IV.

Major Branches of Computer Science

Computer science can be divided into four main fields: software development, computer architecture (hardware), human-computer interfacing (the design of the most efficient ways for humans to use computers), and artificial intelligence (the attempt to make computers behave intelligently). Software development is concerned with creating computer programs that perform efficiently. Computer architecture is concerned with developing optimal hardware for specific computational needs. The areas of artificial intelligence (AI) and human-computer interfacing often involve the development of both software and hardware to solve specific problems.

A.

Software Development

In developing computer software, computer scientists and engineers study various areas and techniques of software design, such as the best types of programming languages and algorithms (see below) to use in specific programs, how to efficiently store and retrieve information, and the computational limits of certain software-computer combinations. Software designers must consider many factors when developing a program. Often, program performance in one area must be sacrificed for the sake of the general performance of the software. For instance, since computers have only a limited amount of memory, software designers must limit the number of features they include in a program so that it will not require more memory than the system it is designed for can supply.

Software engineering is an area of software development in which computer scientists and engineers study methods and tools that facilitate the efficient development of correct, reliable, and robust computer programs. Research in this branch of computer science considers all the phases of the software life cycle, which begins with a formal problem specification, and progresses to the design of a solution, its implementation as a program, testing of the program, and program maintenance. Software engineers develop software tools and collections of tools called programming environments to improve the development process. For example, tools can help to manage the many components of a large program that is being written by a team of programmers.

Algorithms and data structures are the building blocks of computer programs. An algorithm is a precise step-by-step procedure for solving a problem within a finite time and using a finite amount of memory. Common algorithms include searching a collection of data, sorting data, and numerical operations such as matrix multiplication. Data structures are patterns for organizing information, and often represent relationships between data values. Some common data structures are called lists, arrays, records, stacks, queues, and trees.

Computer scientists continue to develop new algorithms and data structures to solve new problems and improve the efficiency of existing programs. One area of theoretical research is called algorithmic complexity. Computer scientists in this field seek to develop techniques for determining the inherent efficiency of algorithms with respect to one another. Another area of theoretical research called computability theory seeks to identify the inherent limits of computation.

Software engineers use programming languages to communicate algorithms to a computer. Natural languages such as English are ambiguous—meaning that their grammatical structure and vocabulary can be interpreted in multiple ways—so they are not suited for programming. Instead, simple and unambiguous artificial languages are used. Computer scientists study ways of making programming languages more expressive, thereby simplifying programming and reducing errors. A program written in a programming language must be translated into machine language (the actual instructions that the computer follows). Computer scientists also develop better translation algorithms that produce more efficient machine language programs.

Databases and information retrieval are related fields of research. A database is an organized collection of information stored in a computer, such as a company’s customer account data. Computer scientists attempt to make it easier for users to access databases, prevent access by unauthorized users, and improve access speed. They are also interested in developing techniques to compress the data, so that more can be stored in the same amount of memory. Databases are sometimes distributed over multiple computers that update the data simultaneously, which can lead to inconsistency in the stored information. To address this problem, computer scientists also study ways of preventing inconsistency without reducing access speed.

Information retrieval is concerned with locating data in collections that are not clearly organized, such as a file of newspaper articles. Computer scientists develop algorithms for creating indexes of the data. Once the information is indexed, techniques developed for databases can be used to organize it. Data mining is a closely related field in which a large body of information is analyzed to identify patterns. For example, mining the sales records from a grocery store could identify shopping patterns to help guide the store in stocking its shelves more effectively. (see Information Storage and Retrieval.)

Operating systems are programs that control the overall functioning of a computer. They provide the user interface, place programs into the computer’s memory and cause it to execute them, control the computer’s input and output devices, manage the computer’s resources such as its disk space, protect the computer from unauthorized use, and keep stored data secure. Computer scientists are interested in making operating systems easier to use, more secure, and more efficient by developing new user interface designs, designing new mechanisms that allow data to be shared while preventing access to sensitive data, and developing algorithms that make more effective use of the computer’s time and memory.

