Preparing for LinkedIn coding interview questions is a crucial step for aspiring software engineers. LinkedIn, a leading professional networking platform, seeks candidates who not only possess strong technical skills but also demonstrate excellent problem-solving abilities and a collaborative mindset. These interviews are designed to assess your proficiency in data structures, algorithms, system design, and even behavioral aspects, ensuring you can tackle complex challenges efficiently. Success in a LinkedIn coding interview signifies your readiness to contribute to innovative projects that impact millions of users globally.
What Are LinkedIn Coding Interview Questions?
LinkedIn coding interview questions are technical challenges primarily focused on data structures and algorithms, but also include system design and behavioral questions. They aim to evaluate a candidate's fundamental computer science knowledge, problem-solving skills, and ability to write efficient, clean code. These questions often involve manipulating arrays, linked lists, trees, graphs, and implementing core algorithms like sorting, searching, and dynamic programming. Beyond pure correctness, interviewers also look for optimal solutions in terms of time and space complexity. For senior roles, system design questions assess your ability to architect scalable, reliable, and distributed systems, mirroring the complex infrastructure at LinkedIn. Behavioral questions gauge cultural fit and communication skills, vital for team collaboration.
Why Do Interviewers Ask LinkedIn Coding Interview Questions?
Interviewers at LinkedIn ask coding interview questions for several key reasons. Firstly, they want to assess your fundamental problem-solving abilities. Can you break down a complex problem into smaller, manageable parts? Secondly, they evaluate your understanding of data structures and algorithms, which are the building blocks of efficient software. This ensures you can write performant code that scales. Thirdly, these questions reveal your coding proficiency—your ability to translate logic into clean, debuggable, and maintainable code. Fourthly, they test your communication skills, as you're expected to articulate your thought process, discuss trade-offs, and explain your solution clearly. Lastly, technical interviews, including those with LinkedIn coding interview questions, simulate real-world engineering challenges, providing insight into how you approach and solve problems under pressure, mirroring the daily tasks of an engineer at a company like LinkedIn.
Preview List
How do you find the pivot index in an array?
How do you determine if two strings are isomorphic?
How do you find the second minimum node in a special binary tree?
How do you implement a queue using two stacks?
How do you find the maximum gap between elements after sorting?
How do you create a data structure with O(1) insert, delete, and get random operations?
How do you implement a debounce function in JavaScript?
How would you design a large-scale notification system architecture?
Why are you a suitable candidate for LinkedIn?
How do you reverse a singly linked list?
How do you detect a cycle in a linked list?
How do you merge two sorted linked lists?
How do you find the lowest common ancestor of two nodes in a binary tree?
How do you find the length of the longest substring without repeating characters?
How do you check if a string of parentheses is valid?
How do you find the median of two sorted arrays?
How do you implement an LRU (Least Recently Used) Cache?
How do you search for an element in a rotated sorted array?
How many distinct ways can you climb n stairs?
How do you find the shortest word ladder transformation sequence?
How do you determine if all courses can be finished given prerequisites?
How do you serialize and deserialize a binary tree?
How do you find the container with the most water given an array of heights?
How do you implement a Trie (Prefix Tree)?
How do you find the Kth largest element in an array?
How do you count the number of subarrays whose sum equals K?
How do you rotate an n x n matrix by 90 degrees clockwise?
How do you determine the alien dictionary order of letters?
How do you validate if a binary tree is a valid Binary Search Tree (BST)?
How do you find all unique combinations of numbers that sum up to a target?
1. How do you find the pivot index in an array?
Why you might get asked this:
This question tests your array manipulation skills, prefix sum technique, and ability to handle sums efficiently, crucial for LinkedIn coding interview questions.
How to answer:
Calculate total sum first. Then iterate, maintaining a running leftSum. If leftSum equals totalSum - leftSum - currentElement, return the index.
