Is Number of Subarrays That Match a Pattern I easy or hard?

The problem is rated Medium because it requires recognizing that pairwise comparisons can be converted into a pattern matching problem. The brute force approach is simple, but identifying the linear-time optimization requires familiarity with sliding window or string matching techniques.

Number of Subarrays That Match a Pattern I Python/Java solution

Most implementations first build the comparison array and then slide a window over it to check matches. This logic is straightforward to implement in Python, Java, C++, or JavaScript and typically runs in O(n) time with O(n) extra space.

How to solve Number of Subarrays That Match a Pattern I in O(n)?

First convert the array into a relation array where each element represents whether nums[i+1] is greater than, equal to, or less than nums[i]. Then slide a window of size equal to the pattern length across this relation array and compare it to the pattern. Each position is checked once, producing an O(n) solution.

What is the best approach for Number of Subarrays That Match a Pattern I?

The most efficient method converts the array into a sequence representing pairwise relationships (-1, 0, 1) and then searches for the pattern inside this sequence using a sliding window. This avoids recomputing comparisons for overlapping subarrays and runs in O(n) time after building the difference array.

Is Number of Subarrays That Match a Pattern I asked at Google/Amazon/Meta?

Pattern matching and sliding window problems are common in interviews at companies like Google, Amazon, and Meta. This problem specifically tests the ability to transform numeric comparisons into a sequence and apply efficient pattern searching techniques.

What data structure is used in Number of Subarrays That Match a Pattern I?

The solution mainly uses arrays. The optimized approach also treats the comparison array like a string and applies techniques from string matching or rolling hash to detect pattern occurrences efficiently.

What is the time complexity of Number of Subarrays That Match a Pattern I?

The brute force solution checks every candidate subarray and compares each pair against the pattern, resulting in O(n * m) time where n is the array size and m is the pattern length. The optimized sliding window approach processes the array once and runs in O(n) time.

Description Hints 1 Solution Video 37:38

3034. Number of Subarrays That Match a Pattern I

Medium67.9% acceptance5 companies

You are given a 0-indexed integer array nums of size n, and a 0-indexed integer array pattern of size m consisting of integers -1, 0, and 1.

A subarray nums[i..j] of size m + 1 is said to match the pattern if the following conditions hold for each element pattern[k]:

nums[i + k + 1] > nums[i + k] if pattern[k] == 1.
nums[i + k + 1] == nums[i + k] if pattern[k] == 0.
nums[i + k + 1] < nums[i + k] if pattern[k] == -1.

Return the count of subarrays in nums that match the pattern.

Example 1:

Input: nums = [1,2,3,4,5,6], pattern = [1,1]
Output: 4
Explanation: The pattern [1,1] indicates that we are looking for strictly increasing subarrays of size 3. In the array nums, the subarrays [1,2,3], [2,3,4], [3,4,5], and [4,5,6] match this pattern.
Hence, there are 4 subarrays in nums that match the pattern.

Example 2:

Input: nums = [1,4,4,1,3,5,5,3], pattern = [1,0,-1]
Output: 2
Explanation: Here, the pattern [1,0,-1] indicates that we are looking for a sequence where the first number is smaller than the second, the second is equal to the third, and the third is greater than the fourth. In the array nums, the subarrays [1,4,4,1], and [3,5,5,3] match this pattern.
Hence, there are 2 subarrays in nums that match the pattern.

Constraints:

2 <= n == nums.length <= 100
1 <= nums[i] <= 10⁹
1 <= m == pattern.length < n
-1 <= pattern[i] <= 1

Asked at 5 companies

Autodesk Capital One Visa Uber Amazon

Topics

Hints open one at a time

Hint 1

Iterate over all indices i then, using a second loop, check if the subarray starting at index i matches the pattern.

37:38

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