这是之前 Google HR 为了可以让我好好准备面试而给我的一份资料。现在分享出来。
Google interviews focus very heavily on algorithms and data structures. Please study more complex and advance Algorithms and Data Structure and also you’ll be expected to know and apply: lists, maps, stacks, priority queues, binary trees, graphs, bags, and sets. You’ll need to talk about how they’re implemented and why you’d choose one implementation or data structure instead of another.
For algorithms you’ll want to know greedy algorithms, divide and conquer, dynamic programming, recursion, and brute force search. You’ll definitely want to be conversant with bigO notation, timespace complexity, and real world performance of all of this. Most importantly you’ll need to be able to pick the right data structure and algorithm for a specific problem.
Practice your coding in a google doc without a compiler as opposed to a plain text editor to avoid any confusion throughout the interview.
You can utilise a platform called “Pramp https://pramp.com/#/“ which enables candidates to practice mock interviews with each other online. Note that the difficulty of the problems will vary but it is a good method for “warming up!”
Preparation:
Start with Steve Yegge’s Blog.
Google interviews focus very heavily on algorithms and data structures. You’ll be expected to know and apply: lists, maps, stacks, priority queues, binary trees, graphs, bags, and sets. You’ll need to to talk about how they’re implemented and why you’d choose one implementation or data structure instead of another. For algorithms you’ll want to know greedy algorithms, divide and conquer, dynamic programming, recursion, and brute force search. You’ll definitely want to be conversant with bigO notation, timespace complexity, and real world performance of all of this. Most importantly you’ll need to be able to pick the right data structure and algorithm for a specific problem.
Suggestions on reading material include:
- Algorithm / Data Structure Theory books
- Google Style Guides (C++, Python, Java; Android, Javascript)
- Coursera - Algorithms, Part 1
- Coursera - Algorithms, Part 2
- Udacity - Intro to Algorithms
- MIT Open courseware - Introduction to Algorithms
Moving onto the practice after theory:
When you practice, do not use an IDE. You need to be able to write legible, compilable code without help with regards to layout, or spelling of standard library class/method names. I suggest solving similar style algorithmic/ DS problems on a google document or on paper to simulate a real interview. I would recommend using a whiteboard to practice, if you can do it on a whiteboard, you can do it on anything.
Several sites that provide similar problems to those typically asked in the interview are:
- HackerRank
- Topcoder
- Project-Euler
- Codeforces
- Leetcode
- InterviewBit
- Kattis
- Problems from Cracking the Coding Interview Book
This will help get you into the problem-solving mindset.
Here are a couple of extra videos which are definitely worth watching before your interview:
- Example of a Coding Interview
- How to best prepare for a technical interview: Preparation
以上为 HR 提供的部分资料。
其他
Google 整体面试流程上基本如下:
- Recruiter Prescreen
- Phone Interview (1~2 sessions)
- Onsite Interview (4~5 sessions, 1 week to receive feedback)
- Hiring Committee Review
- Offer Review
- Offer Delivery (Yippee!)
基本是 1 轮电话面试, 5 轮 onsite, onsite 难度比 online 要高，要在 google doc 或白板上写代码，基本是 Algorithm, System Design 和 OO Design.
如何获取面试机会？
- 参加 Google Code Jam, 并成为 top xx.
- 参加 Google Kickstart, 并成为 top xx.
- 内推.