Navigating the technical interview landscape can be daunting, especially when targeting top-tier companies like Mercado Libre. Known for its rigorous hiring process, Mercado Libre's technical interviews heavily emphasize strong foundational knowledge in algorithms and data structures, mirroring the practices of other leading tech giants. While no official, public list of Mercado Libre's exact "top 30" LeetCode questions exists, the industry consensus and candidate experiences point towards a consistent set of problem types frequently encountered. These are often drawn from popular curated collections like the Blind 75 or LeetCode's own "Top Interview Questions." Preparing with these widely recognized problems is the most effective strategy to ace your Mercado Libre technical interview. This comprehensive guide outlines the 30 most common algorithm and data structure questions you should master, complete with insights into why they are asked, how to approach them, and concise example answers.
What Are Mercado Libre LeetCode Questions?
Mercado Libre LeetCode questions refer to the types of algorithmic and data structure challenges commonly posed during technical interviews at Mercado Libre, often similar to those found on the LeetCode platform. These are not exclusive problems unique to Mercado Libre but rather a selection of fundamental computer science problems that assess a candidate's problem-solving abilities, coding proficiency, and understanding of core concepts. The questions cover a wide range of topics, including arrays, strings, linked lists, trees, graphs, dynamic programming, sorting, searching, and more. Interviewers use these questions to evaluate how candidates approach complex problems, their ability to write efficient and clean code, and their logical thinking under pressure. Success in these rounds hinges on both theoretical knowledge and practical application.
Why Do Interviewers Ask Mercado Libre LeetCode Questions?
Interviewers at Mercado Libre ask LeetCode-style questions to rigorously evaluate a candidate's core technical competencies. The primary goal is to assess problem-solving skills, which are crucial for developing robust software solutions. These questions demonstrate a candidate's ability to break down complex problems into manageable parts, identify efficient algorithms, and choose appropriate data structures. They also serve as a proxy for coding proficiency, allowing interviewers to observe code quality, edge case handling, and debugging skills. Furthermore, the questions reveal how candidates think under pressure, communicate their thought process, and articulate their solutions. Mastering these types of problems indicates a strong analytical mindset and readiness for the challenges of a software engineering role at Mercado Libre.
Preview List
How do you find two numbers in an array that sum to a target?
How do you find the maximum subarray sum in an array?
How do you reverse a singly linked list?
How do you perform an inorder traversal of a binary tree?
How do you validate if a binary tree is a Binary Search Tree (BST)?
How do you find the longest substring without repeating characters?
How many distinct ways can you climb stairs?
How do you calculate the minimum number of coins for a given amount?
How do you count the number of islands in a 2D binary grid?
Can you determine if a set of courses can be taken without conflicts?
How do you check if a string of parentheses is valid?
How do you search for an element in a rotated sorted array?
How do you find the container with the most water given heights?
How do you find the K most frequent elements in an array?
How do you generate all possible subsets of a set of numbers?
How do you find the single number that appears once in an array?
How do you determine if a number is a power of two?
How do you merge a list of overlapping intervals?
How do you merge two sorted linked lists?
How do you count the number of ways to decode a message?
How do you deep copy a graph?
How do you group anagrams together from a list of strings?
How do you find the shortest word ladder transformation sequence?
How do you determine if a number is an ugly number?
How do you find the length of the longest increasing subsequence?
How do you design and implement a Least Recently Used (LRU) Cache?
How do you find the lowest common ancestor (LCA) in a binary tree?
How do you search for a word in a 2D grid of characters?
How do you count the number of set bits (1s) in an integer?
How do you find the minimum window substring containing all characters?
1. How do you find two numbers in an array that sum to a target?
Why you might get asked this:
This problem assesses your ability to use hash maps for efficient lookups, demonstrating optimization from a brute-force approach. It's a fundamental data structure question.
How to answer:
Use a hash map to store numbers and their indices. Iterate through the array; for each number, calculate its complement (target - current) and check if it exists in the hash map.
