# Posts tagged as “search”

A certain bug’s home is on the x-axis at position x. Help them get there from position 0.

The bug jumps according to the following rules:

• It can jump exactly a positions forward (to the right).
• It can jump exactly b positions backward (to the left).
• It cannot jump backward twice in a row.
• It cannot jump to any forbidden positions.

The bug may jump forward beyond its home, but it cannot jump to positions numbered with negative integers.

Given an array of integers forbidden, where forbidden[i] means that the bug cannot jump to the position forbidden[i], and integers ab, and x, return the minimum number of jumps needed for the bug to reach its home. If there is no possible sequence of jumps that lands the bug on position x, return -1.

Example 1:

Input: forbidden = [14,4,18,1,15], a = 3, b = 15, x = 9
Output: 3
Explanation: 3 jumps forward (0 -> 3 -> 6 -> 9) will get the bug home.


Example 2:

Input: forbidden = [8,3,16,6,12,20], a = 15, b = 13, x = 11
Output: -1


Example 3:

Input: forbidden = [1,6,2,14,5,17,4], a = 16, b = 9, x = 7
Output: 2
Explanation: One jump forward (0 -> 16) then one jump backward (16 -> 7) will get the bug home.


Constraints:

• 1 <= forbidden.length <= 1000
• 1 <= a, b, forbidden[i] <= 2000
• 0 <= x <= 2000
• All the elements in forbidden are distinct.
• Position x is not forbidden.

## Solution: BFS

Normal BFS with two tricks:
1. For each position, we need to track whether it’s reached via a forward jump or backward jump
2. How far should we go? If we don’t limit, it can go forever which leads to TLE/MLE. We can limit the distance to 2*max_jump, e.g. 4000, that’s maximum distance we can jump back to home in one shot.

Time complexity: O(max_distance * 2)
Space complexity: O(max_distance * 2)

## C++

You are given a string s of even length consisting of digits from 0 to 9, and two integers a and b.

You can apply either of the following two operations any number of times and in any order on s:

• Add a to all odd indices of s (0-indexed). Digits post 9 are cycled back to 0. For example, if s = "3456" and a = 5s becomes "3951".
• Rotate s to the right by b positions. For example, if s = "3456" and b = 1s becomes "6345".

Return the lexicographically smallest string you can obtain by applying the above operations any number of times on s.

A string a is lexicographically smaller than a string b (of the same length) if in the first position where a and b differ, string a has a letter that appears earlier in the alphabet than the corresponding letter in b. For example, "0158" is lexicographically smaller than "0190" because the first position they differ is at the third letter, and '5' comes before '9'.

Example 1:

Input: s = "5525", a = 9, b = 2
Output: "2050"
Explanation: We can apply the following operations:
Start:  "5525"
Rotate: "2555"
Rotate: "5323"
​​​​​​​Rotate: "2151"
There is no way to obtain a string that is lexicographically smaller then "2050".


Example 2:

Input: s = "74", a = 5, b = 1
Output: "24"
Explanation: We can apply the following operations:
Start:  "74"
Rotate: "47"
​​​​​​​Rotate: "24"​​​​​​​​​​​​
There is no way to obtain a string that is lexicographically smaller then "24".


Example 3:

Input: s = "0011", a = 4, b = 2
Output: "0011"
Explanation: There are no sequence of operations that will give us a lexicographically smaller string than "0011".


Example 4:

Input: s = "43987654", a = 7, b = 3
Output: "00553311"


Constraints:

• 2 <= s.length <= 100
• s.length is even.
• s consists of digits from 0 to 9 only.
• 1 <= a <= 9
• 1 <= b <= s.length - 1

## C++

We have n buildings numbered from 0 to n - 1. Each building has a number of employees. It’s transfer season, and some employees want to change the building they reside in.

You are given an array requests where requests[i] = [fromi, toi] represents an employee’s request to transfer from building fromi to building toi.

All buildings are full, so a list of requests is achievable only if for each building, the net change in employee transfers is zero. This means the number of employees leaving is equal to the number of employees moving in. For example if n = 3 and two employees are leaving building 0, one is leaving building 1, and one is leaving building 2, there should be two employees moving to building 0, one employee moving to building 1, and one employee moving to building 2.

Return the maximum number of achievable requests.

Example 1:

Input: n = 5, requests = [[0,1],[1,0],[0,1],[1,2],[2,0],[3,4]]
Output: 5
Explantion: Let's see the requests:
From building 0 we have employees x and y and both want to move to building 1.
From building 1 we have employees a and b and they want to move to buildings 2 and 0 respectively.
From building 2 we have employee z and they want to move to building 0.
From building 3 we have employee c and they want to move to building 4.
From building 4 we don't have any requests.
We can achieve the requests of users x and b by swapping their places.
We can achieve the requests of users y, a and z by swapping the places in the 3 buildings.


