You are given an integer array nums of length n and a 2D array queries, where queries[i] = [li, ri].
For each queries[i]:
[li, ri] in nums.A Zero Array is an array where all elements are equal to 0.
Return true if it is possible to transform nums into a Zero Array after processing all the queries sequentially, otherwise return false.
Example 1:
Input: nums = [1,0,1], queries = [[0,2]]
Output: true
Explanation:
[0, 2] and decrement the values at these indices by 1.[0, 0, 0], which is a Zero Array.Example 2:
Input: nums = [4,3,2,1], queries = [[1,3],[0,2]]
Output: false
Explanation:
[1, 2, 3] and decrement the values at these indices by 1.[4, 2, 1, 0].[0, 1, 2] and decrement the values at these indices by 1.[3, 1, 0, 0], which is not a Zero Array.
Constraints:
1 <= nums.length <= 1050 <= nums[i] <= 1051 <= queries.length <= 105queries[i].length == 20 <= li <= ri < nums.lengthThis approach utilizes the concept of difference arrays to efficiently apply the operations for each query range. Instead of decrementing elements directly, we apply the operations incrementally over the range, which allows us to keep track of cumulative changes.
The solution uses a 'delta' array to apply increments and decrements at specific points, which is very efficient for range update operations. For each query, we decrement the starting index of the range by 1 and increment the position just after the end of the range by 1. Then, we propagate these effects across the 'nums' array using a cumulative carry. Finally, we check if every element in the final array is zero or not.
JavaScript
C++
C
Java
C#
Time Complexity: O(n + q), where n is the length of nums and q is the number of queries.
Space Complexity: O(n), for the delta array used in the implementation.
This approach directly applies decrement operations specified by each query to the range given. Though simple to understand, it may not be efficient for large input sizes due to the repetitive operations. Consider optimizing if the constraints are strict.
This solution directly walks over each query range and decrements the values if they are greater than zero. After all queries, it checks if every element is zero. This is not time efficient for large datasets but is straightforward to understand and serves as a baseline approach.
JavaScript
C++
C
Java
C#
Time Complexity: O(n * q), where n is the length of nums and q is the number of queries.
Space Complexity: O(1), no extra space is used except input.
| Approach | Complexity |
|---|---|
| Efficient Interval Update using Difference Array | Time Complexity: O(n + q), where n is the length of nums and q is the number of queries. |
| Direct Simulation of Operations | Time Complexity: O(n * q), where n is the length of nums and q is the number of queries. |
Zero Array Transformation II | Leetcode 3356 • Techdose • 11,560 views views
Watch 9 more video solutions →Practice Zero Array Transformation I with our built-in code editor and test cases.
Practice on FleetCode