Top Alphabet Coding Interview Questions and Answers for Freshers (2026)

These are some of the most frequently asked coding interview questions reported by candidates during Alphabet software engineering interviews. The questions cover problem-solving approaches, arrays, strings, linked lists, stacks, queues, and other core data structures and algorithms.

When I receive a coding problem, I first make sure I understand the requirements, inputs, outputs, constraints, and possible edge cases. If anything is unclear, I ask clarifying questions. After understanding the problem, I begin with a simple or brute-force solution before optimizing it using better algorithms or data structures. Throughout the process, I explain my reasoning clearly because interviewers evaluate both problem-solving ability and communication.

Starting with a brute-force solution demonstrates that I understand the problem fundamentally. It provides a logical starting point, helps analyze time and space complexity, and naturally leads to discussing optimizations. Interviewers often appreciate candidates who improve a simple solution rather than trying to jump directly to the most optimized approach.

If I cannot identify the optimal solution immediately, I remain calm and focus on solving the problem step by step. I explain my initial approach, identify inefficiencies, and gradually optimize the solution. Demonstrating structured thinking is often more valuable than immediately producing the perfect algorithm.

Communication is extremely important because interviewers want to understand how I think. Explaining assumptions, discussing trade-offs, and describing my reasoning allows the interviewer to follow my approach. Even if I make a mistake, clear communication demonstrates strong analytical skills.

Interviewers evaluate problem understanding, algorithm selection, data structure knowledge, coding ability, optimization, edge-case handling, testing habits, and communication. They are interested in the overall problem-solving process rather than only the final solution.

A common approach is to use two pointers. One pointer starts from the beginning of the string and the other starts from the end. The characters are swapped while the pointers move toward each other until they meet. Although many programming languages provide built-in methods, interviewers usually prefer candidates to explain the manual logic.

A palindrome reads the same forward and backward. I compare characters from both ends of the string using two pointers. If every corresponding character matches, the string is a palindrome; otherwise, it is not.

Initialize the first element as the largest value and iterate through the remaining elements. Whenever a larger value is found, update the maximum. This solution requires only one traversal of the array and runs in O(n) time.

Begin by assuming the first element is the smallest. Traverse the array and update the minimum whenever a smaller value is encountered. This also requires only one pass through the array.

Maintain two variables while scanning the array: one for the largest element and another for the second largest. Whenever a new largest value is found, update both variables accordingly. Remember to consider edge cases such as duplicate values or arrays containing fewer than two elements.

A hash set provides an efficient solution. While traversing the array, insert each element into the set. If an element already exists in the set, it is a duplicate. This approach offers O(n) average time complexity.

For an unsorted array, a hash set can be used to retain only unique values. For a sorted array, the two-pointer technique removes duplicates in place while maintaining O(1) extra space.

Initialize a variable with zero and iterate through the array, adding each element to the running total. After completing the traversal, the variable contains the sum of all elements.

Two strings are anagrams if they contain the same characters with identical frequencies. One solution is to sort both strings and compare them. A more efficient approach uses a hash map or frequency array to count character occurrences.

Traverse the string while maintaining a hash map that stores each character and its frequency. Increment the count every time a character appears. This approach runs in O(n) time.

Use two passes. First, count the frequency of every character using a hash map. Then iterate through the string again and return the first character whose frequency equals one.

Kadane's Algorithm provides the optimal solution. It maintains the current running sum and the maximum sum found so far. Whenever the running sum becomes negative, it is reset because continuing would only reduce future sums.

Array rotation can be implemented using an auxiliary array or optimized with the reversal algorithm. The reversal approach rotates the array in place while requiring only constant extra space.

Since both arrays are sorted, maintain one pointer for each array. Compare the current elements and place the smaller one into the result array. Continue until all elements from both arrays have been processed.

One solution calculates the expected sum of numbers from 1 to n and subtracts the actual sum of the array. Another elegant solution uses the XOR operation to identify the missing number.

A linked list is a linear data structure composed of nodes. Each node stores data and a pointer to the next node. Unlike arrays, linked lists do not require contiguous memory, making insertions and deletions more efficient in many scenarios.

A singly linked list stores only the next pointer, while a doubly linked list stores both previous and next pointers. Doubly linked lists support backward traversal but require additional memory.

Maintain three pointers: previous, current, and next. Traverse the list while reversing each node's next pointer. After processing all nodes, the previous pointer becomes the new head of the reversed list.

Floyd's Cycle Detection Algorithm uses two pointers moving at different speeds. One moves one step while the other moves two steps. If they meet, the linked list contains a cycle.

Use the fast and slow pointer technique. The slow pointer advances one node at a time while the fast pointer advances two nodes. When the fast pointer reaches the end, the slow pointer points to the middle node.

Maintain two pointers separated by n nodes. Move both pointers together until the first reaches the end. The second pointer will then be positioned just before the target node, allowing it to be removed in one traversal.

Compare the current nodes of both linked lists and append the smaller node to the result list. Continue until one list is exhausted, then attach the remaining nodes from the other list.

If the head is available, update the previous node's next pointer to bypass the target node. If only the target node is given and it is not the last node, copy the next node's value into the current node and skip the next node.

Linked lists provide efficient insertion and deletion because elements do not need to be shifted. They also support dynamic memory allocation, unlike fixed-size arrays.

Linked lists do not support direct indexing, making random access slower than arrays. They also require extra memory to store pointers and involve more complex pointer manipulation.

A stack is a linear data structure that follows the Last In, First Out (LIFO) principle. Common operations include push, pop, and peek. Stacks are widely used in recursion, expression evaluation, and undo functionality.

A queue follows the First In, First Out (FIFO) principle. Elements are inserted at the rear and removed from the front. Queues are commonly used in scheduling, buffering, and breadth-first search.

A stack removes the most recently inserted element first (LIFO), whereas a queue removes the oldest inserted element first (FIFO). The choice depends on the problem being solved.

Maintain an index representing the top of the stack. During a push operation, increment the index and insert the element. During a pop operation, return the top element and decrement the index. Boundary checks should handle overflow and underflow conditions.