Meta Coding Interview Essentials: Algorithms u0026 Data Structures Quiz Quiz

Test your knowledge with 15 key coding interview questions inspired by the most frequently asked problems at Meta, covering arrays, strings, linked lists, trees, graphs, recursion, sorting, searching, and dynamic programming. Improve your readiness for technical interviews by practicing crucial concepts and problem-solving techniques.

1. Arrays u0026 Strings

   Which approach is most efficient for finding the length of the longest substring without repeating characters in a given string?

   1. Using recursion to remove duplicates
   2. Sorting the string and counting unique characters
   3. Brute force by checking all possible substrings
   4. Sliding window with a hash set

   Explanation: The sliding window method with a hash set efficiently tracks unique characters and updates the maximum substring length in linear time. Sorting only identifies unique characters but does not preserve order or continuity, which is essential. Brute force requires checking all substring combinations, which is much slower. Simple recursion is not suitable for this scenario as it cannot efficiently maintain character positions.

2. Arrays u0026 Strings

   Given two sorted arrays, which method best merges them into a single sorted array in-place with minimal space complexity?

   1. Recursively merge one element at a time
   2. Two-pointer technique starting from the end
   3. Copy all elements into a new array and sort
   4. Bubble sort each array first and then combine

   Explanation: The two-pointer method, starting from the ends of both arrays, merges them in-place efficiently while minimizing extra space. Copying elements into a new array uses extra memory. Recursively merging is unnecessary and inefficient for this case. Bubble sorting each array individually is redundant since they are already sorted and does not merge them.

3. Linked Lists

   In the 'Merge Two Sorted Lists' problem involving singly linked lists, what principle ensures efficient merging?

   1. Traversing both lists recursively and summing indices
   2. Iterating with two pointers and comparing node values
   3. Calculating the sum of all node values
   4. Using hash tables to store used nodes

   Explanation: Using two pointers to iterate and compare node values enables merging in a single pass and preserves the sorted order. Hash tables are unnecessary because duplicates or node reuse are not a concern. Summing node values does not help with merging, nor does recursive index summing, which isn’t meaningful for linked lists.

4. Arrays u0026 Strings

   How would you efficiently remove duplicates from a sorted array while ensuring each element appears only once?

   1. Add all elements to a stack and pop duplicates
   2. Sort the array again before removing
   3. Use two pointers, overwriting duplicates as you iterate
   4. Use a hash map to count all occurrences

   Explanation: The two-pointer technique efficiently overwrites duplicates in a sorted array in-place, which uses constant extra space. Sorting again is unnecessary since the input is already sorted. A stack is not well-suited here and adds complexity. Using a hash map increases space complexity, which is not ideal when the array is sorted.

5. Trees u0026 Graphs

   What property characterizes a valid binary search tree (BST)?

   1. Each level of the tree contains unique nodes
   2. Leaf nodes must have even values
   3. Only the root node's value must be greater than its children
   4. For each node, all values in the left subtree are less and right subtree are greater

   Explanation: A valid BST requires that, for every node, all nodes in the left subtree have lesser values and all nodes in the right subtree have greater values. Having unique nodes at each level or the root being greater than children is insufficient for BST validity. There is no requirement relating to leaf node parity.

6. Trees u0026 Graphs

   Given a binary tree, which traversal technique is best for creating a list of values by vertical order (column by column)?

   1. Random walk traversal
   2. Depth-first pre-order traversal
   3. In-order traversal only
   4. Breadth-first traversal with column indexing

   Explanation: Breadth-first (level order) traversal with column indices helps group nodes by vertical columns, essential for vertical order representation. Depth-first pre-order does not maintain column grouping. In-order only gives sorted order for BSTs, not vertical grouping. Random walk is not a valid tree traversal.

7. Recursion

   When generating all possible permutations of a list of distinct integers, which strategy is most effective?

   1. Recursive backtracking with element swapping
   2. Using binary search on the list
   3. Sorting the list before generating permutations
   4. Iteratively adding elements to a queue

   Explanation: Backtracking recursively and swapping elements enables exhaustive generation of permutations while systematically exploring all possibilities. Sorting only arranges the list, not all permutations. Iterative queue methods are less straightforward for this task. Binary search is unrelated to permutation generation.

8. Sorting u0026 Searching

   How can you efficiently find the first and last position of a given element in a sorted array?

