Airbnb vs Expedia: Interview Question Comparison

When preparing for technical interviews at major travel tech companies, understanding the specific focus of each company's question bank can significantly streamline your study process. Both Airbnb and Expedia ask fundamental data structure and algorithm questions, but their distributions of difficulty and emphasis on certain problem-solving patterns differ in meaningful ways. A targeted approach, based on these profiles, will yield more efficient preparation.

Question Volume and Difficulty

Airbnb's list contains 64 questions, categorized as 11 Easy, 34 Medium, and 19 Hard. This distribution indicates a strong emphasis on Medium and Hard problems, suggesting interviews are designed to assess candidates on complex problem-solving and optimization. You should be prepared for multi-step problems that may combine concepts.

Expedia's list is slightly smaller at 54 questions, with a breakdown of 13 Easy, 35 Medium, and only 6 Hard. This profile is notably more centered on Medium-difficulty problems, with a much lighter tail of Hard questions. The interview process here likely focuses on robust implementation of standard algorithms and clean code, with fewer "trick" or extreme optimization problems.

Key Takeaway: Prioritize mastering Medium problems for both, but allocate more time to practicing Hard problems for Airbnb.

Topic Overlap

Both companies heavily test core computer science fundamentals. The top three topics for each are nearly identical:

• Array, String, Hash Table: These are the absolute essentials. Expect problems involving manipulation, searching, and transformation of these data structures.

The primary difference lies in the fourth most frequent topic:

• Airbnb: Dynamic Programming (DP). This aligns with their higher count of Hard problems. DP questions test optimal substructure and memoization/ tabulation in complex scenarios.
• Expedia: Greedy Algorithms. This suggests a focus on problems where a locally optimal choice leads to a global solution, often involving sorting, scheduling, or resource allocation.

This divergence in pattern emphasis should guide your topic-specific practice.

# Example: A Greedy problem (likely for Expedia)
def max_meetings(start, end):
    meetings = sorted(zip(start, end), key=lambda x: x[1])
    count, last_end = 0, 0
    for s, e in meetings:
        if s >= last_end:
            count += 1
            last_end = e
    return count

# Example: A DP problem (likely for Airbnb)
def coin_change(coins, amount):
    dp = [float('inf')] * (amount + 1)
    dp[0] = 0
    for i in range(1, amount + 1):
        for coin in coins:
            if coin <= i:
                dp[i] = min(dp[i], dp[i - coin] + 1)
    return dp[amount] if dp[amount] != float('inf') else -1

Which to Prepare for First

Prepare for Expedia first. Its focus on a high volume of Medium problems with a clear emphasis on Greedy algorithms provides a strong, manageable foundation. Mastering this core will build fluency with Arrays, Strings, and Hash Tables—skills that are 100% transferable to Airbnb's list. Once comfortable with Expedia's profile, transition to Airbnb preparation by layering on dedicated practice for Dynamic Programming and tackling a greater number of challenging Hard problems. This progression builds competence efficiently.

For the complete and updated question lists, visit the CodeJeet pages for Airbnb and Expedia.