What are the top coding interview questions for Google?

When preparing for a coding interview at Google, it's crucial to practice a range of problems that test your knowledge of algorithms, data structures, and problem-solving skills. Here are some of the top coding interview questions that are commonly asked at Google:

Arrays and Strings

Two Sum:
- Problem: Find two numbers in an array that add up to a specific target.
- Solution: Use a hash map to store the complement of each number as you iterate through the array.
Longest Substring Without Repeating Characters:
- Problem: Find the length of the longest substring without repeating characters.
- Solution: Use a sliding window approach to track the current substring and a set to check for duplicates.
Product of Array Except Self:
- Problem: Return an array where each element is the product of all elements in the original array except the current element.
- Solution: Use two passes: one to accumulate products from the left, and one from the right.

Linked Lists

Merge Two Sorted Lists:
- Problem: Merge two sorted linked lists into one sorted linked list.
- Solution: Use a dummy node to simplify the merging process.
Detect Cycle in a Linked List:
- Problem: Determine if a linked list has a cycle.
- Solution: Use Floyd’s cycle-finding algorithm (tortoise and hare).
Reverse a Linked List:
- Problem: Reverse a singly linked list.
- Solution: Iterate through the list, reversing the pointers as you go.

Trees and Graphs

Lowest Common Ancestor of a Binary Tree:
- Problem: Find the lowest common ancestor of two nodes in a binary tree.
- Solution: Use recursion to traverse the tree and find the split point where the nodes diverge.
Binary Tree Level Order Traversal:
- Problem: Return the level order traversal of a binary tree.
- Solution: Use a queue to perform a breadth-first search (BFS).
Number of Islands:
- Problem: Count the number of islands in a 2D grid of water and land.
- Solution: Use DFS or BFS to explore each island and mark it as visited.

Dynamic Programming

Longest Increasing Subsequence:
- Problem: Find the length of the longest increasing subsequence in an array.
- Solution: Use dynamic programming with a dp array to store the length of the LIS ending at each index.
Coin Change:
- Problem: Find the minimum number of coins needed to make up a given amount.
- Solution: Use a bottom-up dynamic programming approach with an array to store the minimum coins for each amount.
Edit Distance:
- Problem: Compute the minimum number of operations to convert one string to another.
- Solution: Use dynamic programming with a 2D array to track the minimum operations for each substring pair.

Sorting and Searching

Merge Intervals:
- Problem: Merge overlapping intervals.
- Solution: Sort the intervals by start time and then merge overlapping intervals.
Find Peak Element:
- Problem: Find a peak element in an array.
- Solution: Use binary search to find a peak in O(log n) time.
Search in Rotated Sorted Array:
- Problem: Search for a target value in a rotated sorted array.
- Solution: Use binary search with a modified condition to handle the rotation.

Miscellaneous

Median of Two Sorted Arrays:
- Problem: Find the median of two sorted arrays.
- Solution: Use a binary search approach to partition the arrays and find the median.
Word Ladder:
- Problem: Find the length of the shortest transformation sequence from a start word to an end word.
- Solution: Use BFS to explore all possible transformations.
Top K Frequent Elements:
- Problem: Find the k most frequent elements in an array.
- Solution: Use a heap or bucket sort to efficiently find the top k elements.

Practicing these questions will help you build a strong foundation for your Google coding interview. Be sure to understand the underlying principles and techniques used to solve these problems, as variations and follow-up questions are common.

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