Outline of our Study

This text follows a bottom up approach to the study of computer science, beginning with such hands-on topics as computer hardware and leading to the more abstract topics such as algorithm complexity and computability. The result is that our study follows a pattern of building larger and larger abstract tools as our understanding of the subject expands. We begin by considering topics dealing with the design and construction of machines for executing algorithms. In Chapter 1 (Data Storage) we look at how information is encoded and stored within modern computers, and in Chapter 2 Data Manipulation) we investigate the basic internal operation of a simple computer. Although part of this study involves technology, the general theme is technology independent. That is, such topics as digital circuit design, data encoding and compression systems, and computer architecture are relevant over a wide range of technology and promise to remain relevant regardless of the direction of
future technology.
We study the software that controls the overall operation of a computer. This software is called an operating system. It is a computer’s operating system that controls the interface between the machine
and its outside world, protecting the machine and the data stored within from unauthorized access, allowing a computer user to request the execution of various programs, and coordinating the internal activities required to fulfill the user’s requests.
We study how computers are connected to each other to form computer networks and how networks are connected to form internets. This study leads to topics such as network protocols, the Internet’s structure and internal operation, the World Wide Web, and numerous issues of security.
Algorithms introduces the study of algorithms from a more formal perspective. We investigate how algorithms are discovered, identify several fundamental algorithmic structures, develop elementary techniques for representing algorithms, and introduce the subjects of algorithm efficiency
and correctness.
Programming Languages we consider the subject of algorithm representation and the program development process. Here we find that the search for better programming techniques has led to a variety of programming methodologies or paradigms, each with its own set of programming languages. We investigate these paradigms and languages as well as consider issues of grammar
and language translation.
Software Engineering introduces the branch of computer science known as software engineering, which deals with the problems encountered when developing large software systems. The underlying theme is that the design of large software systems is a complex task that embraces problems beyond those of traditional engineering. Thus, the subject of software engineering has become an important field of research within computer science, drawing from such diverse fields as engineering, project management, personnel management, programming language design, and even architecture.
In next two chapters we look at ways data can be organized within a computer system.
Data Abstractions we introduce techniques traditionally used for organizing data in a computer’s main memory and then trace the evolution of data abstraction from the concept of primitives to today’s objectorientedtechniques.
Database Systems we consider methods traditionally used for organizing data in a computer’s mass storage and investigate how extremely large and complex database systems are implemented.
Computer Graphics we explore the subject of graphics and animation, a field that deals with creating and photographing virtual worlds. Based on advancements in the more traditional areas of computer science such as machine architecture, algorithm design, data structures, and software engineering,
the discipline of graphics and animation has seen significant progress and has now blossomed into an exciting, dynamic subject. Moreover, the field exemplifies how various components of computer science combine with other disciplines such as physics, art, and photography to produce striking results.
Artificial Intelligence we learn that in order to develop more useful machines computer science has turned to the study of human intelligence for leadership. The hope is that by understanding how our own minds reason and perceive, researchers will be able to design algorithms that mimic these
processes and thus transfer these capabilities to machines. The result is the area of computer science known as artificial intelligence, which leans heavily on research in such areas as psychology, biology, and linguistics.
We close our study with Theory of Computation by investigating the theoretical foundations of computer science—a subject that allows us to understand the limitations of algorithms (and thus machines). Here we identify some problems that cannot be solved algorithmically (and therefore lie beyond the capabilities of machines) as well as learn that the solutions to many other problems require such enormous time or space that they are also unsolvable from a practical perspective. Thus, it is through this study that we are able to grasp the scope and limitations of algorithmic systems.
In each chapter our goal is to explore to a depth that leads to a true understanding of the subject. We want to develop a working knowledge of computer science—a knowledge that will allow you to understand the technical society in which you live and to provide a foundation from which you can learn on your own as science and technology advance.