Big-O notation is mantra of engineer. Space and Time complexities are key indispensable piece of knowledge to measure your algorithm and understanding data structures. As a software engineer, your aptitude and problem solving skills are measured in Big-O notation.Mastering complexities is first step in becoming a successful software engineer. There are class of algorithms and their related complexities. It is difficult to remember all of them all the time.
Eric, who created Big-O cheat sheet apparently understood this fact and put them together a quick Big-O notation reference guide for the community. It’s a great place to start learning fundamentals of designing efficient algorithms and solutions.
Big-O Algorithm Complexity Cheat Sheet (Know Thy Complexities!) @ericdrowell
Hi there! This webpage covers the space and time Big-O complexities of common algorithms used in Computer Science. When preparing for technical interviews in the past, I found myself spending hours crawling the internet putting together the best, average, and worst case complexities for search and sorting algorithms so that I wouldn’t be stumped when asked about them. Over the last few years, I’ve interviewed at several Silicon Valley startups, and also some bigger companies, like Google, Facebook, Yahoo, LinkedIn, and eBay, and each time that I prepared for an interview, I thought to myself “Why hasn’t someone created a nice Big-O cheat sheet?”. So, to save all of you fine folks a ton of time, I went ahead and created one. Enjoy! – Eric