers that might contain duplicates, nums, return all possible subsets.
* The solution set must not contain duplicate subsets.
* Input: nums = [1,2,2]
* Output:
[
  [2],
  [1],
  [1,2,2],
  [2,2],
  [1,2],
  []
]
* Solution:
* 先排序,去重, 去重的地方注釋了remove duplicate
* 對(duì)subsets的隱式圖進(jìn)行遍歷,記錄下每一個(gè)狀態(tài)
* Code:

code block

public List<List<Integer>> subsetsWithDup(int[] nums) {
List<List<Integer>> subsets = new ArrayList<>();
if (nums == null || nums.length == 0) {
subsets.add(new ArrayList<Integer>());
return subsets;
}
Arrays.sort(nums);
dfsHelper(nums, 0, new ArrayList<Integer>(), subsets);
return subsets;
}

private void dfsHelper(int[] nums, int start, List<Integer> state, List<List<Integer>> subsets) {
subsets.add(new ArrayList<Integer>(state));
for (int i = start; i < nums.length; i++) {
// remove duplicate
if (i != start && nums[i] == nums[i - 1]) {
continue;
}
state.add(nums[i]);
dfsHelper(nums, i + 1, state, subsets);
state.remove(state.size() - 1);
}
}

* Time Complexity: O(n * 2 ^ n)
* Space Complexity: O(n)
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