Introduction

In Chapter 25, we discussed how to create and manipulate data structures. The discussion was "low level," in the sense that we painstakingly created each element of each data structure dynamically with new and modified the data structures by directly manipulating their elements and references to their elements. In this chapter, we consider the prepackaged data-structure classes provided by the .NET Framework. These classes are known as collection classesthey store collections of data. Each instance of one of these classes is a collection of items. Some examples of collections are the cards you hold in a card game, the songs stored in your computer, the real-estate records in your local registry of deeds (which map book numbers and page numbers to property owners), and the players on your favorite sports team.

Collection classes enable programmers to store sets of items by using existing data structures, without concern for how they are implemented. This is a nice example of code reuse. Programmers can code faster and expect excellent performance, maximizing execution speed and minimizing memory consumption. In this chapter, we discuss the collection interfaces that list the capabilities of each collection type, the implementation classes and the enumerators that "walk through" collections.

The .NET Framework provides three namespaces dedicated to collections. The System.Collections namespace contains collections that store references to objects. The newer System.Collections.Generic namespace contains generic classes to store collections of specified types. The newer System.Collections.Specialized namespace contains several collections that support specific types, such as strings and bits. You can learn more about this namespace at msdn2.microsoft.com/en-us/library/system.collections.specialized.aspx. The collections in these namespaces provide standardized, reusable components; you do not need to write your own collection classes. These collections are written for broad reuse. They are tuned for rapid execution and for efficient use of memory. As new data structures and algorithms are developed that fit this framework, a large base of programmers already will be familiar with the interfaces and algorithms implemented by those data structures.