Computer science
In 1623, Wilhelm Schickard constructed the first working mechanical calculator. This machine marked a turning point in human attempts to automate arithmetic tasks that had previously required hours of manual calculation. Gottfried Leibniz followed this innovation by demonstrating his Stepped Reckoner in 1673. He documented the binary number system within his designs, earning him recognition as an early computer scientist and information theorist. Charles Babbage began designing his Difference Engine in 1822. His later Analytical Engine project introduced punched cards derived from the Jacquard loom. These cards allowed for unlimited program storage without manual setting errors. Ada Lovelace wrote an algorithm for computing Bernoulli numbers during her translation work on a French article about the Analytical Engine in 1843. Her notes contained what is considered the first published algorithm tailored specifically for implementation on a computer. Herman Hollerith invented a tabulator around 1885 that used punched cards to process statistical data. His company eventually became part of IBM. Percy Ludgate published one of only two known designs for mechanical analytical engines in 1909. Leonardo Torres Quevedo presented his Electromechanical Arithmometer prototype in Paris in 1920. Howard Aiken convinced IBM to develop the ASCC/Harvard Mark I programmable calculator in 1937. The machine was completed and hailed as "Babbage's dream come true" when finished. The Association for Computing Machinery formed in 1947. Columbia University offered one of the first academic-credit courses in computer science in 1946. The world's first computer science degree program, the Cambridge Diploma in Computer Science, began at the University of Cambridge Computer Laboratory in 1953.
Louis Fein argued for the creation of a Graduate School in Computer Sciences in an article published in Communications of the ACM in 1959. He justified the name by comparing it to management science, noting its applied and interdisciplinary nature. Purdue University established the first computer science department in the United States in 1962. Peter Naur suggested the term datalogy to reflect that the discipline revolves around data rather than necessarily involving computers. The Department of Datalogy at the University of Copenhagen became the first scientific institution to use this term in 1969. Naur served as the first professor in datalogy there. Danish scientist Peter Naur also proposed data science as an alternative term, which now describes a multi-disciplinary field including statistics and databases. A folkloric quotation often attributed to Edsger Dijkstra states that "computer science is no more about computers than astronomy is about telescopes." This saying highlights how much of the field does not involve studying physical machines themselves. Certain departments prefer computing science to emphasize this distinction. In Europe, terms derived from expressions like "automatic information" or "information and mathematics" are common. The School of Informatics at the University of Edinburgh adopted similar terminology used in France, Germany, Italy, Spain, Portugal, Slavic languages, and Hungarian. In the U.S., informatics links with applied computing within another domain context.
Peter Denning identified the fundamental question underlying computer science as "What can be automated?" Computability theory examines which computational problems are solvable on various theoretical models of computation. Computational complexity theory studies the time and space costs associated with solving multiple computational problems. The famous P = NP problem remains one of the Millennium Prize Problems and stands as an open issue in the theory of computation. Claude Shannon developed information theory to find fundamental limits on signal processing operations such as compressing data. He also established reliable methods for storing and communicating data through his work. Coding theory studies properties of codes used for converting information from one form to another. These codes serve purposes including data compression, cryptography, error detection, correction, and network coding. Automata theory explores formal languages and models of computation alongside quantum computing theory and logic circuit theory. Cellular automata provide additional frameworks for understanding computational processes. Algorithmic information theory and Kolmogorov complexity offer further insights into algorithmic randomness and structure. Signal detection theory complements these approaches by analyzing uncertainty in econometric applications.
