Interview Prep

Understanding how programs store and manage data

How programs make decisions and repeat actions

Organizing code into reusable, composable units

Where variables live and how they're accessed

Ordered collections of data and how to work with them

Key-value data structures for modeling real-world entities

Functions that call themselves to solve problems

Advanced patterns for processing collections efficiently

Array operations, two-pointer techniques, and sliding window patterns

Fast key-value lookups using hash functions

Collections of unique values with fast membership testing

Dynamic data structures built from nodes and pointers

Last-In-First-Out data structure for tracking state

First-In-First-Out data structure for ordered processing

Hierarchical data structures with parent-child relationships

Networks of connected nodes for modeling relationships

Organizing data efficiently with different sorting strategies

Finding elements efficiently with linear and binary search

Exploring graphs level by level to find shortest paths

Exploring graphs deeply before backtracking

How to measure and compare algorithm efficiency using Big O notation

The fundamental pattern of modern networked applications

Choosing between a single deployable unit and many small services

Storing computed results to avoid expensive recomputation

Growing your system by adding machines or upgrading existing ones

A single entry point that routes, authenticates, and rate-limits API requests

Organizing data into tables with rows and columns

Speeding up queries with B-tree and hash indexes

Ensuring data consistency with atomic operations

Controlling how concurrent transactions see each other's changes

Independent programs running on your computer and how the OS manages them

Lightweight units of execution within a process

Understanding the difference between managing and executing multiple tasks