各种算法的复杂度
你好，这个页面涵盖了计算机科学中常用算法的时间和空间复杂度。在准备过去的技术采访中，我自己花了几个小时爬取网页，把搜索、排序算法中最好情况、最坏情况以及平均情况时间复杂度的内容汇总到一起，这样我就不会在被问及这些问题时被难住了。在过去的几年里，我采访了硅谷的几家初创公司，以及一些大公司，例如谷歌、Facebook、雅虎、LinkedIn和Uber，每次我准备采访时，我都会想“为什么没有人创建一个好的大O备忘单呢？”。所以，为了给你们这些好人节省很多时间，我创造了一个。享受吧！
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 Uber, 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!
大O复杂度统计图
Big-O Complexity Chart
常用数据结构操作
Common Data Structure Operations
线性排序算法
Array Sorting Algorithms
官方网站 Big-O 统计数据图
Get the Official Big-O Cheat Sheet Poster