Example answer:
First, compute the sum of all elements in the array. Then, iterate through the array, maintaining a variable for the sum of elements to the left of the current index. For each element, check if this leftSum is equal to the totalSum minus leftSum and the current element's value. Return the current index if this condition is met; otherwise, continue the iteration.
2. How do you determine if two strings are isomorphic?
Why you might get asked this:
This problem assesses your understanding of hash maps (dictionaries) for character mapping and handling one-to-one correspondence.
How to answer:
Use two hash maps: one for mapping characters from string s to t, and another for mapping t to s. Check consistency in both directions.
Example answer:
Iterate through both strings simultaneously. Use two hash maps: mapstot and mapttos. For each pair of characters schar and tchar, if schar is already mapped in mapstot but not to tchar, return false. Similarly, check mapttos. If no conflict, add the mappings. If you complete the loop, they are isomorphic.
3. How do you find the second minimum node in a special binary tree?
Why you might get asked this:
Tests your ability to traverse binary trees and handle specific constraints (e.g., parent value is min of children) efficiently.
How to answer:
Perform a DFS or BFS traversal. Keep track of two unique minimum values found so far. Update them as you visit nodes.
Example answer:
Initialize min1 to the root's value and min2 to infinity. Perform a depth-first search (DFS) traversal. If a node's value is greater than min1 but less than min2, update min2. If a node's value equals min1, continue DFS on its children as the second minimum could be deeper.
4. How do you implement a queue using two stacks?
Why you might get asked this:
A classic data structure question to test your understanding of stack/queue properties and simulation.
How to answer:
Use one stack for enqueue operations (pushStack). For dequeue (popStack), move elements from pushStack to popStack if popStack is empty, then pop.
Example answer:
Maintain two stacks, inputStack and outputStack. For enqueue, simply push the element onto inputStack. For dequeue, if outputStack is empty, pop all elements from inputStack and push them onto outputStack. Then, pop from outputStack. peek operation is similar to dequeue but without popping.
5. How do you find the maximum gap between elements after sorting?
Why you might get asked this:
Challenges your knowledge of sorting algorithms beyond comparison sorts, hinting at bucket or radix sort for linear time.
How to answer:
If sorting is allowed, sort and then iterate. For linear time, use bucket sort: distribute elements into buckets, then find max gap between min/max of adjacent non-empty buckets.
Example answer:
For a linear time solution, if the range of numbers is known, use bucket sort. Create n-1 buckets for n numbers. Place each number into its corresponding bucket. The maximum gap will be between the maximum element of one non-empty bucket and the minimum element of the next non-empty bucket, or between elements within the same bucket if n is small.
6. How do you create a data structure with O(1) insert, delete, GetRandom?
Why you might get asked this:
This problem tests your creativity in combining data structures to meet strict time complexity requirements.
How to answer:
Combine a hash map (for O(1) insert/delete lookup) with a dynamic array (for O(1) GetRandom and deletion by swapping to end).
Example answer:
Use an ArrayList to store elements and a HashMap to store each element's value mapped to its index in the ArrayList. For insert, add to ArrayList and HashMap. For delete, swap the element to be deleted with the last element in the ArrayList, update its index in the HashMap, then remove the last element. GetRandom is simply ArrayList.get(random_index).
7. How do you implement a debounce function in JavaScript?
Why you might get asked this:
A common frontend system design question, assessing your understanding of asynchronous operations and performance optimization.
How to answer:
Return a function that sets a timer. If the function is called again before the timer expires, clear the old timer and set a new one.
Example answer:
The debounce function takes a function and a delay as arguments. It returns a new function. When this new function is called, it clears any previously set timer. Then, it sets a new timer that will execute the original function after the specified delay, ensuring the original function is only called once after a period of inactivity.
8. How would you design a large-scale notification system architecture?
Why you might get asked this:
A challenging system design question for senior roles, focusing on scalability, reliability, and real-time processing.
How to answer:
Discuss components like message queues (Kafka), push notification services, distributed databases, real-time channels (WebSockets), and error handling/retries.