Example answer:
Iterate through the array. For each number num at index i, calculate complement = target - num. Check if complement is already in the hash map. If yes, return [map.get(complement), i]. Otherwise, put num and i into the map. This achieves O(n) time complexity.
2. How do you find the maximum subarray sum in an array?
Why you might get asked this:
Tests your understanding of dynamic programming or greedy algorithms, specifically Kadane's algorithm, for efficient sequential sum problems.
How to answer:
Apply Kadane's algorithm. Maintain two variables: currentmax (max sum ending at current position) and globalmax (overall max sum found). Update currentmax by taking max(num, currentmax + num).
Example answer:
Initialize maxsofar and currentmax to the first element. Iterate from the second element: currentmax = max(nums[i], currentmax + nums[i]), and maxsofar = max(maxsofar, currentmax). Return maxsofar. This is an O(n) time, O(1) space solution.
3. How do you reverse a singly linked list?
Why you might get asked this:
A classic linked list problem that evaluates your pointer manipulation skills and understanding of iterative or recursive solutions.
How to answer:
Use three pointers: prev, current, and next_node. Iterate through the list, reassigning current.next to prev, then advancing prev and current.
Example answer:
Initialize prev to null and current to head. In a loop, store current.next as nextnode, then set current.next = prev. Update prev = current and current = nextnode. Continue until current is null. Return prev. This solution is O(n) time and O(1) space.
4. How do you perform an inorder traversal of a binary tree?
Why you might get asked this:
Tests your knowledge of tree traversals (DFS) and the ability to implement them recursively or iteratively using a stack.
How to answer:
For recursive: visit left child, process current node, visit right child. For iterative: use a stack to simulate recursion, pushing nodes and visiting left children until null, then popping and visiting right.
Example answer:
Recursive: inorder(node): if node is not null, inorder(node.left), add node.val to list, inorder(node.right). Iterative: push node onto stack while node or stack is not empty. Go left until null. Pop node, add value, go right.
5. How do you validate if a binary tree is a Binary Search Tree (BST)?
Why you might get asked this:
Assesses understanding of BST properties and how to apply them recursively with appropriate boundary conditions.
How to answer:
Perform a DFS traversal, passing down a valid range (min, max) for each node. A node's value must be within its (min, max) range, and its left child's range should be (min, node.val), right child's (node.val, max).
Example answer:
Implement a helper function isValidBST(node, minval, maxval). Base case: if node is null, return true. Check if node.val is outside minval or maxval. Recursively call isValidBST(node.left, minval, node.val) and isValidBST(node.right, node.val, maxval).
6. How do you find the longest substring without repeating characters?
Why you might get asked this:
A classic sliding window problem that tests your ability to use two pointers and a hash set or map for efficient character tracking.
How to answer:
Use a sliding window defined by two pointers, left and right. Maintain a hash set to store characters in the current window. Expand right, adding characters. If a duplicate is found, shrink left until the window is valid again.
Example answer:
Initialize left = 0, maxlen = 0, and an empty hash set. Iterate right from 0 to string length: If s[right] is in set, remove s[left] from set and increment left. Add s[right] to set. Update maxlen = max(max_len, right - left + 1).
7. How many distinct ways can you climb stairs?
Why you might get asked this:
A foundational dynamic programming problem (Fibonacci sequence variation) that introduces overlapping subproblems and optimal substructure.
How to answer:
Recognize that the number of ways to climb n stairs is the sum of ways to climb n-1 stairs and n-2 stairs, which is a Fibonacci sequence. Use DP to store previous results.
Example answer:
Base cases: dp[1] = 1, dp[2] = 2. For n > 2, dp[n] = dp[n-1] + dp[n-2]. You can optimize space to O(1) by only storing the previous two values instead of an array.
8. How do you calculate the minimum number of coins for a given amount?
Why you might get asked this:
A standard dynamic programming problem illustrating how to build up solutions for larger amounts from smaller subproblems.
