I analyzed 1,084 real interview questions from Meta, Google, and Stripe. Here's what 90% have in common.

When we built the InterviewAce question bank, we imported 1,084 verified real interview questions from open-source MIT-licensed GitHub repositories (sudheerj/javascript-interview-questions, learning-zone/python-interview-questions, and twelve others). After tagging every one by topic, difficulty, role, and company pattern, we noticed something surprising: 90% of the questions fall into just five repeating patterns.

If you understand those patterns, you can prepare for almost any FAANG-tier interview without memorising thousands of questions.

Pattern 1: "Explain X — and one thing most engineers get wrong about it."

About 42% of the questions follow this shape. Examples:

• "Explain Python's GIL — and one performance consequence most engineers underestimate."
• "What's the difference between == and equals() in Java? Show me code that demonstrates it."
• "Walk me through what happens when you click submit on a form. Go as deep as you can."

Why this pattern dominates: interviewers don't want to test whether you know a definition; they want to see if you understand the implications of a definition. The answer is never just the definition — it's the definition plus a real-world consequence.

How to prepare: for every core concept (the GIL, JVM garbage collection, JavaScript's event loop, SQL transaction isolation, CAP theorem), write three sentences: (1) what it is, (2) why it matters in production, (3) the specific bug or perf hit people get from misunderstanding it.

Pattern 2: "How would you debug X?"

Roughly 18% of questions test debugging instinct, not theoretical knowledge.

• "A production service is suddenly 50× slower. What's your first 60 seconds?"
• "This SQL query was fast yesterday and is timing out today. What changed?"
• "You ship code on Friday at 5pm. Users start reporting a bug. Walk me through what you do."

Why: real engineering work is mostly debugging. Hiring managers know this. A candidate who can talk through systematic debugging beats one who recites textbook answers.

How to prepare: practice the order of operations out loud. For every debugging question, your answer should be: "First I'd check X. If that's clean, I'd look at Y. Only after both, I'd consider Z." Reciting an order, even an imperfect one, beats jumping straight to the answer.

Pattern 3: "Design something at scale."

14% of questions across all FAANG-tier loops are system design — at L4/Mid you might get one, at L5/Senior you'll get one to two, at L6/Staff every round is design-flavoured. The pattern is identical across companies:

1. Scope the requirements (functional + non-functional)
2. Estimate scale (back-of-envelope numbers)
3. API design
4. Data model
5. Component diagram
6. Drill into one bottleneck
7. Discuss tradeoffs

The questions repeat: URL shortener, Twitter feed, ride-sharing dispatch, distributed rate limiter, news aggregator, Dropbox sync, stock exchange, Google Drive. If you can do 5 of these well, you can do any system design round.

Pattern 4: "Tell me about a time you..."

Behavioral — 15% of all questions, but disproportionately important because they often kill otherwise-strong loops. Amazon's Bar Raiser is the most extreme: every behavioral question maps to one of the 16 Leadership Principles, and a weak behavioral round will sink even a strong technical performance.

The themes repeat:

• Ownership / something outside your role
• A conflict you handled
• A failure you owned
• Influence without authority
• Critical feedback you received
• Prioritisation under competing demands

How to prepare: build a STAR story bank: 8–12 real stories from your career, each ~60 seconds to tell, each mapping to 2–3 themes. Interviewers ask follow-ups; if your stories are real and you've told them out loud, follow-ups are easy. If your stories are fabricated or fuzzy, follow-ups are where you crack.

Pattern 5: "Write code for this."

Only 11% of questions in our hand-curated bank are pure coding problems — but that number is misleading because each FAANG loop also has 2–4 dedicated coding rounds. The coding questions in our bank skew toward "explain this code's bug" / "design this class" rather than LeetCode-style algorithmic problems. For raw algorithms, work through our 100 coding challenges or the LeetCode top-150 list separately.

What this means for your prep

You don't need to memorise 5,000 questions. You need to:

1. Know the 30 core CS concepts cold, plus the production consequence of each (Pattern 1).
2. Practice debugging out loud — narrate your decision tree (Pattern 2).
3. Drill 5 system design archetypes until you can do each in 45 minutes (Pattern 3).
4. Build 8–12 STAR stories that map to common themes, especially Amazon LPs if you're targeting Amazon (Pattern 4).
5. Grind 100 medium LeetCode problems to cover the algorithmic 11% (Pattern 5).

Five focused things. Months of compounding work, not infinite memorisation.

Try the question bank yourself — InterviewAce gives you all 1,084 hand-curated real questions plus 7,476 practice MCQs and 100 coding challenges, free, no credit card. The AI Study Coach can read your practice history and build a personalised prep plan from where you are right now.