Example answer:
Design involves a publisher-subscriber model using a message broker (e.g., Kafka) for asynchronous processing and decoupling. Notification services (e.g., AWS SNS, Firebase) handle delivery to various devices. A distributed database stores notification metadata and user preferences. WebSockets can be used for real-time in-app notifications. Include strategies for fault tolerance, scalability, and handling high fan-out scenarios.
9. Why are you suitable for LinkedIn?
Why you might get asked this:
A crucial behavioral question assessing your motivation, cultural fit, and understanding of LinkedIn's mission.
How to answer:
Align your skills and career aspirations with LinkedIn's mission and values. Provide specific examples of how your experience contributes.
Example answer:
My passion for building impactful products aligns perfectly with LinkedIn's mission to connect the world's professionals. My experience in scalable backend systems (mention a specific project) directly applies to LinkedIn's infrastructure. I also value collaboration and continuous learning, which I see as core to LinkedIn's culture. My drive to help others succeed resonates with LinkedIn's user-centric approach.
10. How do you reverse a singly linked list?
Why you might get asked this:
A foundational linked list problem, testing pointer manipulation skills.
How to answer:
Iteratively, keep track of previous, current, and next pointers. In each step, reverse the current node's next pointer.
Example answer:
Initialize prev to null, current to the head of the list. Iterate while current is not null. In each iteration, store current.next in a temporary variable (nexttemp), then set current.next to prev. Update prev to current, and current to nexttemp. Finally, prev will be the new head.
11. How do you detect a cycle in a linked list?
Why you might get asked this:
A classic linked list problem, often solved using Floyd's Tortoise and Hare algorithm.
How to answer:
Use two pointers: a 'slow' pointer moving one step at a time and a 'fast' pointer moving two steps. If they meet, a cycle exists.
Example answer:
Initialize a slow pointer and a fast pointer to the head of the linked list. Move the slow pointer one step at a time, and the fast pointer two steps at a time. If the two pointers ever meet (i.e., point to the same node), then a cycle exists in the linked list. If the fast pointer reaches null or its next is null, no cycle exists.
12. How do you merge two sorted linked lists?
Why you might get asked this:
Tests your ability to handle pointers and build a new list while preserving sorted order.
How to answer:
Create a dummy head node. Iterate, comparing nodes from both lists, appending the smaller one to the merged list. Handle remaining nodes.
Example answer:
Create a dummy node to simplify edge cases. Use a current pointer to traverse the merged list, initially pointing to the dummy node. While both input lists have nodes, compare their current nodes, append the smaller one to current.next, and advance that list's pointer. Finally, append any remaining nodes from either list. Return dummy.next.
13. How do you find the lowest common ancestor of two nodes in a binary tree?
Why you might get asked this:
A common tree traversal problem, often solved with recursion or iterative approaches.
How to answer:
Recursively traverse the tree. If the current node is one of the target nodes or if target nodes are found in different subtrees, it's the LCA.
Example answer:
Implement a recursive DFS function. If the current node is null, or matches one of the target nodes (p or q), return the current node. Recursively call for left and right subtrees. If both recursive calls return a non-null node, it means p and q are in different subtrees, so the current node is the LCA. Otherwise, return the non-null result (if any).
14. How do you find the length of the longest substring without repeating characters?
Why you might get asked this:
A popular string manipulation problem, often solved using the sliding window technique.
How to answer:
Use a sliding window with a hash set to track characters within the current window. Expand the window, shrinking from left if a duplicate is found.
Example answer:
Use a sliding window defined by two pointers, left and right. Maintain a hash set to store characters within the current window. As right moves, add s[right] to the set. If s[right] is already in the set, move left forward and remove s[left] from the set until no duplicates exist. Update the maximum length at each step.
15. How do you check if a string of parentheses is valid?
Why you might get asked this:
A classic stack problem, testing your understanding of Last-In, First-Out (LIFO) structures.
How to answer:
Use a stack. Push opening brackets onto the stack. When a closing bracket appears, pop from the stack and check for a match.
