# Problem

You have an initial power P, an initial score of 0 points, and a bag of tokens.

Each token can be used at most once, has a value token[i], and has potentially two ways to use it.

• If we have at least token[i] power, we may play the token face up, losing token[i] power, and gaining 1 point.
• If we have at least 1 point, we may play the token face down, gaining token[i]power, and losing 1 point.

Return the largest number of points we can have after playing any number of tokens.

Example 1:

Input: tokens = [100], P = 50
Output: 0


Example 2:

Input: tokens = [100,200], P = 150
Output: 1


Example 3:

Input: tokens = [100,200,300,400], P = 200
Output: 2


Note:

1. tokens.length <= 1000
2. 0 <= tokens[i] < 10000
3. 0 <= P < 10000

# Solution: Greedy + Two Pointers

Sort the tokens, gain points from the low end gain power from the high end.

Time complexity: O(nlogn)

Space complexity: O(1)

# Problem

On a 2D plane, we place stones at some integer coordinate points.  Each coordinate point may have at most one stone.

Now, a move consists of removing a stone that shares a column or row with another stone on the grid.

What is the largest possible number of moves we can make?

Example 1:

Input: stones = [[0,0],[0,1],[1,0],[1,2],[2,1],[2,2]]
Output: 5


Example 2:

Input: stones = [[0,0],[0,2],[1,1],[2,0],[2,2]]
Output: 3


Example 3:

Input: stones = [[0,0]]
Output: 0


Note:

1. 1 <= stones.length <= 1000
2. 0 <= stones[i][j] < 10000

# Solution 2: Union Find

Find all connected components (islands)

Ans = # of stones – # of islands

# Problem

Given two sequences pushed and popped with distinct values, return true if and only if this could have been the result of a sequence of push and pop operations on an initially empty stack.

Example 1:

Input: pushed = [1,2,3,4,5], popped = [4,5,3,2,1]
Output: true
Explanation: We might do the following sequence:
push(1), push(2), push(3), push(4), pop() -> 4,
push(5), pop() -> 5, pop() -> 3, pop() -> 2, pop() -> 1


Example 2:

Input: pushed = [1,2,3,4,5], popped = [4,3,5,1,2]
Output: false
Explanation: 1 cannot be popped before 2.


Note:

1. 0 <= pushed.length == popped.length <= 1000
2. 0 <= pushed[i], popped[i] < 1000
3. pushed is a permutation of popped.
4. pushed and popped have distinct values.

# Solution: Simulation

Simulate the push/pop operation.

Push element from |pushed sequence| onto stack s one by one and pop when top of the stack s is equal the current element in the |popped sequence|.

Time complexity: O(n)

Space complexity: O(n)

# Problem

Given an array of integers A, a move consists of choosing any A[i], and incrementing it by 1.

Return the least number of moves to make every value in A unique.

Example 1:

Input: [1,2,2]
Output: 1
Explanation:  After 1 move, the array could be [1, 2, 3].


Example 2:

Input: [3,2,1,2,1,7]
Output: 6
Explanation:  After 6 moves, the array could be [3, 4, 1, 2, 5, 7].
It can be shown with 5 or less moves that it is impossible for the array to have all unique values.


Note:

1. 0 <= A.length <= 40000
2. 0 <= A[i] < 40000

# Solution: Greedy

Sort the elements, make sure A[i] >= A[i-1] + 1, if not increase A[i] to A[i – 1] + 1

Time complexity: O(nlogn)

Space complexity: O(1)

# 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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