# Posts tagged as “binary”

You are given a binary string binary consisting of only 0‘s or 1‘s. You can apply each of the following operations any number of times:

• Operation 1: If the number contains the substring "00", you can replace it with "10".
• For example, "00010" -> "10010
• Operation 2: If the number contains the substring "10", you can replace it with "01".
• For example, "00010" -> "00001"

Return the maximum binary string you can obtain after any number of operations. Binary string x is greater than binary string y if x‘s decimal representation is greater than y‘s decimal representation.

Example 1:

Input: binary = "000110"
Output: "111011"
Explanation: A valid transformation sequence can be:
"000110" -> "000101"
"000101" -> "100101"
"100101" -> "110101"
"110101" -> "110011"
"110011" -> "111011"


Example 2:

Input: binary = "01"
Output: "01"
Explanation: "01" cannot be transformed any further.


Constraints:

• 1 <= binary.length <= 105
• binary consist of '0' and '1'.

## Solution: Greedy + Counting

Leading 1s are good, no need to change them.
For the rest of the string
1. Apply operation 2 to make the string into 3 parts, leading 1s, middle 0s and tailing 1s.
e.g. 11010101 => 11001101 => 11001011 => 11000111
2. Apply operation 1 to make flip zeros to ones except the last one.
e.g. 11000111 => 11100111 => 11110111

There will be only one zero (if the input string is not all 1s) is the final largest string, the position of the zero is leading 1s + zeros – 1.

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

## C++

Your task is to form an integer array nums from an initial array of zeros arr that is the same size as nums.

Return the minimum number of function calls to make nums from arr.

The answer is guaranteed to fit in a 32-bit signed integer.

Example 1:

Input: nums = [1,5]
Output: 5
Explanation: Increment by 1 (second element): [0, 0] to get [0, 1] (1 operation).
Double all the elements: [0, 1] -> [0, 2] -> [0, 4] (2 operations).
Increment by 1 (both elements)  [0, 4] -> [1, 4] -> [1, 5] (2 operations).
Total of operations: 1 + 2 + 2 = 5.


Example 2:

Input: nums = [2,2]
Output: 3
Explanation: Increment by 1 (both elements) [0, 0] -> [0, 1] -> [1, 1] (2 operations).
Double all the elements: [1, 1] -> [2, 2] (1 operation).
Total of operations: 2 + 1 = 3.


Example 3:

Input: nums = [4,2,5]
Output: 6
Explanation: (initial)[0,0,0] -> [1,0,0] -> [1,0,1] -> [2,0,2] -> [2,1,2] -> [4,2,4] -> [4,2,5](nums).


Example 4:

Input: nums = [3,2,2,4]
Output: 7


Example 5:

Input: nums = [2,4,8,16]
Output: 8


Constraints:

• 1 <= nums.length <= 10^5
• 0 <= nums[i] <= 10^9

## Solution: count 1s

For 5 (101b), we can add 1s for 5 times which of cause isn’t the best way to generate 5, the optimal way is to [+1, *2, +1]. We have to add 1 for each 1 in the binary format. e.g. 11 (1011), we need 3x “+1” op, and 4 “*2” op. Fortunately, the “*2” can be shared/delayed, thus we just need to find the largest number.
e.g. [2,4,8,16]
[0, 0, 0, 0] -> [0, 0, 0, 1] -> [0, 0, 0, 2]
[0, 0, 0, 2] -> [0, 0, 1, 2] -> [0, 0, 2, 4]
[0, 0, 2, 4] -> [0, 1, 2, 4] -> [0, 2, 4, 8]
[0, 2, 4, 8] -> [1, 2, 4, 8] -> [2, 4, 8, 16]
ans = sum{count_1(arr_i)} + high_bit(max(arr_i))

Time complexity: O(n*log(max(arr_i))
Space complexity: O(1)

## Python3

Given a binary tree with the following rules:

1. root.val == 0
2. If treeNode.val == x and treeNode.left != null, then treeNode.left.val == 2 * x + 1
3. If treeNode.val == x and treeNode.right != null, then treeNode.right.val == 2 * x + 2

Now the binary tree is contaminated, which means all treeNode.val have been changed to -1.

You need to first recover the binary tree and then implement the FindElements class:

• FindElements(TreeNode* root) Initializes the object with a contamined binary tree, you need to recover it first.
• bool find(int target) Return if the target value exists in the recovered binary tree.

Example 1:

Input
["FindElements","find","find"]
[[[-1,null,-1]],[1],[2]]
Output


[null,false,true]

Explanation FindElements findElements = new FindElements([-1,null,-1]); findElements.find(1); // return False findElements.find(2); // return True

Example 2:

Input
["FindElements","find","find","find"]
[[[-1,-1,-1,-1,-1]],[1],[3],[5]]
Output


[null,true,true,false]

Explanation FindElements findElements = new FindElements([-1,-1,-1,-1,-1]); findElements.find(1); // return True findElements.find(3); // return True findElements.find(5); // return False

Example 3:

Input
["FindElements","find","find","find","find"]
[[[-1,null,-1,-1,null,-1]],[2],[3],[4],[5]]
Output


[null,true,false,false,true]

Explanation FindElements findElements = new FindElements([-1,null,-1,-1,null,-1]); findElements.find(2); // return True findElements.find(3); // return False findElements.find(4); // return False findElements.find(5); // return True

Constraints:

• TreeNode.val == -1
• The height of the binary tree is less than or equal to 20
• The total number of nodes is between [1, 10^4]
• Total calls of find() is between [1, 10^4]
• 0 <= target <= 10^6

## Solutoin 1: Recursion and HashSet

Time complexity: Recover O(n), find O(1)
Space complexity: O(n)

## Solution 2: Recursion and Binary format

The binary format of t = (target + 1) (from high bit to low bit, e.g. in reverse order) decides where to go at each node.
t % 2 == 1, go right, otherwise go left
t = t / 2 or t >>= 1

Time complexity: Recover O(n), find O(log|target|)
Space complexity: O(1)

## C++

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

Starting with a positive integer N, we reorder the digits in any order (including the original order) such that the leading digit is not zero.

Return true if and only if we can do this in a way such that the resulting number is a power of 2.

Example 1:

Input: 1
Output: true


Example 2:

Input: 10
Output: false


Example 3:

Input: 16
Output: true


Example 4:

Input: 24
Output: false


Example 5:

Note:

1. 1 <= N <= 10^9

# Solution: HashTable

Compare the counter of digit string with that of all power of 2s.

e.g. 64 -> {4: 1, 6: 1} == 46 {4:1, 6: 1}

Time complexity: O(1)

Space complexity: O(1)

C++