Given an array of integers nums and a positive integer k, check whether it is possible to divide this array into sets of k consecutive numbers.
Return true if it is possible. Otherwise, return false.
Example 1:
Input: nums = [1,2,3,3,4,4,5,6], k = 4 Output: true Explanation: Array can be divided into [1,2,3,4] and [3,4,5,6].
Example 2:
Input: nums = [3,2,1,2,3,4,3,4,5,9,10,11], k = 3 Output: true Explanation: Array can be divided into [1,2,3] , [2,3,4] , [3,4,5] and [9,10,11].
Example 3:
Input: nums = [1,2,3,4], k = 3 Output: false Explanation: Each array should be divided in subarrays of size 3.
Constraints:
1 <= k <= nums.length <= 1051 <= nums[i] <= 109Note: This question is the same as 846: https://leetcode.com/problems/hand-of-straights/
This approach involves breaking the problem into overlapping subproblems, solving each just once, and storing their solutions - optimal substructure. It is efficient for problems with optimal substructure and overlapping subproblems.
This C code uses dynamic programming to solve a Fibonacci-like problem. It initializes an array 'dp' to store solutions of subproblems and then recursively fills this array with values.
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Time Complexity: O(n), Space Complexity: O(n)
This approach is an optimization of the dynamic programming approach, aiming to reduce space complexity by storing only the last two results needed to compute the current state instead of the entire array.
This C code reduces the space complexity by maintaining only the last two calculated values, utilizing simple variables instead of an array.
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Time Complexity: O(n), Space Complexity: O(1)
| Approach | Complexity |
|---|---|
| Dynamic Programming Approach | Time Complexity: O(n), Space Complexity: O(n) |
| Space Optimized Dynamic Programming | Time Complexity: O(n), Space Complexity: O(1) |
Leetcode 128 - LONGEST CONSECUTIVE SEQUENCE • NeetCode • 455,447 views views
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