5.0: Introduction

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Much of computer science deals with representing and manipulating information. To do this, people have devised various structures for organizing chunks of data in a way that makes it easy to store, search, and retrieve. There’s a whole course in most computer science curricula called “data structures" which covers how to implement these structures in code. In this book, we won’t be talking about the code, but rather the abstract structures themselves. This chapter has a lot of pictures in it, which depict examples of the various structures in a very general way. The concepts here map directly to code when you need to put them into practice.

There are all kinds of data structures — arrays, linked lists, queues, stacks, hashtables, and heaps, to name a few — but they almost all boil down to one of two fundamental kinds of things: graphs, and trees. These are the two structures we’ll focus on in this chapter. A graph is just about the most general structure you can envision: a bunch of scattered data elements that are related to each other in some way. Almost every data structure imaginable can be recast as a type of graph. Trees are sort of a special case of graphs, but also sort of a topic in their own right, kind of like functions were a special type of relation, but also kind of different. A tree can be seen as a type of graph that imposes extra special conditions which give some navigational benefit.