Example answer:
Initialize an empty stack. Iterate through the string. If an opening parenthesis (, {, [ is encountered, push it onto the stack. If a closing parenthesis ), }, ] is encountered, check if the stack is empty or if its top element is the corresponding opening parenthesis. If not, return false. Otherwise, pop the top. After iteration, if the stack is empty, the string is valid.
16. How do you find the median of two sorted arrays?
Why you might get asked this:
A challenging problem often requiring binary search to achieve optimal time complexity.
How to answer:
Use binary search to find a partition point in the smaller array such that, when combined with a corresponding partition in the larger array, the two halves satisfy median conditions.
Example answer:
The goal is to partition both arrays A and B into two parts such that max(leftA, leftB) <= min(rightA, rightB) and the total number of elements in the left parts equals (m+n+1)/2. Perform a binary search on the partition point of the smaller array. Adjust the search range based on the comparison of elements at the partition boundaries.
17. How do you implement an LRU (Least Recently Used) Cache?
Why you might get asked this:
A common design question for interviewers to assess data structure choice and optimization.
How to answer:
Combine a hash map (for O(1) key lookups) with a doubly linked list (to maintain order of usage for O(1) updates to MRU/LRU).
Example answer:
Use a HashMap to store key-node pairs, where the node is from a DoublyLinkedList. The DoublyLinkedList will maintain the order of usage, with the most recently used (MRU) at the head and least recently used (LRU) at the tail. get operations move the accessed node to the head. put operations add new nodes to the head; if capacity is exceeded, remove the tail node.
18. How do you search for an element in a rotated sorted array?
Why you might get asked this:
Tests your ability to adapt standard algorithms like binary search to modified data structures.
How to answer:
Apply a modified binary search. Determine which half of the array is sorted, then check if the target falls within that sorted half to narrow the search.
Example answer:
Perform a binary search. In each step, identify whether the left half or the right half of the array is sorted. If nums[low] <= nums[mid], the left half is sorted. If target is within nums[low] and nums[mid], search left; otherwise search right. If nums[low] > nums[mid], the right half is sorted. If target is within nums[mid] and nums[high], search right; otherwise search left.
19. How many distinct ways can you climb n stairs?
Why you might get asked this:
A classic dynamic programming or recursion problem that often uses Fibonacci sequence logic.
How to answer:
Recognize this as a Fibonacci sequence. The number of ways to climb n stairs is the sum of ways to climb n-1 stairs and n-2 stairs.
Example answer:
This problem can be solved using dynamic programming. Create an array dp where dp[i] stores the number of ways to climb i stairs. Initialize dp[0] = 1 (one way to be at the base) and dp[1] = 1. For i from 2 to n, dp[i] = dp[i-1] + dp[i-2]. The result is dp[n]. This is essentially the Fibonacci sequence.
20. How do you find the shortest word ladder transformation sequence?
Why you might get asked this:
A graph traversal problem that typically uses Breadth-First Search (BFS) to find the shortest path.
How to answer:
Model words as nodes in a graph, with an edge between words differing by one letter. Use BFS to find the shortest path from start to end word.
Example answer:
Create a graph where nodes are words and an edge exists between two words if they differ by exactly one character. Use Breadth-First Search (BFS) starting from the beginWord. Maintain a queue for words to visit and their transformation lengths. Keep track of visited words to avoid cycles. The first time you reach the endWord, the length recorded is the shortest transformation sequence.
21. How do you determine if all courses can be finished given prerequisites?
Why you might get asked this:
A graph problem assessing your knowledge of topological sort or cycle detection in a directed graph.
How to answer:
Model courses and prerequisites as a directed graph. Use topological sort (e.g., Kahn's algorithm or DFS) to detect cycles. If no cycle, courses can be finished.
Example answer:
Represent the courses and their prerequisites as a directed graph. Each course is a node, and a prerequisite creates a directed edge. Use Kahn's algorithm (BFS-based topological sort). Calculate in-degrees for all nodes. Add nodes with in-degree 0 to a queue. Process nodes from the queue, decrementing in-degrees of their neighbors. If the number of processed nodes equals the total courses, no cycle exists, meaning courses can be finished.
