# Posts tagged as “hard”

You are given an array words of size n consisting of non-empty strings.

We define the score of a string word as the number of strings words[i] such that word is a prefix of words[i].

• For example, if words = ["a", "ab", "abc", "cab"], then the score of "ab" is 2, since "ab" is a prefix of both "ab" and "abc".

Return an array answer of size n where answer[i] is the sum of scores of every non-empty prefix of words[i].

Note that a string is considered as a prefix of itself.

Example 1:

Input: words = ["abc","ab","bc","b"]
Output: [5,4,3,2]
Explanation: The answer for each string is the following:
- "abc" has 3 prefixes: "a", "ab", and "abc".
- There are 2 strings with the prefix "a", 2 strings with the prefix "ab", and 1 string with the prefix "abc".
The total is answer[0] = 2 + 2 + 1 = 5.
- "ab" has 2 prefixes: "a" and "ab".
- There are 2 strings with the prefix "a", and 2 strings with the prefix "ab".
The total is answer[1] = 2 + 2 = 4.
- "bc" has 2 prefixes: "b" and "bc".
- There are 2 strings with the prefix "b", and 1 string with the prefix "bc".
The total is answer[2] = 2 + 1 = 3.
- "b" has 1 prefix: "b".
- There are 2 strings with the prefix "b".
The total is answer[3] = 2.


Example 2:

Input: words = ["abcd"]
Output: [4]
Explanation:
"abcd" has 4 prefixes: "a", "ab", "abc", and "abcd".
Each prefix has a score of one, so the total is answer[0] = 1 + 1 + 1 + 1 = 4.


Constraints:

• 1 <= words.length <= 1000
• 1 <= words[i].length <= 1000
• words[i] consists of lowercase English letters.

## Solution: Trie

Insert all the words into a tire whose node val is the number of substrings that have the current prefix.

During query time, sum up the values along the prefix path.

Time complexity: O(sum(len(word))
Space complexity: O(sum(len(word))

## C++

You are given an integer array nums and an integer k.

Find the longest subsequence of nums that meets the following requirements:

• The subsequence is strictly increasing and
• The difference between adjacent elements in the subsequence is at most k.

Return the length of the longest subsequence that meets the requirements.

subsequence is an array that can be derived from another array by deleting some or no elements without changing the order of the remaining elements.

Example 1:

Input: nums = [4,2,1,4,3,4,5,8,15], k = 3
Output: 5
Explanation:
The longest subsequence that meets the requirements is [1,3,4,5,8].
The subsequence has a length of 5, so we return 5.
Note that the subsequence [1,3,4,5,8,15] does not meet the requirements because 15 - 8 = 7 is larger than 3.


Example 2:

Input: nums = [7,4,5,1,8,12,4,7], k = 5
Output: 4
Explanation:
The longest subsequence that meets the requirements is [4,5,8,12].
The subsequence has a length of 4, so we return 4.


Example 3:

Input: nums = [1,5], k = 1
Output: 1
Explanation:
The longest subsequence that meets the requirements is [1].
The subsequence has a length of 1, so we return 1.


Constraints:

• 1 <= nums.length <= 105
• 1 <= nums[i], k <= 105

## Solution: DP + Segment Tree | Max range query

Let dp[i] := length of LIS end with number i.
dp[i] = 1 + max(dp[i-k:i])

Naive dp takes O(n*k) time which will cause TLE.

We can use segment tree to speed up the max range query to log(m), where m is the max value of the array.

Time complexity: O(n*logm)
Space complexity: O(m)

## C++

A parentheses string is a non-empty string consisting only of '(' and ')'. It is valid if any of the following conditions is true:

• It is ().
• It can be written as AB (A concatenated with B), where A and B are valid parentheses strings.
• It can be written as (A), where A is a valid parentheses string.

You are given an m x n matrix of parentheses grid. A valid parentheses string path in the grid is a path satisfying all of the following conditions:

• The path starts from the upper left cell (0, 0).
• The path ends at the bottom-right cell (m - 1, n - 1).
• The path only ever moves down or right.
• The resulting parentheses string formed by the path is valid.

Return true if there exists a valid parentheses string path in the grid. Otherwise, return false.

Example 1:

Input: grid = [["(","(","("],[")","(",")"],["(","(",")"],["(","(",")"]]
Output: true
Explanation: The above diagram shows two possible paths that form valid parentheses strings.
The first path shown results in the valid parentheses string "()(())".
The second path shown results in the valid parentheses string "((()))".
Note that there may be other valid parentheses string paths.


