In the Count the Number of Good Subarrays coding problem, you are given an array nums and an integer k. A subarray is considered "good" if it contains at least k pairs of indices such that and .
You need to find the total number of such good subarrays.
This is a classic sliding window interview pattern question asked by Uber and Meta. It tests whether a candidate can maintain a complex running state (the count of pairs) as the window moves. It also requires the insight that if a subarray is "good," then any larger subarray containing it is also "good," which is the fundamental prerequisite for an efficient two-pointer solution.
The problem uses Sliding Window and a Frequency Map.
left and right pointer and a current_pairs count.right. When adding nums[right], the number of new pairs formed is the current count of nums[right] in the window.current_pairs >= k:
left and ending at any index from right to the end of the array is "good."n - right.left. When removing nums[left], decrement current_pairs by the count of nums[left] remaining in the window.nums = [1, 1, 1, 1], k = 2
right = 0: "1". Pairs = 0.right = 1: "1, 1". Pairs = 1.right = 2: "1, 1, 1". Pairs = 3 (which is ).
[1,1,1] and [1,1,1,1]).left: remove nums[0]. Pairs = . (Now < k).right = 3: "1, 1, 1". (Window is indices 1 to 3). Pairs = 3 ().
[1,1,1] at the end).left: remove nums[1]. Pairs = 1.
Total = 3.Practice the logic of "At least ." For subarrays, if a condition is satisfied for nums[i..j], it is usually satisfied for nums[i..j+1]. This allows you to count all future right-endpoints in one step.
| Title | Difficulty | Topics | LeetCode |
|---|---|---|---|
| Count Complete Subarrays in an Array | Medium | Solve | |
| Length of Longest Subarray With at Most K Frequency | Medium | Solve | |
| Maximum Erasure Value | Medium | Solve | |
| Minimum Consecutive Cards to Pick Up | Medium | Solve | |
| Maximum Sum of Distinct Subarrays With Length K | Medium | Solve |