Interview Readiness Master Recap — Complete Cheatsheet for FAANG Coding Loops

Overview#

This is the master reference document for FAANG coding interview readiness. It consolidates the pattern recognition guide, complexity cheatsheet, STAR story LP mapping, UMPIRE checklist, and company-specific rubric into a single reviewable page. Use it on day 4 of the final week as your mock session warm-up, and on interview morning as your 30-minute review.

Why This Matters#

FAANG technical interview preparation culminates in the ability to rapidly recognize a pattern, apply the right algorithm, and communicate the decision clearly — all under time pressure. This master recap exists because candidates who can retrieve the right pattern in under 30 seconds consistently outperform candidates who know the same patterns but cannot access them quickly under stress.

Pattern recognition speed is a trainable skill. Reading this reference daily in the final week builds retrieval fluency across all major algorithm families simultaneously.

Pattern Recognition — At a Glance#

Use these signals to identify the correct algorithm family within the first 2 minutes of reading a problem:

Input is sorted?
  -> Binary search or two pointers
 
Find all combinations, subsets, or permutations?
  -> Backtracking
 
Shortest path or fewest steps?
  -> BFS
 
Any valid path or all paths?
  -> DFS
 
Minimum cost or maximum value?
  -> Dynamic programming
 
Overlapping intervals?
  -> Sort by start, then greedy merge or heap
 
Top K elements?
  -> Min-heap of size K
 
Substring or subarray with a constraint?
  -> Sliding window
 
Contiguous subarray sum equals target?
  -> Prefix sum plus hash map
 
Frequency counting or duplicates?
  -> Hash map or Counter
 
Prefix match or autocomplete?
  -> Trie
 
Range queries on an array?
  -> Segment tree or binary indexed tree
 
Graph connectivity?
  -> Union-Find (disjoint set)
 
Ordering with dependencies?
  -> Topological sort (BFS with in-degree or DFS)
 
Running median or dual priority queues?
  -> Two heaps (max-heap left, min-heap right)
 
Next greater or next smaller element?
  -> Monotonic stack

Complexity Cheatsheet#

The STAR Story Index with LP Mapping#

For each of the 10 must-prepare stories, the primary Amazon LP and Google signal:

Story 1: Biggest impact project
  Amazon: "Deliver Results" / "Invent and Simplify"
  Google: Technical depth, scale thinking
 
Story 2: Disagreed with manager on a technical decision
  Amazon: "Have Backbone; Disagree and Commit"
  Google: Emergent leadership, comfort with ambiguity
 
Story 3: Failed and recovered
  Amazon: "Learn and Be Curious"
  Google: Intellectual humility, growth mindset
 
Story 4: Learned a new technology quickly
  Amazon: "Learn and Be Curious"
  Google: Adaptability, passion for hard problems
 
Story 5: Decision with incomplete information
  Amazon: "Bias for Action" / "Are Right, A Lot"
  Google: Comfort with ambiguity
 
Story 6: Improved a process or system
  Amazon: "Invent and Simplify" / "Frugality"
  Google: Systems thinking, impact
 
Story 7: Received tough feedback
  Amazon: "Earn Trust"
  Google: Collaboration, coachability
 
Story 8: Mentored someone or helped a teammate
  Amazon: "Hire and Develop the Best"
  Google: Emergent leadership, collaboration
 
Story 9: Competing priorities with a hard deadline
  Amazon: "Deliver Results"
  Google: Execution under pressure
 
Story 10: Went above and beyond defined scope
  Amazon: "Ownership" / "Customer Obsession"
  Google: Initiative, passion

The UMPIRE Checklist — Per Problem#

Run this checklist on every problem in every round:

U — Understood?
  Restated the problem in your own words?
  Asked about input range, duplicates, edge cases?
 
M — Matched?
  Named the pattern family?
  Explained why this pattern fits?
 
P — Planned?
  Wrote pseudocode or named data structures before coding?
  Estimated brute force complexity first?
 
I — Implemented?
  Clean code with descriptive variable names?
  Helper functions for complex sections?
 
R — Reviewed?
  Traced through the given example step by step?
  Tested at least one edge case?
 
E — Evaluated?
  Stated exact time complexity with reasoning?
  Stated exact space complexity with reasoning?
  Said it proactively, not after being asked?

Company Quick Reference#

Closing Mindset — Three Principles for Interview Day#

Principle 1: The interviewer wants you to succeed. Interviewers are not adversaries. They are team members evaluating whether they want to work with you. They are rooting for you to perform well. A hint is not a trap — it is them trying to help.

Principle 2: Communication over cleverness. A clearly explained O(n squared) solution with proactive edge case handling and a correct complexity analysis scores higher than a silent O(n) solution with no explanation. Interviewers cannot score what they cannot observe.

Principle 3: Progress is visible. Saying "I would start with X, optimize to Y given more time, and the main edge case I would handle is Z" demonstrates engineering judgment even if you do not finish. Showing structured progress on an incomplete problem scores significantly higher than submitting a silent broken solution.

Common Mistakes#

• Reading this recap for the first time on interview morning — it should be a familiar document by then
• Using the pattern cheatsheet as a lookup table during the interview instead of internalizing it beforehand
• Skipping the UMPIRE checklist under time pressure — it is fastest to run through it quickly than to debug a missed constraint later
• Not preparing a company-specific behavioral angle for each story in the STAR index
• Forgetting that communication is scored — closing the problem correctly is as important as solving it

Interview Tips#

• Read the pattern recognition section aloud once per day in the final week to build retrieval speed
• Practice the closing statement until it is automatic: "Time is O(...), space is O(...), I traced the example and handled the edge case. Happy to discuss optimizations or follow-ups."
• For the company quick reference table, memorize your target company's row before day 1
• The three closing mindset principles work best when you read them 30 minutes before the interview starts, not the night before
• After every interview, write down every problem asked — it is data for future preparation

Key Takeaways#

• Pattern recognition speed is trainable — reading the pattern cheatsheet daily in the final week builds retrieval fluency
• The 16-signal pattern guide covers every major algorithm family tested at FAANG companies
• The complexity cheatsheet covers 12 fundamental data structures and algorithms with exact time and space bounds
• Each STAR story maps to specific Amazon LPs and Google Googleyness signals — use both mappings in preparation
• The UMPIRE checklist ensures you never skip a scored phase under time pressure
• Company rubrics differ: Google scores approach discussion, Meta scores speed, Amazon scores LP alignment
• Communication over cleverness is the single most important principle — interviewers score what they can observe
• The closing statement — complexity, verification, invitation for follow-up — is the last scored behavior of every round