Expected answer points:

• Don't panic — say out loud what you know about the problem
• Try to classify it: sliding window, DFS, DP, etc.
• Start with brute force, then optimize
• Ask clarifying questions — interviewers often give hints
• Signal when you're stuck — they want to see your thinking process

Expected answer points:

• Accuracy over speed — incomplete but correct beats buggy and rushed
• Target: Easy in 10-15 min, Medium in 20-30 min
• Speed comes from pattern recognition after 100+ problems
• Taking 45 min on Easy signals lack of practice

Expected answer points:

• Verify solution with multiple examples
• Discuss edge cases: empty input, all same elements, overflow
• Expect optimization questions — improve space or time
• Show different approaches and compare trade-offs

Expected answer points:

• Start by clarifying requirements — functional and non-functional
• Design for scale: consider read/write volume, latency targets
• Discuss trade-offs: SQL vs NoSQL, caching strategies, sharding
• Use top-down approach: API design → data model → infrastructure
• Practice common patterns: URL shortener, chat system, feed ranking

Expected answer points:

• Customer Obsession, Ownership, Invent & Simplify, Learn & Be Curious
• Disagree & Commit, Deliver Results, Dive Deep, Bias for Action
• Prepare 2-3 STAR stories per principle from real experience
• Focus on specific outcomes and measurable impact

Expected answer points:

• Stay professional and don't take it personally
• Focus on the problem — your code speaks for itself
• Ask clarifying questions to redirect conversation
• If it becomes abusive, you can report after — don't burn bridges

Expected answer points:

• Yes — state Big O before writing code: "I'll use O(n) time, O(1) space"
• After solving, revisit and discuss optimization opportunities
• Interviewers expect you to know complexity for every solution

Expected answer points:

• Google focuses on General Cognitive Ability (GCA) — how you learn
• Prepare stories showing problem-solving, not just technical skills
• Practice explaining your thought process, not just outcomes
• Know Google's mission and be ready to discuss alignment

Expected answer points:

• Focus on understanding patterns, not memorizing solutions
• Solve problems daily using spaced repetition
• Practice out loud to simulate interview conditions
• Use timed sessions to build speed and pressure tolerance
• Review failed problems within 24 hours to reinforce learning

Expected answer points:

• Still go through the problem-solving process — don't just blurt the answer
• Admit you've seen it but walk through your reasoning anyway
• Discuss alternative approaches to show deeper understanding
• Focus on clean implementation and edge cases

Expected answer points:

• Use whatever you're most comfortable with — Python, Java, C++, Go all work
• Python is popular for its readability and speed of implementation
• Java and C++ are preferred at companies with legacy codebases
• Avoid languages you're learning during prep — stick to mastery

Expected answer points:

• Always state Big O before writing code: "This runs in O(n) time, O(1) space"
• Consider best, average, and worst case scenarios
• Know when to use amortized analysis for dynamic data structures
• Explain trade-offs between time and space complexity

Expected answer points:

• Don't panic — everyone writes buggy code under pressure
• Read your code aloud while tracing through test cases
• Use small test inputs to isolate the bug systematically
• Fix the bug, then verify with additional test cases
• Ask if the interviewer wants you to walk through the fix

Expected answer points:

• Meta expects quick solution framing — practice problem decomposition
• Write code cleanly on first attempt — re-checking wastes time
• Expect rapid follow-ups: edge cases, optimize, alternate approaches
• Focus on recursion and tree problems — common at Meta
• Speed matters more at Meta than other companies

Expected answer points:

• Yes — clarifying questions show structured thinking
• Ask about input size, constraints, and edge cases upfront
• Confirm if the function signature matters or can be customized
• State your assumptions and wait for confirmation
• Good questions demonstrate professional communication skills

Expected answer points:

• Stay calm — follow-ups are a sign you're doing well
• Prioritize: solve the base problem first, then optimize
• Think out loud: "Let me think about this..."
• If stuck, ask for a hint — interviewers want you to succeed
• Document your thought process even if you can't complete all follow-ups

Expected answer points:

• Apple emphasizes clean, readable code and OOP design
• Less focus on dynamic programming, more on practical problem-solving
• System design matters more for senior roles
• Prepare to discuss trade-offs in your solutions
• Show passion for Apple's products and values

Expected answer points:

• Practice under pressure with mock interviews on Pramp
• Use deep breathing before the interview starts
• Remember: the interviewer wants you to succeed
• Focus on the problem, not the outcome — one bad round doesn't fail you
• Prepare STAR stories for behavioral questions to feel confident

Expected answer points:

• Phone screens: collaborative coding on shared doc, less time pressure
• On-site: 4-5 rounds, harder problems, whiteboarding required
• On-site includes behavioral and system design (senior roles)
• On-site tests endurance — manage energy across multiple rounds
• Both require same preparation rigor and communication skills

Expected answer points:

• First get a working solution — correctness over optimization
• Check if interviewer asks for better time/space complexity
• Look for O(n²) that can become O(n) or O(n log n)
• Consider if hash maps can replace nested loops
• Final answer: "I can optimize to O(n) time with O(n) space using a hash map"