Microsoft vs Apple: Interview Question Comparison

When preparing for technical interviews at top tech companies, understanding their specific focus areas can significantly streamline your study. Microsoft and Apple, while both giants, present distinct interview landscapes in terms of question volume, difficulty distribution, and topical emphasis. This comparison breaks down their profiles to help you prioritize your preparation effectively.

Question Volume and Difficulty

The most striking difference is the sheer volume of available practice questions. Microsoft's catalog is vast, with 1,352 documented questions, dwarfing Apple's 356. This volume suggests a broader, more established set of patterns and a wider range of problems you might encounter.

The difficulty distribution also reveals different hiring pipelines. Microsoft's spread is 379 Easy, 762 Medium, and 211 Hard questions. This indicates a strong emphasis on Medium-difficulty problems, which are the core of most coding interviews, with a substantial pool of Hard questions for more advanced roles. Apple's distribution is 100 Easy, 206 Medium, and 50 Hard. While still Medium-heavy, the proportion of Hard questions is slightly lower relative to its total, and the overall smaller pool might suggest a more curated or role-specific question set. For both, mastering Medium problems is the critical first step.

Topic Overlap

Both companies heavily test the same four fundamental data structures and algorithms: Array, String, Hash Table, and Dynamic Programming. This core overlap means a strong foundation in these areas serves you for interviews at either company.

• Array and String manipulation is ubiquitous, covering everything from two-pointer techniques to sliding windows.
• Hash Tables are essential for optimizing lookups and solving frequency-counting problems.
• Dynamic Programming is a key area for assessing problem-solving and optimization skills, especially for medium and hard questions.

Given this overlap, a robust study plan built around these topics is universally beneficial. You can practice core patterns with examples in multiple languages:

# Example: Two-pointer for a sorted array (common in Array problems)
def two_sum_sorted(numbers, target):
    left, right = 0, len(numbers) - 1
    while left < right:
        current_sum = numbers[left] + numbers[right]
        if current_sum == target:
            return [left + 1, right + 1]
        elif current_sum < target:
            left += 1
        else:
            right -= 1
    return [-1, -1]