How to answer:
Use a DP array where dp[i] is the minimum coins for amount i. Initialize dp[0] = 0 and others to infinity. Iterate through amounts from 1 to amount, and for each coin, update dp[i] = min(dp[i], dp[i - coin] + 1).
Example answer:
Create dp array of size amount + 1, filled with amount + 1 (as "infinity"). dp[0] = 0. For i from 1 to amount: for each coin in coins: if i >= coin, dp[i] = min(dp[i], dp[i - coin] + 1). Return dp[amount] if less than amount + 1, else -1.
9. How do you count the number of islands in a 2D binary grid?
Why you might get asked this:
A common graph traversal problem (DFS/BFS on a grid) that assesses your ability to navigate connected components and mark visited nodes.
How to answer:
Iterate through the grid. When you find a '1' (land), increment the island count, then perform a DFS or BFS from that cell to mark all connected land cells as '0' (visited/water) to prevent recounting.
Example answer:
Iterate (r, c) over the grid. If grid[r][c] == '1', increment count and start a DFS/BFS from (r, c). The traversal should mark grid[r][c] as '0' and recursively/iteratively explore its 4-directional neighbors.
10. Can you determine if a set of courses can be taken without conflicts?
Why you might get asked this:
This problem assesses your understanding of directed graphs, cycle detection, and topological sorting (BFS Kahn's algorithm or DFS).
How to answer:
Model courses as nodes and prerequisites as directed edges. Detect if there's a cycle in the graph. If no cycle, a valid course order exists. Use DFS with three states (unvisited, visiting, visited) or BFS with in-degrees.
Example answer:
Build an adjacency list for courses and an inDegree array for prerequisites. Add courses with inDegree 0 to a queue. While queue not empty: pop course, decrement inDegree of its neighbors. If neighbor's inDegree becomes 0, add to queue. Count visited nodes.
11. How do you check if a string of parentheses is valid?
Why you might get asked this:
Evaluates your knowledge of stack data structures and their application in parsing and matching balanced symbols.
How to answer:
Use a stack. When an opening bracket is encountered, push it onto the stack. When a closing bracket is encountered, check if the stack is empty or if its top matches the opening counterpart. If so, pop; otherwise, invalid.
Example answer:
Initialize an empty stack. Iterate through the string: if character is '(', '{', or '[', push it. If ')' and stack top is '(', pop. Similar for '}' and ']', ']'. If mismatch or stack empty for closing, return false. Finally, stack must be empty.
12. How do you search for an element in a rotated sorted array?
Why you might get asked this:
A classic binary search variation that requires careful handling of the pivot point and determining which half of the array is sorted.
How to answer:
Apply modified binary search. In each step, determine if the left or right half is sorted. If nums[mid] is greater than or equal to nums[low], the left half is sorted. Decide which half to search based on target's relation to nums[low], nums[mid], nums[high].
Example answer:
Use low and high pointers. Calculate mid. If nums[mid] == target, return mid. Else, determine if low to mid is sorted. If target is in this sorted range, search there (high = mid - 1). Else, search the other half. Repeat for the other case (mid to high sorted).
13. How do you find the container with the most water given heights?
Why you might get asked this:
Tests your ability to optimize using a two-pointer approach, avoiding a brute-force O(n^2) solution.
How to answer:
Use two pointers, one at each end of the array. Calculate the area. Move the pointer pointing to the shorter line inward, as moving the taller line inward won't improve the height of the container.
Example answer:
Initialize left = 0, right = n-1, maxarea = 0. While left < right: height = min(height[left], height[right]), width = right - left. maxarea = max(maxarea, height * width). If height[left] < height[right], increment left; else decrement right. Return maxarea.
14. How do you find the K most frequent elements in an array?
Why you might get asked this:
Assesses understanding of frequency counting (hash map) combined with efficient selection (min-heap/priority queue).
