Ebook Size : 12 MB
Download : Algorithms 4th Edition (PDF)
Online course. You can take our free Coursera MOOCs Algorithms, Part I and Algorithms, Part II. They include a full set of lecture videos and assessments.
The objective of this book is to study a broad variety of important and useful algorithms—methods for solving problems that are suited for computer implementation. Algorithms go hand in hand with data structures—schemes for organizing data that leave them amenable to efficient processing by an algorithm. This chapter introduces the basic tools that we need to study algorithms and data structures.
First, we introduce our basic programming model. All of our programs are implemented using a small subset of the Java programming language plus a few of our own libraries for input/output and for statistical calculations. Section 1.1 is a summary of language constructs, features, and libraries that we use in this book. Next, we emphasize data abstraction, where we define abstract data types (ADTs) in the service of modular programming. In Section 1.2 we introduce the process of implementing an ADT in Java, by specifying an applications programming interface (API) and then using the Java class mechanism to develop an implementation for use in client code.
As important and useful examples, we next consider three fundamental ADTs: the bag, the queue, and the stack. Section 1.3 describes APIs and implementations of bags, queues, and stacks using arrays, resizing arrays, and linked lists that serve as models and starting points for algorithm implementations throughout the book. Performance is a central consideration in the study of algorithms. Section 1.4 describes our approach to analyzing algorithm performance. The basis of our approach is the scientific method: we develop hypotheses about performance, create mathematical models, and run experiments to test them, repeating the process as necessary.