Prepare for your Google coding interview

Algorithms and data structure rounds calibrated to Google's focus on algorithm fundamentals, optimization, and problem-solving at scale.

Socratify AI

The Interview

What Google is looking for

Easy Interview

Easy Coding Problems

01Array Operations

02String Manipulation

03Basic Algorithms

04Implementation Clarity

Medium Interview

Medium Coding Problems

01Algorithm Selection

02Time Complexity Optimization

03Data Structure Application

04Edge Case Handling

Hard Interview

Hard Coding Problems

01Complex Algorithm Design

02Space-Time Trade-offs

03Advanced Data Structures

04System-Level Thinking

Google-level algorithm depth and scale thinking//Strong focus on fundamentals and clean code//Optimization and complexity analysis rigor

Practice Library

Google exercises

Ready to ace your Google coding interview?

Prepare for your Google coding interview

Algorithms and data structure rounds calibrated to Google's focus on algorithm fundamentals, optimization, and problem-solving at scale.

Socratify AI

The Interview

What Google is looking for

Easy Interview

Easy Coding Problems

01Array Operations

02String Manipulation

03Basic Algorithms

04Implementation Clarity

Medium Interview

Medium Coding Problems

01Algorithm Selection

02Time Complexity Optimization

03Data Structure Application

04Edge Case Handling

Hard Interview

Hard Coding Problems

01Complex Algorithm Design

02Space-Time Trade-offs

03Advanced Data Structures

04System-Level Thinking

Google-level algorithm depth and scale thinking//Strong focus on fundamentals and clean code//Optimization and complexity analysis rigor

How It Works

Master Google Coding Interviews

Algorithm and data structure problems scored on correctness, optimization, and code clarity. · Click to expand

1Your Coding Goals

Algorithm Design

Practitioner

Data Structure Mastery

Practitioner

2Coding Case Prep

Given an unsorted array of integers, find two numbers that add up to a target. Optimize...

LEARNMedium

Google

3Frameworks

Framework

Is time complexity the bottleneck?

Are you sorting more times than necessary?

Current: O(n log n) sort on all 50M events

With heap: O(n log k) where k=top 100 events, 2.1s vs 12s

Are lookups in the query linear scan?

Linear scan of 50M events per request: 400ms per query

Hash table index: 2ms lookup, trade 8GB memory vs 400ms latency

Is space complexity acceptable?

Is caching missing intermediate results?

Recalculate top 100 for every region: 8 regions × 50M events

Materialized view with 10-minute TTL: 800 cached results, 95% hit rate

Are data structures bloated?

Full event object in memory: 2KB per event × 50M = 100GB footprint

Store only ID + timestamp: 48 bytes per event = 2.4GB, sorted index

Are there correctness gaps for edge cases?

Does the algorithm handle deleted events?

Naive: delete event from timeline, breaks iteration on live reads (race)

Soft delete with version vector: O(1) mark, consistency preserved

Are concurrent writes handled?

Two threads insert same event ID: duplicate in result

4Feedback

Algorithm Correctness

Distinctive

Complexity Analysis

Strong

Code Clarity

Meeting Bar

Optimization Mindset

Strong

Repeat

Practice Library

Google exercises

Given an unsorted array of integers, find three numbers that sum to a target value....

LEARNMedium

Technology · Array/Hash TableGoogle

Implement a function to find the longest palindromic substring in O(n²) time and O(1)...

CASE INTERVIEWHard

Technology · String/Dynamic ProgrammingGoogle

Design an algorithm to serialize and deserialize a binary search tree.

CASE INTERVIEWHard

Technology · Tree/DFSGoogle

Walk me through your approach to solving a coding problem under time pressure.

BEHAVIORALMedium

Behavioral · Problem-Solving ApproachGoogle

Tell me about a time you optimized code and the impact it had.

BEHAVIORALMedium

Behavioral · Technical GrowthGoogle