   1. Use modified binary search twice: leftmost and rightmost
   2. Scan the entire array left to right
   3. Use a hash set to find indices
   4. Sort the array and look for unique occurrences

   Explanation: Using binary search twice—once for the first occurrence, once for the last—is efficient and runs in logarithmic time. Scanning the array is slower. Sorting is unnecessary when the array is already sorted. Hash sets do not store index information, so they cannot help in finding positions.

9. Dynamic Programming

   Which method best solves the problem of finding the longest palindromic substring in a string?

   1. Traverse with sliding window and hash map
   2. Expand around center for each character
   3. Reverse the string and compare with the original
   4. Sort the characters and check for palindromes

   Explanation: Expanding around each center efficiently finds all palindromic substrings and helps identify the longest one. Reversing and comparing only detects if the whole string is a palindrome. Sorting loses order and structure necessary for palindromes. Hash maps do not directly help identify palindromic substrings.

10. Arrays u0026 Strings

    What approach efficiently computes the product of all elements in an array except the element at each index, without using division?

    1. Calculate total product and divide by current element at each index
    2. Precompute left and right products and multiply them for each index
    3. Sort array and use running sum
    4. Use recursion to multiply all pairs

    Explanation: Precomputing prefix (left) and suffix (right) products and multiplying them avoids division and allows for an efficient solution. Using division is not allowed in this problem. Sorting and using sums does not give the correct products. Recursion to multiply all pairs is highly inefficient.

11. Trees u0026 Graphs

    How can you efficiently determine whether an undirected graph is bipartite?

    1. Find the largest connected component
    2. Count the number of vertices and edges
    3. Try to color the graph using two colors with BFS or DFS
    4. Check if all vertices have even degrees

    Explanation: Attempting to color the graph with two colors (using BFS or DFS) determines if adjacent nodes can be separated, which defines bipartiteness. Simply counting vertices and edges or finding connected components doesn't reveal bipartiteness. Vertex degree parity is unrelated to whether a graph is bipartite.

12. Arrays u0026 Strings

    When moving all zeroes in an array to the end while maintaining the order of non-zero elements, which method is preferred?

    1. Sorting the array in ascending order
    2. Deleting and reinserting zeros from the array
    3. Using a queue to enqueue non-zero values
    4. Two-pointer approach with in-place swapping

    Explanation: The two-pointer approach allows in-place swapping of non-zero elements and zeros, preserving relative order efficiently. Deleting and reinserting elements leads to higher time complexity. Sorting the array loses original order. Enqueuing values into a queue uses extra space unnecessarily.

13. Recursion

    In generating all subsets (the power set) of a set of integers, which technique is most efficient?

    1. Use a hash table to avoid duplicates
    2. Recursive backtracking by deciding for each element to include or not
    3. Sum all elements and split based on averages
    4. Sort the set before starting recursion

    Explanation: Recursive backtracking allows each subset to be constructed by choosing to include or exclude each element, covering all possibilities. Sorting before recursion isn't necessary for completeness. Splitting by averages is irrelevant for subset generation. Using a hash table is more for handling duplicates, which may not be present.

14. Sorting u0026 Searching

    What is the main advantage of using the binary search algorithm on sorted arrays?

    1. It works on both sorted and unsorted arrays
    2. O(log n) time complexity for searching
    3. It uses a queue to improve performance
    4. It sorts the array while searching

    Explanation: Binary search divides the search space in half at each step, resulting in logarithmic time complexity, which is very efficient. It only works on sorted arrays, not unsorted ones. Binary search does not sort the array. Using a queue is unrelated to its operation.

15. Dynamic Programming

    Which key idea underlies solving the 'Best Time to Buy and Sell Stock' problem to maximize profit with one transaction?

    1. Calculating the running total of all price changes
    2. Tracking the minimum price observed and computing profit at each day
    3. Sorting the array of prices to select the lowest and highest
    4. Buying every time the price drops and selling whenever it rises

    Explanation: By keeping track of the lowest price and evaluating profit by comparing with the current price, you can determine the maximum achievable profit in a single pass. Running totals don't capture the optimal buy-sell pair. Buying and selling on every fluctuation doesn't guarantee maximum profit with one transaction. Sorting prices ignores the ordering and timing required for correct buys and sells.