О подготовке к интервью в Google

Get that job at Google

А неплохой у них отбор...
Выдержки:

Algorithm Complexity: you need to know Big-O. It's a must. If you struggle with basic big-O complexity analysis, then you are almost guaranteed not to get hired. It's, like, one chapter in the beginning of one theory of computation book, so just go read it. You can do it.

Sorting: know how to sort. Don't do bubble-sort. You should know the details of at least one n*log(n) sorting algorithm, preferably two (say, quicksort and merge sort). Merge sort can be highly useful in situations where quicksort is impractical, so take a look at it.

For God's sake, don't try sorting a linked list during the interview.

Hashtables: hashtables are arguably the single most important data structure known to mankind. You absolutely have to know how they work. Again, it's like one chapter in one data structures book, so just go read about them. You should be able to implement one using only arrays in your favorite language, in about the space of one interview.

Trees: you should know about trees. I'm tellin' ya: this is basic stuff, and it's embarrassing to bring it up, but some of you out there don't know basic tree construction, traversal and manipulation algorithms. You should be familiar with binary trees, n-ary trees, and trie-trees at the very very least. Trees are probably the best source of practice problems for your long-term warmup exercises.

You should be familiar with at least one flavor of balanced binary tree, whether it's a red/black tree, a splay tree or an AVL tree. You should actually know how it's implemented.

You should know about tree traversal algorithms: BFS and DFS, and know the difference between inorder, postorder and preorder.

You might not use trees much day-to-day, but if so, it's because you're avoiding tree problems. You won't need to do that anymore once you know how they work. Study up!

Graphs

Graphs are, like, really really important. More than you think. Even if you already think they're important, it's probably more than you think.

There are three basic ways to represent a graph in memory (objects and pointers, matrix, and adjacency list), and you should familiarize yourself with each representation and its pros and cons.

You should know the basic graph traversal algorithms: breadth-first search and depth-first search. You should know their computational complexity, their tradeoffs, and how to implement them in real code.

You should try to study up on fancier algorithms, such as Djikstra and A*, if you get a chance. They're really great for just about anything, from game programming to distributed computing to you name it. You should know them.

Whenever someone gives you a problem, think graphs. They are the most fundamental and flexible way of representing any kind of a relationship, so it's about a 50-50 shot that any interesting design problem has a graph involved in it. Make absolutely sure you can't think of a way to solve it using graphs before moving on to other solution types. This tip is important!