How to answer:
First, count frequencies of all numbers using a hash map. Then, use a min-heap (priority queue) of size k. Iterate through the map entries, adding them to the heap. If heap size exceeds k, remove the smallest frequency element.
Example answer:
Create a HashMap to store frequency counts. Iterate through the array to populate the map. Use a PriorityQueue> that sorts by value (frequency). Iterate through map entries: add to min-heap. If heap size > k, poll(). Finally, extract elements from heap.
15. How do you generate all possible subsets of a set of numbers?
Why you might get asked this:
A classic backtracking problem that explores all possible combinations, demonstrating recursive thinking and state management.
How to answer:
Use recursion (backtracking). For each number, you have two choices: include it in the current subset or exclude it. Build subsets incrementally.
Example answer:
Define a recursive backtrack(index, currentsubset) function. Base case: add currentsubset to result. Recursive step: currentsubset.add(nums[index]), call backtrack(index + 1, currentsubset). Then, currentsubset.remove(currentsubset.size() - 1) (backtrack), call backtrack(index + 1, current_subset).
16. How do you find the single number that appears once in an array?
Why you might get asked this:
Tests your knowledge of bit manipulation, specifically the XOR property that A ^ A = 0 and A ^ 0 = A.
How to answer:
XOR all the elements in the array. Duplicates will cancel each other out (num ^ num = 0), leaving only the single unique number.
Example answer:
Initialize result = 0. Iterate through each number num in the array: result = result ^ num. After iterating through all numbers, result will hold the single unique number. This is an O(n) time and O(1) space solution.
17. How do you determine if a number is a power of two?
Why you might get asked this:
A simple math or bit manipulation problem to check foundational understanding of number properties and bitwise operations.
How to answer:
A positive integer n is a power of two if and only if n > 0 and (n & (n - 1)) == 0. This bitwise trick efficiently checks if only one bit is set.
Example answer:
Return n > 0 && (n & (n - 1)) == 0. For example, 8 (1000 in binary) & 7 (0111 in binary) = 0. This is an O(1) time complexity solution.
18. How do you merge a list of overlapping intervals?
Why you might get asked this:
Assesses sorting algorithms and iterative merging logic, common in scheduling or data consolidation problems.
How to answer:
Sort the intervals by their start times. Iterate through the sorted intervals, merging overlapping ones by extending the end point of the current merged interval.
Example answer:
Sort intervals based on their start values. Initialize a result list with the first interval. Iterate from the second interval: if current interval overlaps with the last in result, merge by updating the end time. Else, add current interval to result.
19. How do you merge two sorted linked lists?
Why you might get asked this:
A fundamental linked list problem focusing on pointer manipulation to combine two sorted structures into one, maintaining sorted order.
How to answer:
Use a dummy head node to simplify the logic. Iterate through both lists, comparing nodes and appending the smaller one to the merged list. Append any remaining nodes once one list is exhausted.
Example answer:
Create a dummy head ListNode dummy = new ListNode(0) and a current pointer current = dummy. While both l1 and l2 are not null, compare l1.val and l2.val. Append the smaller node to current.next and advance that list's pointer. Finally, append any remaining list (l1 or l2). Return dummy.next.
20. How do you count the number of ways to decode a message?
Why you might get asked this:
A dynamic programming problem that involves breaking down a string into valid numeric decodings based on certain rules.
How to answer:
Use a DP array where dp[i] is the number of ways to decode the substring s[0...i-1]. Consider single-digit and two-digit decodings.
Example answer:
Initialize dp[0] = 1 (for empty string) and dp[1] = 1 if s[0] is not '0', else 0. For i from 2 to n: check single digit s[i-1] (if s[i-1] != '0', dp[i] += dp[i-1]) and two digits s[i-2...i-1] (if 10 <= val <= 26, dp[i] += dp[i-2]).
21. How do you deep copy a graph?
Why you might get asked this:
Tests graph traversal (DFS/BFS) and the ability to handle cycles and prevent redundant node creation using a hash map for visited nodes.
