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An Evolution Of Computer Science

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Computer Science is many things: engineering, math, science, art. The field is diverse; from coding robots who can map the bottoms of oceans to animating digital characters for Disney’s next film, computing has immersed itself in virtually every area and concentration of career. The idea of computing itself exists in both the physical and theoretical world, requiring abstract and concrete thinking to fully understand it. But what exactly makes computer science what it is? What specifically makes an profession that has been around for less than a century one of the most integral parts of modern society? The discipline’s definitions, though varied, exemplify how computer science has evolved from an obscure discovery in the 1940s to a now prominent fixture of contemporary life and sciences.

At Boston University’s Department of Computer Science, the discipline is defined as the organized study of the structure, interpretation, and computerization of algorithms that determine the attainment, storage, communication of, and access to information [Streubel 2003]. In this definition the purpose of computer science is summed up in the question: “what computational processes can be efficiently automated and implemented” [Streubel 2003]? However, in the document, computing is defined as more than just the use of computers to study algorithms; computer science is how we use the tools available to solve problems and find solutions. In short, computer science can be defined as a unique way to problem solve. The discipline allows scientists and engineers to tackle challenges that advances numerous other fields of study, such as chemistry, astrophysics, biology and many more, even leading to a new classification of scientist – a computational scientist – who uses computers to make contributions to their work [Streubel 2003]. Not only is computer science a way to study structures and information, but also a system of solving puzzles that benefits numerous disciplines as well as its own by using computers as its foundation.

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While the Boston University classifies computer science as more of an abstract method of puzzle-solving, Peter Denning, the director of the Cebrowski Institute for information and modernization at the Naval Postgraduate School, argues that computer science is just that; an exact science. He argues the discipline is the study of naturally-occurring information processes present in the physical realm [Denning 2005]. He also states computer science works with an established, organized body of knowledge used for prediction and authentication in the field of computing, similar to how accepted fields of science, such as mathematics or biology, operate [Denning 2005]. People are skeptical about computer science as a field of pure science due to the fact computing is commonly seen as the study of only synthetic objects. However, Denning declares that computer science surveys both organic and synthetic information processes [Denning 2005]. As stated by Boston University, computer science aids in discoveries of other disciplines, such as physicists who illustrate particle behavior with quantum information processes and substantiate their findings with computer simulation experiments [Denning 2005]. Computing is obviously much more than just software computations; Denning believes it is the system of creating successful hypotheses, involving information processes, which become models to explain and predict phenomena in the world [Denning 2005]. He argues computer science fits the “scientific paradigm” of forming theories and then testing said theories, which is corroborated through the fact computers, used in studies such as cognition research, are tools to test hypotheses, such as intelligent behavior being the result of information processes in brains and nervous systems [Denning 2005]. Due to the fact computer science fits the bill in studying both natural and synthetic objects (technology), while also corroborating with the scientific method and contributing to scientific discoveries, the definition of computers science as a true, pure science is definitely viable.

For computer science educators, the field is more than just algorithms or science. Avi Cohen of the Ministry of Education in Israel and Bruria Haberman, a member of the computer science department of The Weizmann Institute of Science, stress that computer science should be acknowledged as a “scientific paradigm” of “a language of technology” [Cohen and Haberman 2007]. As a language, computer science defines the architecture, processes, connections, and communications of technology, not just the mathematical or theoretical processes that encompass the surface of the field [Cohen and Haberman 2007].

Language itself is hard to define, given the evolving nature of modern day vocabularies. However, considering computer science often involves extensive use of symbols and words specifically targeted at conveying concepts, hypotheses, and reasonings, the thought of the discipline as a language is not much of a stretch. In further support of this idea, Cohen and Haberman confront computer science’s correlation with mathematics, which is also considered to be a language – “the language of science” [Cohen and Haberman 2007]. If mathematics, with its many terms, definitions, and theories, can be considered a language, why can’t computer science? Computer science also has many characteristics of a language, such as its own breadth of terminology, in which some do not exist in any other field, or are used in a unique way to computer science [Cohen and Haberman 2007]. As for its definition as a “language of technology,” computer science reinforces both abstract and concrete representations of technological concepts heavily ingrained into common patterns of thinking in other areas; the discipline simplifies the “doing and understanding” of technology, and thus defines what a language should accomplish [Cohen and Haberman 2007].

Evidently, computer science as a field is seen in varying ways by different people. At Boston University, computer science is a unique way to problem solve. Peter Denning claims the field is a true science. For Avi Cohen and Bruria Haberman, computer science is the language of technology. These definitions are varied, but also interconnected. For Peter Denning and Cohen and Haberman, computer science corroborates with the “scientific paradigm,” but for distinctive rationales: one as the embodiment of the use of the scientific method, the other as the embodiment of language. Neither of these views are wrong or even mutually exclusive; one could argue that computer science as a language is just a way to communicate the scientific method in a way that computers understand. To elaborate, scientists often construct systems which implement hypothesized information processes through computers and then correlate them with the real thing [Denning 2005]. This illustrates how computers in these studies are tools to test hypotheses, an essential part to the scientific method. In addition, language could even be seen as the personification of problem solving; without the articulation of issues, and the communication needed to solve them, attempting to settle issues would be inefficient, if not utterly impossible. This is especially true in computer science, where the core of the discipline is to relay and structure information processes, processes that require strict terminology in order to be understood by human or machine [Streubel 2003]. If anything, computer science should be considered, in addition to mathematics, a “language” of science.

So many other scientific fields rely on the syntax and problem-solving of computing that it would be impossible to solve many natural mysteries without computer science. The previous example of physicists who illustrate particle behavior with quantum information processes is evidence of this [Denning 2005]. Without the common language of computing, in which scientists define and prove their theories with computational experiments, finding solutions to enigmas would take much longer to discover, if at all. In short, computer science is arguably most accurately defined as a language, more specifically, a language of science that describes technological problem solving to benefit nearly all other fields. In an ever-changing technological landscape, computer science as a language accurately explains the evolution of the field; from its humble beginnings in the 1940s into a procedure of communication for science and technology.

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