Array Questions at Meta: What to Expect

Array questions make up nearly half of Meta’s technical interview problems. This isn’t a coincidence. Meta’s products—from Facebook’s News Feed to Instagram’s Reels—rely heavily on efficiently processing, filtering, and ranking streams of data. These data streams are fundamentally represented and manipulated as arrays or sequences. Your ability to solve array problems directly demonstrates your capacity to handle the core data transformations that power social platforms. Expect these questions to test not just your coding skills, but your optimization mindset and ability to reason about real-time data processing at scale.

What to Expect — Types of Problems

Meta’s array questions are designed to be practical and layered. You will rarely see a simple “reverse an array” problem. Instead, expect problems that combine multiple concepts. The most common types are:

1. Two Pointers & Sliding Window: Used for problems involving subarrays, sorted arrays, or removing duplicates. Think “find a contiguous subarray with a target sum” or “merge two sorted arrays.”
2. Hash Map for Frequency/Index Tracking: Essential for problems involving pairs, duplicates, or needing O(1) lookups. Examples include “Two Sum” and finding subarrays with a specific property.
3. In-place Array Manipulation: Tests your ability to modify an array without extra space, a key skill for memory-efficient systems. Problems often involve reordering elements (like moving zeros) or applying rotations.
4. Intervals: Common for modeling real-world scheduling or merging events, like “merge overlapping intervals” or “insert a new interval.”
5. Binary Search on Sorted Arrays: Goes beyond simple lookup to find boundaries, peaks, or rotated points in data streams.

Problems often combine these patterns. For instance, a question might require using a hash map to enable a two-pointer solution.

How to Prepare — Study Tips with One Code Example

Focus on mastering the patterns, not memorizing solutions. For each problem type, learn the underlying logic and practice variations. Always articulate your thought process before coding. Start with a brute force solution, then optimize. Time and space complexity analysis is non-negotiable.

A fundamental pattern is the Two Pointer technique for removing duplicates from a sorted array in-place. This is a classic test of efficient in-place manipulation.

def removeDuplicates(nums):
    if not nums:
        return 0
    # `write_index` points to the last position of the unique array
    write_index = 1
    for read_index in range(1, len(nums)):
        if nums[read_index] != nums[read_index - 1]:
            nums[write_index] = nums[read_index]
            write_index += 1
    # The first `write_index` elements are now unique
    return write_index

The key is using one pointer (read_index) to scan the array and another (write_index) to track the position for the next unique element. This runs in O(n) time and O(1) space.

Recommended Practice Order

Build your skills progressively:

1. Start with fundamental in-place operations (remove element, move zeros).
2. Master Two Sum and its variants using hash maps.
3. Practice two-pointer techniques on sorted arrays (pair sum, removing duplicates).
4. Tackle sliding window problems for subarrays.
5. Move to interval merging and insertion.
6. Finally, combine patterns in harder problems like trapping rain water or product of array except self.

This order builds from single-concept to multi-pattern problems, mirroring the increasing complexity in interviews.

Practice Array at Meta