Sliding Window Flashcards
What is the sliding window pattern used for?
The sliding window pattern is used to process sequential data, such as arrays and strings, to efficiently solve subarray or substring problems by maintaining a dynamic window that slides through the data, adjusting its boundaries as needed to track relevant elements or characters.
How does the sliding window pattern improve efficiency?
Instead of computing sums or other properties for all possible subarrays or substrings, the sliding window pattern updates the result incrementally by adding the new element entering the window and removing the old element exiting the window, which can often be done in constant time, reducing the overall time complexity.
What type of data structure is suitable for the sliding window pattern?
The sliding window pattern is suitable for data stored in a contiguous manner, such as arrays or strings.
What is an example of a problem that can be solved using the sliding window pattern?
Finding the maximum sum subarray of size : k
Given an array of integers and a positive integer : k
find the maximum sum of any contiguous subarray of size : k
What conditions must be fulfilled for a problem to be suitable for the sliding window pattern?
The input data must be contiguous, such as an array or string.
The problem requires repeated computations on a contiguous subset of data elements.
The computations performed every time the window moves should take constant or very small time.
How can the sliding window pattern be applied in telecommunications?
It can be used to find the maximum number of users connected to a cellular network’s base station in every k-millisecond sliding window.
How does the sliding window pattern help in video streaming?
It can be used to calculate the median number of buffering events in each one-minute interval of a stream of numbers representing buffering events in a user session.
How can the sliding window pattern be applied in social media content mining?
It can be used to find the shortest sequence of posts by one user that includes all the topics that another user has posted about.
Locate the 6th largest element in an array.
Some other pattern
Explanation: Finding the 6th largest element in an array typically requires sorting or using a selection algorithm (e.g., quickselect), which does not align with the sliding window pattern.
Given a string S and a string T, find the shortest substring in S that contains all the characters in T.
Sliding Window
Explanation: This problem can be efficiently solved using the sliding window pattern by expanding and contracting the window to find the smallest substring in S that contains all characters of T.
Given an array of integers and a target sum, find the length of the smallest subarray whose sum is greater than or equal to the target sum.
Solution: Sliding Window
Explanation: The sliding window pattern can be used to dynamically adjust the window size to find the smallest subarray with a sum that meets or exceeds the target.
Find safe places for five queens on a 5×5 chessboard.
Some other pattern
Explanation: Placing queens on a chessboard involves combinatorial search and backtracking, which is not suitable for the sliding window pattern.