22. How do you serialize and deserialize a binary tree?
Why you might get asked this:
Tests your understanding of tree traversals (preorder, BFS) and converting complex structures to linear data.
How to answer:
Use a traversal (e.g., preorder or BFS) to convert the tree to a string, marking null nodes. For deserialization, reconstruct the tree using the same traversal logic.
Example answer:
For serialization, use a preorder traversal. Append the node's value to a string, followed by a delimiter. For null nodes, append a special marker (e.g., "#"). For deserialization, split the string by the delimiter. Use a queue or recursive function to rebuild the tree, consuming elements from the split string and reconstructing nodes based on the preorder sequence.
23. How do you find the container with the most water given an array of heights?
Why you might get asked this:
A problem typically solved with the two-pointer approach, optimizing for time complexity.
How to answer:
Use two pointers, one at each end. Move the pointer pointing to the shorter line inward. Calculate area at each step, update max.
Example answer:
Initialize two pointers, left at the beginning of the height array and right at the end. While left is less than right, calculate the current area as min(height[left], height[right]) * (right - left). Update the maximum area found so far. If height[left] is less than height[right], increment left; otherwise, decrement right. This moves the shorter line inward, as it's the limiting factor for current area.
24. How do you implement a Trie (Prefix Tree)?
Why you might get asked this:
Tests your ability to design and implement a specialized tree data structure for string operations.
How to answer:
Define a TrieNode class with a map for children nodes and a boolean flag for end-of-word. Implement insert, search, and startsWith methods.
Example answer:
Implement a TrieNode class that contains a map of characters to child TrieNodes and a boolean isEndOfWord. The Trie class will have a root node. For insert, traverse/create nodes for each character. For search, traverse until the end of the word and check isEndOfWord. For startsWith, traverse until the prefix is matched.
25. How do you find the Kth largest element in an array?
Why you might get asked this:
A common problem that can be solved efficiently with Quickselect (average O(N)) or a min-heap (O(N log K)).
How to answer:
Use Quickselect (partitioning like Quicksort) to find the element in O(N) average time, or a min-heap of size K in O(N log K).
Example answer:
Using a min-heap (priority queue): Iterate through the array. For each number, add it to the min-heap. If the heap's size exceeds k, remove the smallest element (heap's root). After processing all numbers, the root of the min-heap will be the Kth largest element. This approach ensures the heap always contains the k largest elements seen so far.
26. How do you count the number of subarrays whose sum equals K?
Why you might get asked this:
A common array problem leveraging prefix sums and hash maps for efficient counting.
How to answer:
Use prefix sums. Store cumulative sums and their frequencies in a hash map. For each currentSum, check if currentSum - K exists in the map.
Example answer:
Initialize count = 0 and currentsum = 0. Use a hash map freqmap to store (prefixsum, frequency) pairs, initialized with {0: 1} (for an empty prefix). Iterate through the array: add the current number to currentsum. Check if currentsum - k exists in freqmap. If yes, add its frequency to count. Finally, increment freqmap[currentsum].
27. How do you rotate an n x n matrix by 90 degrees clockwise?
Why you might get asked this:
Tests your ability to manipulate 2D arrays (matrices) efficiently in-place.
How to answer:
Perform a transpose (swap matrix[i][j] with matrix[j][i]), then reverse each row.
Example answer:
First, transpose the matrix: swap elements matrix[i][j] with matrix[j][i] for all i < j. This flips the matrix over its main diagonal. Second, reverse each row of the transposed matrix. This combines to achieve a 90-degree clockwise rotation efficiently in-place.
28. How do you determine the alien dictionary order of letters?
Why you might get asked this:
A graph problem involving topological sort, requiring careful construction of dependencies.
How to answer:
Build a directed graph where an edge u -> v means u comes before v. Perform topological sort. Handle cycles.