The study of numerical computation involves the development of algorithms for calculations, often on large sets of data or with high precision. Because many of these computations may take days or months to execute, computer scientists are interested in making the calculations as efficient as possible. They also explore ways to increase the numerical precision of computations, which can have such effects as improving the accuracy of a weather forecast. The goals of improving efficiency and precision often conflict, with greater efficiency being obtained at the cost of precision and vice versa.

Symbolic computation involves programs that manipulate nonnumeric symbols, such as characters, words, drawings, algebraic expressions, encrypted data (data coded to prevent unauthorized access), and the parts of data structures that represent relationships between values (see Encryption). One unifying property of symbolic programs is that they often lack the regular patterns of processing found in many numerical computations. Such irregularities present computer scientists with special challenges in creating theoretical models of a program’s efficiency, in translating it into an efficient machine language program, and in specifying and testing its correct behavior.

B.

Computer Architecture

Computer architecture is the design and analysis of new computer systems. Computer architects study ways of improving computers by increasing their speed, storage capacity, and reliability, and by reducing their cost and power consumption. Computer architects develop both software and hardware models to analyze the performance of existing and proposed computer designs, then use this analysis to guide development of new computers. They are often involved with the engineering of a new computer because the accuracy of their models depends on the design of the computer’s circuitry. Many computer architects are interested in developing computers that are specialized for particular applications such as image processing, signal processing, or the control of mechanical systems. The optimization of computer architecture to specific tasks often yields higher performance, lower cost, or both.

C.

Artificial Intelligence

Artificial intelligence (AI) research seeks to enable computers and machines to mimic human intelligence and sensory processing ability, and models human behavior with computers to improve our understanding of intelligence. The many branches of AI research include machine learning, inference, cognition, knowledge representation, problem solving, case-based reasoning, natural language understanding, speech recognition, computer vision, and artificial neural networks.

A key technique developed in the study of artificial intelligence is to specify a problem as a set of states, some of which are solutions, and then search for solution states. For example, in chess, each move creates a new state. If a computer searched the states resulting from all possible sequences of moves, it could identify those that win the game. However, the number of states associated with many problems (such as the possible number of moves needed to win a chess game) is so vast that exhaustively searching them is impractical. The search process can be improved through the use of heuristics—rules that are specific to a given problem and can therefore help guide the search. For example, a chess heuristic might indicate that when a move results in checkmate, there is no point in examining alternate moves.

D.

Robotics

Another area of computer science that has found wide practical use is robotics—the design and development of computer controlled mechanical devices. Robots range in complexity from toys to automated factory assembly lines, and relieve humans from tedious, repetitive, or dangerous tasks. Robots are also employed where requirements of speed, precision, consistency, or cleanliness exceed what humans can accomplish. Roboticists—scientists involved in the field of robotics—study the many aspects of controlling robots. These aspects include modeling the robot’s physical properties, modeling its environment, planning its actions, directing its mechanisms efficiently, using sensors to provide feedback to the controlling program, and ensuring the safety of its behavior. They also study ways of simplifying the creation of control programs. One area of research seeks to provide robots with more of the dexterity and adaptability of humans, and is closely associated with AI.

E.

Human-Computer Interfacing

Human-computer interfaces provide the means for people to use computers. An example of a human-computer interface is the keyboard, which lets humans enter commands into a computer and enter text into a specific application. The diversity of research into human-computer interfacing corresponds to the diversity of computer users and applications. However, a unifying theme is the development of better interfaces and experimental evaluation of their effectiveness. Examples include improving computer access for people with disabilities, simplifying program use, developing three-dimensional input and output devices for virtual reality, improving handwriting and speech recognition, and developing heads-up displays for aircraft instruments in which critical information such as speed, altitude, and heading are displayed on a screen in front of the pilot’s window. One area of research, called visualization, is concerned with graphically presenting large amounts of data so that people can comprehend its key properties.