Lyle R. Johnson and Frederick P. Brooks Jr. coined the term architecture within IBM's main research center during 1959. They belonged to the Machine Organization department at that facility. Computer engineers study computational logic and design hardware ranging from individual processor components to supercomputers. Embedded systems represent another critical area where computers operate independently within larger devices. Concurrent execution allows several computations to run simultaneously while potentially interacting with each other. Petri nets and process calculi serve as mathematical models for general concurrent computation. The parallel random access machine model provides yet another framework for studying concurrency. Distributed systems connect multiple computers via networks while maintaining private memory on each node. Information exchange between nodes enables achievement of common goals across the entire system. Computer networks address performance, resilience, security, scalability, and cost-effectiveness alongside service variety. Computer security protects information from unauthorized access or modification while maintaining accessibility for intended users. Modern cryptography includes symmetric encryption, asymmetric encryption, digital signatures, cryptographic hash functions, key-agreement protocols, blockchain technology, zero-knowledge proofs, and garbled circuits. Database management systems organize, store, create, maintain, and search large amounts of data through query languages. Data mining discovers patterns hidden within massive datasets.
Alan Turing posed the question "Can computers think?" in the late 1940s, a question that remains effectively unanswered today. The Dartmouth Conference held in 1956 marked the starting point for artificial intelligence research. This field draws expertise from applied mathematics, symbolic logic, semiotics, electrical engineering, philosophy of mind, neurophysiology, and social intelligence. AI aims to synthesize goal-oriented processes such as problem-solving, decision-making, environmental adaptation, learning, and communication found in humans and animals. The Turing test continues to assess computer output on scales comparable to human intelligence. Automation of evaluative and predictive tasks has become increasingly successful substitutes for human monitoring in complex real-world domains involving large datasets. Computer vision understands and processes image and video data within this broader context. Natural language processing handles textual and linguistic data understanding and generation. Neural networks form another core component enabling pattern recognition capabilities. Planning and scheduling algorithms support decision-making frameworks used across industries. Computational game theory explores strategic interactions between intelligent agents. Evolutionary computation mimics biological evolution to solve optimization problems. Swarm intelligence studies collective behaviors emerging from simple individual actions. Robotics represents both popular perception and practical application areas where embedded components require computational understanding.
Functional programming treats computation as evaluation of mathematical functions while avoiding mutable state or data changes. It operates through expressions or declarations rather than imperative statements. Imperative programming uses commands that change a program's state much like natural language imperatives express orders. An imperative program describes how a computer should operate step-by-step. Object-oriented programming constructs programs using objects containing fields known as attributes and procedures called methods. These objects interact with one another allowing access and modification of associated data fields. Service-oriented programming utilizes services as units of work designed for integrated business applications and mission-critical software systems. Many languages support multiple paradigms making distinctions more stylistic than technical barriers. Formal methods apply mathematically based techniques specifying, developing, verifying software and hardware systems. They help avoid errors and provide testing frameworks especially important in safety-critical environments. High costs limit formal method usage primarily to high-integrity life-critical systems requiring utmost security or reliability. Logic calculi, formal languages, automata theory, and program semantics form theoretical underpinnings supporting these approaches. Type systems and algebraic data types further enhance specification capabilities across diverse problem domains.
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Common questions
When did Wilhelm Schickard construct the first working mechanical calculator?
Wilhelm Schickard constructed the first working mechanical calculator in 1623. This machine marked a turning point in human attempts to automate arithmetic tasks that had previously required hours of manual calculation.
Who wrote the first published algorithm tailored specifically for implementation on a computer?
Ada Lovelace wrote an algorithm for computing Bernoulli numbers during her translation work on a French article about the Analytical Engine in 1843. Her notes contained what is considered the first published algorithm tailored specifically for implementation on a computer.
Which university offered one of the first academic-credit courses in computer science and when?
Columbia University offered one of the first academic-credit courses in computer science in 1946. The world's first computer science degree program, the Cambridge Diploma in Computer Science, began at the University of Cambridge Computer Laboratory in 1953.
What fundamental question does Peter Denning identify as underlying computer science?
Peter Denning identified the fundamental question underlying computer science as What can be automated? Computability theory examines which computational problems are solvable on various theoretical models of computation.
When did the Dartmouth Conference mark the starting point for artificial intelligence research?
The Dartmouth Conference held in 1956 marked the starting point for artificial intelligence research. This field draws expertise from applied mathematics, symbolic logic, semiotics, electrical engineering, philosophy of mind, neurophysiology, and social intelligence.