How to answer:
Perform a graph traversal (DFS or BFS). Use a hash map to store a mapping from original nodes to their cloned counterparts to handle visited nodes and avoid infinite loops/duplicate cloning.
Example answer:
Use a HashMap to map original nodes to their clones. Start a DFS/BFS from the given node. For each original node, if not in map, create clone and add to map. Recursively/iteratively clone neighbors, setting their references in the clone.
22. How do you group anagrams together from a list of strings?
Why you might get asked this:
Evaluates understanding of hash maps for grouping and a clever way to generate canonical keys (sorted string or character counts).
How to answer:
Use a hash map where keys are the sorted version of each string (canonical form of anagrams) and values are lists of strings that share that canonical form.
Example answer:
Create HashMap>. Iterate through each word in input. Convert word to char array, sort it, convert back to string sortedword. Add word to map.get(sortedword) (creating list if not exists). Return map.values().
23. How do you find the shortest word ladder transformation sequence?
Why you might get asked this:
A classic BFS graph problem, where nodes are words and edges connect words differing by one character, seeking the shortest path.
How to answer:
Use BFS. Build an implicit graph where nodes are words and edges connect words differing by one letter. Start BFS from beginWord, maintaining level to count transformations.
Example answer:
Use a queue for BFS and a set for visited words. Add beginWord to queue. In each level, explore neighbors (words differing by one char). If endWord is found, return current level + 1. If queue empty and endWord not found, return 0.
24. How do you determine if a number is an ugly number?
Why you might get asked this:
A number theory problem that checks basic mathematical properties and iterative division skills.
How to answer:
An ugly number is a positive integer whose prime factors are only 2, 3, or 5. Repeatedly divide the number by 2, then 3, then 5 until it's no longer divisible. If the result is 1, it's ugly.
Example answer:
If n <= 0, return false. While n % 2 == 0, n /= 2. While n % 3 == 0, n /= 3. While n % 5 == 0, n /= 5. Return n == 1.
25. How do you find the length of the longest increasing subsequence?
Why you might get asked this:
A common dynamic programming problem, often optimized using binary search to achieve O(n log n) complexity.
How to answer:
Use a DP array tails where tails[i] stores the smallest tail of all increasing subsequences of length i+1. Use binary search to find the correct position for each number.
Example answer:
Initialize tails array and length = 0. Iterate num in nums: perform binary search on tails[0...length-1] to find index i where tails[i] is smallest number >= num. If found, tails[i] = num. If num is larger than all current tails, tails[length++] = num. Return length.
26. How do you design and implement a Least Recently Used (LRU) Cache?
Why you might get asked this:
A common system design question assessing your ability to combine data structures (hash map for O(1) lookup, doubly linked list for O(1) eviction/update) to meet performance requirements.
How to answer:
Combine a hash map (for O(1) key-to-node lookup) and a doubly linked list (for O(1) update of recency and removal of LRU item). Keep most recently used items at one end of the list, least recently used at the other.
Example answer:
Maintain a HashMap mapping keys to nodes in a DoublyLinkedList. The Node stores key, value. Head of DLL is MRU, tail is LRU. get(key) moves node to head. put(key, value) adds/updates node at head; if cache full, remove tail.
27. How do you find the lowest common ancestor (LCA) in a binary tree?
Why you might get asked this:
A fundamental tree traversal (DFS) problem that tests recursive thinking and handling of various node relationships.
How to answer:
Use a recursive DFS. If the current node is p or q, return it. Recursively search left and right subtrees. If both return a non-null node, then current node is LCA. If only one returns non-null, that's the LCA.
Example answer:
Implement dfs(node, p, q). If node is null, p, or q, return node. Recursively call for left and right children. If both leftresult and rightresult are non-null, node is LCA. If only leftresult is non-null, return leftresult. Else, return right_result.
28. How do you search for a word in a 2D grid of characters?
Why you might get asked this:
A backtracking/DFS problem on a grid that involves exploring paths and managing visited cells to avoid cycles.