Example 2:

Input: n = 3, requests = [[0,0],[1,2],[2,1]]
Output: 3
Explantion: Let's see the requests:
From building 0 we have employee x and they want to stay in the same building 0.
From building 1 we have employee y and they want to move to building 2.
From building 2 we have employee z and they want to move to building 1.
We can achieve all the requests. 

Example 3:

Input: n = 4, requests = [[0,3],[3,1],[1,2],[2,0]]
Output: 4


Constraints:

• 1 <= n <= 20
• 1 <= requests.length <= 16
• requests[i].length == 2
• 0 <= fromi, toi < n

## Solution: Combination

Try all combinations: O(2^n * (r + n))
Space complexity: O(n)

## Python3

Given a string s, return the maximum number of unique substrings that the given string can be split into.

You can split string s into any list of non-empty substrings, where the concatenation of the substrings forms the original string. However, you must split the substrings such that all of them are unique.

substring is a contiguous sequence of characters within a string.

Example 1:

Input: s = "ababccc"
Output: 5
Explanation: One way to split maximally is ['a', 'b', 'ab', 'c', 'cc']. Splitting like ['a', 'b', 'a', 'b', 'c', 'cc'] is not valid as you have 'a' and 'b' multiple times.


Example 2:

Input: s = "aba"
Output: 2
Explanation: One way to split maximally is ['a', 'ba'].


Example 3:

Input: s = "aa"
Output: 1
Explanation: It is impossible to split the string any further.


Constraints:

• 1 <= s.length <= 16
• s contains only lower case English letters.

## Solution: Brute Force

Try all combinations.
Time complexity: O(2^n)
Space complexity: O(n)

## DFS/C++

Given 2n balls of k distinct colors. You will be given an integer array balls of size k where balls[i] is the number of balls of color i

All the balls will be shuffled uniformly at random, then we will distribute the first n balls to the first box and the remaining n balls to the other box (Please read the explanation of the second example carefully).

Please note that the two boxes are considered different. For example, if we have two balls of colors a and b, and two boxes [] and (), then the distribution [a] (b) is considered different than the distribution [b] (a) (Please read the explanation of the first example carefully).

We want to calculate the probability that the two boxes have the same number of distinct balls.

Example 1:

Input: balls = [1,1]
Output: 1.00000
Explanation: Only 2 ways to divide the balls equally:
- A ball of color 1 to box 1 and a ball of color 2 to box 2
- A ball of color 2 to box 1 and a ball of color 1 to box 2
In both ways, the number of distinct colors in each box is equal. The probability is 2/2 = 1


Example 2:

Input: balls = [2,1,1]
Output: 0.66667
Explanation: We have the set of balls [1, 1, 2, 3]
This set of balls will be shuffled randomly and we may have one of the 12 distinct shuffles with equale probability (i.e. 1/12):
[1,1 / 2,3], [1,1 / 3,2], [1,2 / 1,3], [1,2 / 3,1], [1,3 / 1,2], [1,3 / 2,1], [2,1 / 1,3], [2,1 / 3,1], [2,3 / 1,1], [3,1 / 1,2], [3,1 / 2,1], [3,2 / 1,1]
After that we add the first two balls to the first box and the second two balls to the second box.
We can see that 8 of these 12 possible random distributions have the same number of distinct colors of balls in each box.
Probability is 8/12 = 0.66667


Example 3:

Input: balls = [1,2,1,2]
Output: 0.60000
Explanation: The set of balls is [1, 2, 2, 3, 4, 4]. It is hard to display all the 180 possible random shuffles of this set but it is easy to check that 108 of them will have the same number of distinct colors in each box.
Probability = 108 / 180 = 0.6


Example 4:

Input: balls = [3,2,1]
Output: 0.30000
Explanation: The set of balls is [1, 1, 1, 2, 2, 3]. It is hard to display all the 60 possible random shuffles of this set but it is easy to check that 18 of them will have the same number of distinct colors in each box.
Probability = 18 / 60 = 0.3


Example 5:

Input: balls = [6,6,6,6,6,6]
Output: 0.90327


Constraints:

• 1 <= balls.length <= 8
• 1 <= balls[i] <= 6
• sum(balls) is even.
• Answers within 10^-5 of the actual value will be accepted as correct.

## Solution 0: Permutation (TLE)

Enumerate all permutations of the balls, count valid ones and divide that by the total.

Time complexity: O((8*6)!) = O(48!)
After deduplication: O(48!/(6!)^8) ~ 1.7e38
Space complexity: O(8*6)

## Solution 1: Combination

For each color, put n_i balls into box1, the left t_i – n_i balls go to box2.
permutations = fact(n//2) / PROD(fact(n_i)) * fact(n//2) * PROD(fact(t_i – n_i))
E.g
balls = [1×2, 2×6, 3×4]
One possible combination:
box1: 1 22 333
box2: 1 2222 3
permutations = 6! / (1! * 2! * 3!) * 6! / (1! * 4! * 1!) = 1800

Time complexity: O((t+1)^k) = O(7^8)
Space complexity: O(k + (t*k)) = O(8 + 48)

vector version