You only need 25 questions to learn all the coding interview patterns Quiz

Sharpen your coding fundamentals with these key topics and problems that cover essential patterns in data structures and algorithms. Practice core questions across arrays, strings, stacks, and heaps to excel in technical interviews.

1. Understanding Array Traversal Techniques

   Which technique efficiently finds pairs in a sorted array that sum to a given value by using two pointers?

   1. Brute force
   2. Hash map lookup
   3. Two-pointer method
   4. Binary search

   Explanation: The two-pointer method is efficient for traversing sorted arrays to find pairs that satisfy a condition, like a target sum. Binary search is for searching individual elements, not pairs. Hash map lookup is used for unsorted arrays or for storing previous values. Brute force checks all combinations but is less efficient.

2. Exploring Subarrays and Prefix Products

   To compute an array where each element is the product of all other elements except itself, which approach avoids using division and achieves O(n) time complexity?

   1. Prefix and suffix products
   2. Find maximum then subtract
   3. Naive nested loops
   4. Sort and multiply method

   Explanation: Prefix and suffix products allow calculation without division and with linear time complexity. Sort and multiply is unrelated. Finding maximum and subtracting does not solve the 'product except self' problem. Naive nested loops are correct but inefficient.

3. Mastering String Sliding Window

   Which algorithmic pattern is best for finding the length of the longest substring without repeating characters in a string?

   1. Recursion
   2. Sliding window
   3. Heap sort
   4. Depth-first search

   Explanation: Sliding window is optimal for problems involving substrings with constraints, such as uniqueness. Recursion is not typically efficient for these scenarios. Heap sort is for ordering data, not finding substrings. Depth-first search is used for tree and graph traversal.

4. Trapping Rain Water with Stacks

   Which data structure provides an efficient solution for calculating trapped rainwater given elevation heights represented as an array?

   1. Queue
   2. Heap
   3. Linked list
   4. Stack

   Explanation: A stack is suitable for maintaining indices as you scan elevation heights, enabling efficient computation of trapped water. A queue does not help with this specific pattern. Linked lists are not typically needed for this problem. Heaps are unrelated to the core logic.

5. Evaluating Expressions in Reverse Polish Notation

   Which approach efficiently evaluates arithmetic expressions in Reverse Polish Notation?

   1. Stack-based evaluation
   2. Direct left-to-right calculation
   3. Array prefix sum
   4. Tree in-order traversal

   Explanation: Stack-based evaluation allows operators and operands to be processed in order for Reverse Polish Notation. Left-to-right calculation fails due to operator precedence. Tree traversal is unnecessary. Prefix sum arrays are meant for subarray sums, not expression evaluation.