# Posts published in “Search”

In a given grid, each cell can have one of three values:

• the value 0 representing an empty cell;
• the value 1 representing a fresh orange;
• the value 2 representing a rotten orange.

Every minute, any fresh orange that is adjacent (4-directionally) to a rotten orange becomes rotten.

Return the minimum number of minutes that must elapse until no cell has a fresh orange.  If this is impossible, return -1instead.

Example 1:

Input: [[2,1,1],[1,1,0],[0,1,1]]
Output: 4


Example 2:

Input: [[2,1,1],[0,1,1],[1,0,1]]
Output: -1
Explanation:  The orange in the bottom left corner (row 2, column 0) is never rotten, because rotting only happens 4-directionally.


Example 3:

Input: [[0,2]]
Output: 0
Explanation:  Since there are already no fresh oranges at minute 0, the answer is just 0.


Note:

1. 1 <= grid.length <= 10
2. 1 <= grid[0].length <= 10
3. grid[i][j] is only 01, or 2.

## Solution: BFS

Time complexity: O(mn)
Space complexity: O(mn)

## C++

On a 2-dimensional grid, there are 4 types of squares:

• 1 represents the starting square.  There is exactly one starting square.
• 2 represents the ending square.  There is exactly one ending square.
• 0 represents empty squares we can walk over.
• -1 represents obstacles that we cannot walk over.

Return the number of 4-directional walks from the starting square to the ending square, that walk over every non-obstacle square exactly once.

Example 1:

Input: [[1,0,0,0],[0,0,0,0],[0,0,2,-1]]
Output: 2
Explanation: We have the following two paths:
1. (0,0),(0,1),(0,2),(0,3),(1,3),(1,2),(1,1),(1,0),(2,0),(2,1),(2,2)
2. (0,0),(1,0),(2,0),(2,1),(1,1),(0,1),(0,2),(0,3),(1,3),(1,2),(2,2)

Example 2:

Input: [[1,0,0,0],[0,0,0,0],[0,0,0,2]]
Output: 4
Explanation: We have the following four paths:
1. (0,0),(0,1),(0,2),(0,3),(1,3),(1,2),(1,1),(1,0),(2,0),(2,1),(2,2),(2,3)
2. (0,0),(0,1),(1,1),(1,0),(2,0),(2,1),(2,2),(1,2),(0,2),(0,3),(1,3),(2,3)
3. (0,0),(1,0),(2,0),(2,1),(2,2),(1,2),(1,1),(0,1),(0,2),(0,3),(1,3),(2,3)
4. (0,0),(1,0),(2,0),(2,1),(1,1),(0,1),(0,2),(0,3),(1,3),(1,2),(2,2),(2,3)

Example 3:

Input: [[0,1],[2,0]]
Output: 0
Explanation:
There is no path that walks over every empty square exactly once.
Note that the starting and ending square can be anywhere in the grid.


Note:

1. 1 <= grid.length * grid[0].length <= 20

count how many empty blocks there are and try all possible paths to end point and check whether we visited every empty blocks or not.

## Problem

Return all non-negative integers of length N such that the absolute difference between every two consecutive digits is K.

Note that every number in the answer must not have leading zeros except for the number 0 itself. For example, 01 has one leading zero and is invalid, but 0 is valid.

You may return the answer in any order.

Example 1:

Input: N = 3, K = 7
Output: [181,292,707,818,929]
Explanation: Note that 070 is not a valid number, because it has leading zeroes.


Example 2:

Input: N = 2, K = 1
Output: [10,12,21,23,32,34,43,45,54,56,65,67,76,78,87,89,98]

Note:

1. 1 <= N <= 9
2. 0 <= K <= 9

## Solution: Search

Time complexity: O(2^N)
Space complexity: O(N)

## C++/BFS

Given a set of distinct integers, nums, return all possible subsets (the power set).

Note: The solution set must not contain duplicate subsets.

Example:

Input: nums = [1,2,3]Output:[  [3],  [1],  [2],  [1,2,3],  [1,3],  [2,3],  [1,2],  []]

# Solution: Combination

Time complexity: O(2^n)
Space complexity: O(n)

# Problem

Given an array A of strings, find any smallest string that contains each string in A as a substring.

We may assume that no string in A is substring of another string in A.

Example 1:

Input: ["alex","loves","leetcode"]
Output: "alexlovesleetcode"
Explanation: All permutations of "alex","loves","leetcode" would also be accepted.


Example 2:

Input: ["catg","ctaagt","gcta","ttca","atgcatc"]
Output: "gctaagttcatgcatc"

Note:

1. 1 <= A.length <= 12
2. 1 <= A[i].length <= 20

# Solution 1: Search + Pruning

Try all permutations. Pre-process the cost from word[i] to word[j] and store it in g[i][j].

Time complexity: O(n!)

Space complexity: O(n)

# Solution 2: DP

g[i][j] is the cost of appending word[j] after word[i], or weight of edge[i][j].

We would like find the shortest path to visit each node from 0 to n – 1 once and only once this is called the Travelling sells man’s problem which is NP-Complete.

We can solve it with DP that uses exponential time.

dp[s][i] := min distance to visit nodes (represented as a binary state s) once and only once and the path ends with node i.

e.g. dp[7][1] is the min distance to visit nodes (0, 1, 2) and ends with node 1, the possible paths could be (0, 2, 1), (2, 0, 1).

Time complexity: O(n^2 * 2^n)

Space complexity: O(n * 2^n)

## C++

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