Example 2:

Input: grid = [[")",")"],["(","("]]
Output: false
Explanation: The two possible paths form the parentheses strings "))(" and ")((". Since neither of them are valid parentheses strings, we return false.


Constraints:

• m == grid.length
• n == grid[i].length
• 1 <= m, n <= 100
• grid[i][j] is either '(' or ')'.

## Solution: DP

Let dp(i, j, b) denote whether there is a path from (i,j) to (m-1, n-1) given b open parentheses.
if we are at (m – 1, n – 1) and b == 0 then we found a valid path.
dp(i, j, b) = dp(i + 1, j, b’) or dp(i, j + 1, b’) where b’ = b + 1 if grid[i][j] == ‘(‘ else -1

Time complexity: O(m*n*(m + n))
Space complexity: O(m*n*(m + n))

## Python3

You are given a 0-indexed 2D integer array flowers, where flowers[i] = [starti, endi] means the ith flower will be in full bloom from starti to endi (inclusive). You are also given a 0-indexed integer array persons of size n, where persons[i] is the time that the ith person will arrive to see the flowers.

Return an integer array answer of size n, where answer[i] is the number of flowers that are in full bloom when the ith person arrives.

Example 1:

Input: flowers = [[1,6],[3,7],[9,12],[4,13]], persons = [2,3,7,11]
Output: [1,2,2,2]
Explanation: The figure above shows the times when the flowers are in full bloom and when the people arrive.
For each person, we return the number of flowers in full bloom during their arrival.


Example 2:

Input: flowers = [[1,10],[3,3]], persons = [3,3,2]
Output: [2,2,1]
Explanation: The figure above shows the times when the flowers are in full bloom and when the people arrive.
For each person, we return the number of flowers in full bloom during their arrival.


Constraints:

• 1 <= flowers.length <= 5 * 104
• flowers[i].length == 2
• 1 <= starti <= endi <= 109
• 1 <= persons.length <= 5 * 104
• 1 <= persons[i] <= 109

## Solution: Prefix Sum + Binary Search

Use a treemap to store the counts (ordered by time t), when a flower begins to bloom at start, we increase m[start], when it dies at end, we decrease m[end+1]. prefix_sum[t] indicates the # of blooming flowers at time t.

For each people, use binary search to find the latest # of flowers before his arrival.

Time complexity: O(nlogn + mlogn)
Space complexity: O(n)

## C++

There is an undirected graph with n nodes, numbered from 0 to n - 1.

You are given a 0-indexed integer array scores of length n where scores[i] denotes the score of node i. You are also given a 2D integer array edges where edges[i] = [ai, bi] denotes that there exists an undirected edge connecting nodes ai and bi.

A node sequence is valid if it meets the following conditions:

• There is an edge connecting every pair of adjacent nodes in the sequence.
• No node appears more than once in the sequence.

The score of a node sequence is defined as the sum of the scores of the nodes in the sequence.

Return the maximum score of a valid node sequence with a length of 4If no such sequence exists, return -1.

Example 1:

Input: scores = [5,2,9,8,4], edges = [[0,1],[1,2],[2,3],[0,2],[1,3],[2,4]]
Output: 24
Explanation: The figure above shows the graph and the chosen node sequence [0,1,2,3].
The score of the node sequence is 5 + 2 + 9 + 8 = 24.
It can be shown that no other node sequence has a score of more than 24.
Note that the sequences [3,1,2,0] and [1,0,2,3] are also valid and have a score of 24.
The sequence [0,3,2,4] is not valid since no edge connects nodes 0 and 3.


Example 2:

Input: scores = [9,20,6,4,11,12], edges = [[0,3],[5,3],[2,4],[1,3]]
Output: -1
Explanation: The figure above shows the graph.
There are no valid node sequences of length 4, so we return -1.


Constraints:

• n == scores.length
• 4 <= n <= 5 * 104
• 1 <= scores[i] <= 108
• 0 <= edges.length <= 5 * 104
• edges[i].length == 2
• 0 <= ai, bi <= n - 1
• ai != bi
• There are no duplicate edges.

## Solution: Greedy / Top3 neighbors

Since |E| is already 5*104, we can’t enumerate all possible sequences. We must do in O(|E|) or O(|E|log|E|).

Enumerate all the edges, we have a pair of node a, b. To get the optimal answer, we just need to find the largest neighbor of a and b, which we call c, d respectively. Just need to make sure a, b, c, d are unique. i.e. c != d, c != b and d != a. Since the a’s largest neighbor can be either b or d. We can’t just store the largest neighbor, but top 3 instead for each node to avoid duplications.

Time complexity: O(|E|*9)
Space complexity: O(|V|*3)