Computer science
Machines for calculating fixed numerical tasks such as the abacus have existed since antiquity, aiding in computations such as multiplication and division.
[18] Leibniz may be considered the first computer scientist and information theorist, because of various reasons, including the fact that he documented the binary number system.
[20] "A crucial step was the adoption of a punched card system derived from the Jacquard loom"[20] making it infinitely programmable.
[21] Around 1885, Herman Hollerith invented the tabulator, which used punched cards to process statistical information; eventually his company became part of IBM.
Following Babbage, although unaware of his earlier work, Percy Ludgate in 1909 published[22] the 2nd of the only two designs for mechanical analytical engines in history.
In 1914, the Spanish engineer Leonardo Torres Quevedo published his Essays on Automatics,[23] and designed, inspired by Babbage, a theoretical electromechanical calculating machine which was to be controlled by a read-only program.
[27] In 1937, one hundred years after Babbage's impossible dream, Howard Aiken convinced IBM, which was making all kinds of punched card equipment and was also in the calculator business[28] to develop his giant programmable calculator, the ASCC/Harvard Mark I, based on Babbage's Analytical Engine, which itself used cards and a central computing unit.
In 1945, IBM founded the Watson Scientific Computing Laboratory at Columbia University in New York City.
The renovated fraternity house on Manhattan's West Side was IBM's first laboratory devoted to pure science.
[38] Louis justifies the name by arguing that, like management science, the subject is applied and interdisciplinary in nature, while having the characteristics typical of an academic discipline.
[37] His efforts, and those of others such as numerical analyst George Forsythe, were rewarded: universities went on to create such departments, starting with Purdue in 1962.
[40] Certain departments of major universities prefer the term computing science, to emphasize precisely that difference.
[44] In Europe, terms derived from contracted translations of the expression "automatic information" (e.g. "informazione automatica" in Italian) or "information and mathematics" are often used, e.g. informatique (French), Informatik (German), informatica (Italian, Dutch), informática (Spanish, Portuguese), informatika (Slavic languages and Hungarian) or pliroforiki (πληροφορική, which means informatics) in Greek.
[33] Early computer science was strongly influenced by the work of mathematicians such as Kurt Gödel, Alan Turing, John von Neumann, Rózsa Péter and Alonzo Church and there continues to be a useful interchange of ideas between the two fields in areas such as mathematical logic, category theory, domain theory, and algebra.
[33] Amnon H. Eden described them as the "rationalist paradigm" (which treats computer science as a branch of mathematics, which is prevalent in theoretical computer science, and mainly employs deductive reasoning), the "technocratic paradigm" (which might be found in engineering approaches, most prominently in software engineering), and the "scientific paradigm" (which approaches computer-related artifacts from the empirical perspective of natural sciences,[53] identifiable in some branches of artificial intelligence).
It falls within the discipline of computer science, both depending on and affecting mathematics, software engineering, and linguistics.
Formal methods are a particular kind of mathematically based technique for the specification, development and verification of software and hardware systems.
However, the high cost of using formal methods means that they are usually only used in the development of high-integrity and life-critical systems, where safety or security is of utmost importance.
Formal methods are best described as the application of a fairly broad variety of theoretical computer science fundamentals, in particular logic calculi, formal languages, automata theory, and program semantics, but also type systems and algebraic data types to problems in software and hardware specification and verification.
Computer graphics is the study of digital visual contents and involves the synthesis and manipulation of image data.
HCI has several subfields that focus on the relationship between emotions, social behavior and brain activity with computers.
Artificial intelligence (AI) aims to or is required to synthesize goal-orientated processes such as problem-solving, decision-making, environmental adaptation, learning, and communication found in humans and animals.
", and the question remains effectively unanswered, although the Turing test is still used to assess computer output on the scale of human intelligence.
But the automation of evaluative and predictive tasks has been increasingly successful as a substitute for human monitoring and intervention in domains of computer application involving complex real-world data.
It focuses largely on the way by which the central processing unit performs internally and accesses addresses in memory.
The term "architecture" in computer literature can be traced to the work of Lyle R. Johnson and Frederick P. Brooks Jr., members of the Machine Organization department in IBM's main research center in 1959.
Computers within that distributed system have their own private memory, and information can be exchanged to achieve common goals.
[69] Technologies studied in modern cryptography include symmetric and asymmetric encryption, digital signatures, cryptographic hash functions, key-agreement protocols, blockchain, zero-knowledge proofs, and garbled circuits.
Unlike in most other academic fields, in computer science, the prestige of conference papers is greater than that of journal publications.
[77][78] One proposed explanation for this is the quick development of this relatively new field requires rapid review and distribution of results, a task better handled by conferences than by journals.
