Array Questions at Google: What to Expect

Array questions make up over half of Google's technical interview problem pool—a clear signal of their importance. This emphasis exists because arrays are the most fundamental data structure, underpinning everything from strings (character arrays) and hash maps (using arrays for buckets) to dynamic programming tables and system design concepts like ring buffers. Successfully manipulating arrays demonstrates core skills: efficient traversal, in-place operations, managing indices, and translating abstract logic into clean, bug-free code. At Google, where performance at scale is critical, your ability to write optimal array algorithms directly reflects your potential to handle large-scale data processing.

What to Expect — Types of Problems

Google's array problems are rarely about simple iteration. Expect questions that layer multiple concepts to test problem-solving depth. Common patterns include:

• Two Pointers & Sliding Window: Essential for problems involving sorted arrays, subarrays, or removing duplicates. Examples: "3Sum," finding the longest substring without repeating characters (treating the string as a character array).
• Binary Search: Applied not just on sorted arrays but also on the answer space or rotated arrays. Questions test your ability to identify the monotonic condition that makes binary search valid.
• Prefix Sum & Hashing: Used for problems involving subarray sums (e.g., "Subarray Sum Equals K") or finding contiguous sequences. This tests your ability to optimize from O(n²) to O(n) using a hash map to store cumulative data.
• In-place Array Manipulation: A Google favorite, where you must modify the array using O(1) extra space. Problems like "Move Zeroes," "Rotate Array," or the Dutch National Flag problem test careful index management and swap operations.
• Interleaved Concepts: Many problems combine arrays with other structures. For instance, merging intervals (arrays + sorting), using a heap to find the top K frequent elements in an array, or applying dynamic programming on an array (like "House Robber").

How to Prepare — Study Tips with One Code Example

Focus on patterns, not memorization. For each problem type, learn the underlying principle, then practice variations. A key strategy is to manually trace through 2-3 examples on paper before coding to solidify edge case handling. Always state time and space complexity clearly.

A fundamental pattern is the Two-Pointer Swap for In-place Operations. Here is an example for moving all zeros in an array to the end while maintaining the relative order of non-zero elements. The efficient approach uses a "last non-zero found" pointer.

def moveZeroes(nums):
    last_non_zero = 0
    for i in range(len(nums)):
        if nums[i] != 0:
            nums[last_non_zero], nums[i] = nums[i], nums[last_non_zero]
            last_non_zero += 1
    # In-place modification, no return needed

Recommended Practice Order

Build competence sequentially. Start with basic traversal and operations. Then, master two-pointer techniques (including sliding window), as they are incredibly versatile. Move on to binary search applications, followed by prefix sum and hashing patterns. Practice in-place manipulation problems to build index management skills. Finally, tackle problems that combine arrays with sorting, heaps, or dynamic programming. For each category, solve 5-8 problems of varying difficulty to internalize the pattern.

Practice Array at Google