Sliding window technique in Data Structures Theory - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the sliding window technique?

The sliding window technique is a method used to solve problems that involve arrays or lists by creating a 'window' of elements and moving it across the data to find a solution efficiently.

beginner

How does the sliding window technique improve efficiency?

It avoids repeated work by reusing previous calculations as the window moves, reducing the time complexity compared to checking all possible subarrays or segments.

beginner

Give a real-life example where the sliding window technique can be applied.

Checking the highest temperature over every 7-day period in a month can use a sliding window to move day by day, updating the highest temperature without rechecking all days each time.

intermediate

What are the two main types of sliding windows?

Fixed-size windows, which move by one element at a time, and variable-size windows, which can expand or shrink based on conditions.

beginner

Why is the sliding window technique preferred over brute force in many problems?

Because it reduces the number of operations by not recalculating everything from scratch for each new position, leading to faster and more efficient solutions.

What does the 'window' represent in the sliding window technique?

A The entire data set

B A subset of elements in a sequence

C A single element only

D An unrelated data structure

The window is a subset of elements that moves across the data to analyze parts of the sequence.

Which problem is best suited for the sliding window technique?

A Finding the maximum sum of any continuous subarray of fixed length

B Sorting an array

C Searching for a specific element in an unsorted list

D Calculating factorial of a number

Sliding window efficiently finds sums or other properties in continuous subarrays.

How does a fixed-size sliding window move?

A By doubling its size each time

B By jumping randomly

C It stays fixed and does not move

D By adding and removing one element at a time

A fixed-size window moves by removing the first element and adding the next element in the sequence.

What is a key benefit of using a variable-size sliding window?

A It never changes size

B It always processes the entire data set at once

C It can adjust to meet certain conditions dynamically

D It sorts the data automatically

Variable-size windows expand or shrink to satisfy problem-specific conditions.

Which of these is NOT a typical use case for sliding window?

A Binary search in a sorted array

B Calculating moving averages

C Finding longest substring without repeating characters

D Detecting patterns in streaming data

Binary search is a different algorithm and does not use sliding windows.

Explain the sliding window technique and how it helps solve problems involving arrays or lists.

Think about how you can look at parts of a list without starting over each time.

Describe the difference between fixed-size and variable-size sliding windows with examples.

Consider how the window size changes or stays the same.