Example answer:
Build a directed graph where nodes are characters and edges represent dependencies (e.g., if "abc" comes before "abd", then 'c' comes before 'd'). Iterate through adjacent words to find the first differing character pair, which establishes an edge. Once the graph is built, perform a topological sort (e.g., Kahn's algorithm or DFS) to get the valid character order. If a cycle is detected, no valid order exists.
29. How do you validate if a binary tree is a valid Binary Search Tree (BST)?
Why you might get asked this:
A fundamental tree problem requiring recursive traversal and proper handling of value ranges.
How to answer:
Recursively traverse the tree, passing down min and max bounds for node values. Check if the current node's value is within these bounds.
Example answer:
Implement a recursive helper function isValidBST(node, minVal, maxVal). For each node, check if node.val <= minVal or node.val >= maxVal. If so, return false. Then, recursively call for the left child with (node.left, minVal, node.val) and for the right child with (node.right, node.val, maxVal). The initial call should be isValidBST(root, -infinity, +infinity).
30. How do you find all unique combinations of numbers that sum up to a target?
Why you might get asked this:
A classic backtracking problem that explores all possible paths to a solution.
How to answer:
Use backtracking. Recursively explore combinations, adding numbers to a current combination and subtracting from the target. Handle duplicates.
Example answer:
Implement a recursive backtracking function. It takes the remaining target, currentcombination, and startindex. If target is 0, add currentcombination to results. If target is negative, return. Loop from startindex through candidate numbers. Add candidate[i] to current_combination, recursively call with target - candidate[i], then backtrack by removing candidate[i]. Sort candidates initially to handle duplicates if each number can only be used once.
Other Tips to Prepare for a LinkedIn Coding Interview
Mastering LinkedIn coding interview questions requires more than just memorizing solutions; it demands a deep understanding of concepts and effective communication. One excellent piece of advice is from Lin-Manuel Miranda: "You don't get a chance to be good until you're good." This applies directly to interview preparation—consistent, focused practice is key. Start by solidifying your foundational knowledge in data structures and algorithms. Work through a variety of problems, paying close attention to time and space complexity.
When practicing, always articulate your thought process aloud, just as you would in an actual interview. Explain your approach, discuss trade-offs, and justify your chosen solution. Consider using tools like Verve AI Interview Copilot to simulate real interview scenarios and get instant feedback on your verbal communication and technical accuracy. As Oprah Winfrey wisely stated, "Every experience in your life is being orchestrated to teach you something you need to know to move forward." Embrace each practice problem and mock interview as a learning opportunity. Verve AI Interview Copilot (https://vervecopilot.com) can provide structured practice for LinkedIn coding interview questions, helping you refine your explanations and code-walkthroughs. Leverage its AI-powered insights to identify areas for improvement in your problem-solving approach and communication style, making your preparation more targeted and efficient. Practicing common LinkedIn coding interview questions with a tool like Verve AI Interview Copilot can significantly boost your confidence and performance.
Frequently Asked Questions
Q1: How long is a typical LinkedIn coding interview?
A1: LinkedIn coding interviews usually last 45-60 minutes, including problem solving, coding, and discussion of your approach and complexity.
Q2: Should I focus on a specific programming language?
A2: While LinkedIn doesn't mandate a specific language, be proficient in one you're comfortable with for Data Structures and Algorithms.
Q3: Are behavioral questions common in LinkedIn interviews?
A3: Yes, behavioral questions are integrated into the interview process to assess culture fit and collaboration skills, even in technical rounds.
Q4: What's the best way to practice system design for LinkedIn?
A4: Practice common system design problems like designing Twitter or a URL shortener, focusing on scalability, reliability, and various components.
Q5: How important is time and space complexity?
A5: Very important. Interviewers expect you to analyze your solution's complexity and optimize it to meet given constraints.
Q6: Should I ask questions at the end of the interview?
A6: Absolutely! Asking insightful questions demonstrates your engagement, curiosity, and genuine interest in the role and company.