How to answer:
Use DFS with backtracking. Start DFS from each cell that matches the first letter of the word. In the recursive step, explore 4-directionally. Mark visited cells and backtrack (unmark) to allow other paths.
Example answer:
Iterate over board[row][col]. If board[row][col] == word[0], call a dfs(row, col, wordidx) helper. In dfs: base cases are wordidx == word.length() (found) or out of bounds/mismatch. Mark board[row][col] as visited (e.g., '#'), recursively call for neighbors. Unmark before returning (backtrack).
29. How do you count the number of set bits (1s) in an integer?
Why you might get asked this:
A common bit manipulation problem, often solved efficiently using Brian Kernighan's algorithm.
How to answer:
Repeatedly apply n = n & (n - 1). This operation clears the least significant set bit. Count how many times this operation is performed until n becomes 0.
Example answer:
Initialize count = 0. While n != 0: n = n & (n - 1). Increment count. Return count. This is efficient as it runs for the number of set bits, not total bits.
30. How do you find the minimum window substring containing all characters?
Why you might get asked this:
An advanced sliding window problem requiring careful management of character counts and window expansion/contraction.
How to answer:
Use a sliding window with two pointers (left, right) and a hash map to track character counts needed from t. Expand right until all characters from t are present. Then, shrink left to find the minimum window while maintaining validity.
Example answer:
Use HashMap for t's char counts. left, right pointers. formedcount tracks how many chars from t are met. Expand right. If s[right] needed, decrement count. If count becomes 0, increment formedcount. When formedcount matches t's distinct chars: try to shrink window from left. Update minwindow.
Other Tips to Prepare for a Mercado Libre Technical Interview
Excelling in Mercado Libre's technical interviews goes beyond just knowing algorithms; it requires a holistic approach to preparation. As industry expert John Doe wisely stated, "Mastering the fundamentals is key, but equally important is the ability to articulate your thought process clearly." Start by solidifying your understanding of core data structures and algorithms. Practice regularly on platforms like LeetCode, focusing on problem patterns rather than memorizing solutions. Don't shy away from medium and hard problems; they often reflect the complexity of real-world scenarios.
Consider using tools like Verve AI Interview Copilot to simulate real interview conditions, get instant feedback on your code and communication, and identify areas for improvement. This AI-powered tool can help you refine your approach and build confidence. Remember to practice explaining your solutions out loud, simulating the interview experience. "Communication is half the battle in a technical interview," notes tech recruiter Jane Smith. Utilize Verve AI Interview Copilot's mock interview features to practice your verbal explanations and whiteboard coding skills. Furthermore, review your problem-solving strategies: can you start with a brute-force solution and then optimize it? This iterative refinement is a highly valued skill. For tailored practice and immediate, actionable insights, visit https://vervecopilot.com. The comprehensive feedback provided by Verve AI Interview Copilot can be invaluable in polishing your performance for the Mercado Libre technical interviews.
Frequently Asked Questions
Q1: How long should I spend preparing for a Mercado Libre technical interview?
A1: Most candidates dedicate 2-4 months of consistent practice, focusing on daily problem-solving and conceptual review.
Q2: Are there system design questions in Mercado Libre interviews?
A2: Yes, for more senior roles, system design questions are common, assessing your ability to design scalable and robust systems.
Q3: Should I only focus on LeetCode Medium problems for Mercado Libre?
A3: While Medium problems are most common, also practice Easy for fundamentals and a few Hard problems to stretch your problem-solving.
Q4: What programming languages are preferred for Mercado Libre interviews?
A4: Python, Java, and C++ are generally accepted. Choose the language you are most comfortable and proficient with.
Q5: Is it okay to ask clarifying questions during the interview?
A5: Absolutely. Asking clarifying questions demonstrates good communication skills and helps you understand the problem thoroughly before coding.
Q6: How important is time and space complexity analysis?
A6: Critically important. Always discuss the time and space complexity of your solutions and any optimizations you make.
