tsiege/tech-interview-cheat-sheet

This repository is a study guide for technical job interviews at software companies. Those interviews often test candidates on computer science fundamentals like data structures, algorithms, and how to analyze the speed and memory use of code. The guide is written as a plain summary of those topics, described as the equivalent of a computer science course you might have skipped or forgotten. The content is organized into a few main areas. The first is asymptotic notation, which is the standard way of describing how an algorithm's performance scales as the amount of data grows. It explains the difference between best-case, worst-case, and average-case analysis using Big-O, Big-Omega, and Big-Theta notation. The second major area covers common data structures: arrays, linked lists, hash tables, and binary trees. Each one gets a plain-English definition, notes on what it is good and bad at, and a table of how fast common operations like searching, inserting, and deleting run in different scenarios. The third area covers algorithms, including search methods (breadth-first search and depth-first search) and sorting methods (selection sort, insertion sort, merge sort, and quick sort). Each algorithm gets an explanation of how it works, when to use it, and its time complexity. The repository also includes a set of coding challenges written in TypeScript that are meant to reinforce the concepts described in the guide. These are separate from the written content and linked from the README. The project is community-maintained and accepts corrections and additions through pull requests, provided contributors include a source for any factual changes. It is intended as a supplement for interview preparation, not a replacement for deeper study of any individual topic.