Computer science

Computer science is the study of how computers work and how we can use them. It includes many different areas, both ideas and practical uses. Some areas look at ideas like algorithms and how computers can process information. Other areas involve making hardware and software that we use every day.

Important parts of computer science include algorithms and ways to organize information. These help solve problems faster. Other areas such as cryptography and computer security focus on keeping information safe. Computer graphics helps create pictures and animations we see in movies and games. Artificial intelligence and machine learning aim to make computers learn and think.

The main goal of computer science is to find out what tasks computers can do automatically. It is a big field that affects many parts of our lives, from how we talk to each other to how we have fun. The Turing Award is a big award for people who do great work in this field.

History

Main article: History of computer science

Gottfried Wilhelm Leibniz (1646–1716) developed logic in a binary number system and has been called the "founder of computer science".

The story of computer science starts long before modern computers were invented. Simple tools like the abacus have been used for thousands of years to help with math. Early thinkers also made steps, called algorithms, to solve problems.

Over time, people built machines to do calculations faster. In 1623, Wilhelm Schickard made a mechanical calculator, and later, Gottfried Leibniz created a machine that used binary numbers. In the 1800s, Charles Babbage designed plans for machines that could be programmed, which helped start modern computers. During the 1940s, new machines like the ENIAC showed that computers could do more than just math, and computer science became its own field of study.

Etymology and scope

The term "computer science" was first used in 1959 in Communications of the ACM. It is a field that studies computation and information. It is related to many other subjects. While it often uses computers, it also includes theories and ideas that do not always need a computer. Some universities call this field "computing science" to show this difference. Other names, like "datalogy" and "data science," have been suggested for studying data and its handling.

Computer science connects with many other areas, such as mathematics, physics, and linguistics. It often works with these fields, sharing ideas and methods. Some people think computer science is very much like mathematics because of its logical and theoretical nature. The field also links to engineering, especially in designing and building computer systems. These connections help computer science grow and solve many different kinds of problems.

Main article: Informatics § Etymology

Philosophy

Main article: Philosophy of computer science

Computer science is a fascinating field, and people often ask if it is more like science, mathematics, or engineering. Some experts believe it is an empirical science because we can test and see how computers and programs behave in real life. Others think it is more like engineering because it involves creating reliable systems, similar to building bridges or airplanes.

A few consider computer science part of mathematics because computer programs can be studied using logical reasoning and formal methods. The field includes many areas, from building and testing computer systems to developing ideas about how computation works.

Fields

Further information: Outline of computer science

Computer science is a big field that studies how we can use computers to solve problems. It looks at both ideas and real ways to use computers. People who work in this area are called computer scientists.

This field covers many topics. It includes how computers understand problems, how to design computer parts, and how to make computers work together. Some important areas are learning what computers can and cannot do, making ways to store and find information fast, and creating computer programs that are safe and easy to use. Computer science also looks at artificial intelligence, which tries to make computers think and learn like humans.

		M = { X : X ∉ X } {\displaystyle M=\{X:X\not \in X\}}
Automata theory	Formal languages	Computability theory	Computational complexity theory

Models of computation	Quantum computing theory	Logic circuit theory	Cellular automata


Coding theory	Channel capacity	Algorithmic information theory	Signal detection theory	Kolmogorov complexity

O(n²)
Analysis of algorithms	Algorithm design	Data structures	Combinatorial optimization	Computational geometry	Randomized algorithms

	Γ ⊢ x : Int {\displaystyle \Gamma \vdash x:{\text{Int}}}
Formal semantics	Type theory	Compiler design	Programming languages	Formal verification	Automated theorem proving


2D computer graphics	Computer animation	Rendering	Mixed reality	Virtual reality	Solid modeling


FFT algorithms	Image processing	Speech recognition	Data compression	Medical image computing	Speech synthesis


Numerical analysis	Computational physics	Computational chemistry	Bioinformatics	Neuroinformatics	Psychoinformatics	Medical informatics	Computational engineering	Computational musicology


Affective computing	Brain–computer interface	Human-centered design	Physical computing	Social computing


Computational learning theory	Computer vision	Neural networks	Planning and scheduling

Natural language processing	Computational game theory	Evolutionary computation	Autonomic computing

Representation and reasoning	Pattern recognition	Robotics	Swarm intelligence


Processing unit	Microarchitecture	Multiprocessing	Processor design

Ubiquitous computing	Systems architecture	Operating systems	Input/output

Embedded system	Real-time computing	Dependability	Interpreter

Discoveries

The philosopher of computing Bill Rapaport talked about three big ideas in computer science.

First, smart people like Gottfried Wilhelm Leibniz, George Boole, Alan Turing, Claude Shannon, and Samuel Morse found that all information can be shown using just two symbols, like on and off, or 0 and 1.

Second, Alan Turing showed that computers need only five basic actions to do any job: moving left or right, reading a symbol, and printing a 0 or 1. Finally, Corrado Böhm and Giuseppe Jacopini discovered that only three ways of mixing these actions—doing steps one after another, making choices, and repeating actions—are needed for any computer work.

Programming paradigms

Main article: Programming paradigm

Programming languages have different ways to get tasks done, called programming paradigms. One common way is functional programming. This acts like math functions and avoids changing data. Another is imperative programming, where you give the computer step-by-step commands. Object-oriented programming focuses on "objects" that hold data and actions, working together like team members. There's also service-oriented programming, which builds programs from small, useful services. Many languages can use several of these styles, so choosing one is often about personal preference.

Research

Conferences are important events in computer science. Researchers from many places meet to share their newest work and meet each other. In this field, conference papers are often more important than journal articles. This is because conferences let people share new ideas quickly, which is very useful in a fast-changing area like computer science.

Main article: List of computer science conferences

Main articles: Category:Computer science journals