<p><strong>Computer science</strong>, or <strong>computing science</strong>, is the study of the theoretical foundations of information and computation and their implementation and application in computer systems.<sup class="reference" id="_ref-0">[1]</sup><sup class="reference" id="_ref-1">[2]</sup><sup class="reference" id="_ref-2">[3]</sup> Computer science has many sub-fields; some emphasize the computation of specific results (such as computer graphics), while others relate to properties of computational problems (such as computational complexity theory). Still others focus on the challenges in implementing computations. For example, programming language theory studies approaches to describing computations, while computer programming applies specific programming languages to solve specific computational problems. A further subfield, human-computer interaction, focuses on the challenges in making computers and computations useful, usable and universally accessible to people.</p>

<h2><span class="mw-headline">History</span></h2>

<p>The history of computer science predates the invention of the modern digital computer by many centuries. Machines for calculating fixed numerical tasks, such as the abacus, have existed since antiquity. Wilhelm Schickard built the first mechanical calculator in 1623.<sup class="reference" id="_ref-3">[4]</sup> Charles Babbage designed a difference engine in Victorian times (between 1837 and 1901)<sup class="reference" id="_ref-4">[5]</sup> helped by Ada Lovelace.<sup class="reference" id="_ref-5">[6]</sup> Around 1900 the IBM corporation sold punch-card machines.<sup class="reference" id="_ref-6">[7]</sup> However all of these machines were constrained to perform a single task, or at best, some subset of all possible tasks.</p>

<p>During the 1940s, as newer and more powerful computing machines were developed, the term <em>computer</em> came to refer to the machines rather than their human predecessors. As it became clear that computers could be used for more than just mathematical calculations, the field of computer science broadened to study computation in general. Computer science began to be established as a distinct academic discipline in the 1960s, with the creation of the first computer science departments and degree programs.<sup class="reference" id="_ref-Denning_cs_discipline_0">[8]</sup> Since practical computers became available, many applications of computing have become distinct areas of study in their own right.</p>

<h2><span class="mw-headline">Major achievements</span></h2>

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<li>Scientific computing enabled advanced study of the mind and mapping the human genome was possible with Human Genome Project.<sup class="reference" id="_ref-bgu_1">[12]</sup> Distributed computing projects like Folding@home explore protein folding. </li>

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<h2><span class="mw-headline">Relationship with other fields</span></h2>

<p>Despite its name, much of computer science does not involve the study of computers themselves. Because of this several alternative names have been proposed. Danish scientist Peter Naur suggested the term datalogy, to reflect the fact that the scientific discipline revolves around data and data treatment, while not necessarily involving computers. The first scientific institution applying the datalogy term was DIKU, the Department of Datalogy at the University of Copenhagen, founded in 1969, with Peter Naur being the first professor in datalogy. The term is used mainly in the Scandinavian countries. Also, in the early days of computing, a number of terms for the practitioners of the field of computing were suggested in the <em>Communications of the ACM</em>&mdash;<em>turingineer</em>, <em>turologist</em>, <em>flow-charts-man</em>, <em>applied meta-mathematician</em>, and <em>applied epistemologist</em>.<sup class="reference" id="_ref-9">[13]</sup> Three months later in the same journal, <em>comptologist</em> was suggested, followed next year by <em>hypologist</em>.<sup class="reference" id="_ref-10">[14]</sup> Recently the term <em>computics</em> has been suggested.<sup class="reference" id="_ref-11">[15]</sup></p>

<p>In fact, the renowned computer scientist Edsger Dijkstra is often quoted as saying, <em>&quot;Computer science is no more about computers than astronomy is about telescopes.&quot;</em> The design and deployment of computers and computer systems is generally considered the province of disciplines other than computer science. For example, the study of computer hardware is usually considered part of computer engineering, while the study of commercial computer systems and their deployment is often called information technology or information systems. Computer science is sometimes criticized as being insufficiently scientific, a view espoused in the statement <em>&quot;Science is to computer science as hydrodynamics is to plumbing&quot;</em> credited to Stan Kelly-Bootle<sup class="reference" id="_ref-12">[16]</sup> and others. However, there has been much cross-fertilization of ideas between the various computer-related disciplines. Computer science research has also often crossed into other disciplines, such as artificial intelligence, cognitive science, physics (see quantum computing), and linguistics.</p>

<p>Computer science is considered by some to have a much closer relationship with mathematics than many scientific disciplines.<sup class="reference" id="_ref-Denning_cs_discipline_1">[8]</sup> Early computer science was strongly influenced by the work of mathematicians such as Kurt G&ouml;del and Alan Turing, 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.</p>

<p>The relationship between computer science and software engineering is a contentious issue, which is further muddied by disputes over what the term &quot;software engineering&quot; means, and how computer science is defined. David Parnas, taking a cue from the relationship between other engineering and science disciplines, has claimed that the principal focus of computer science is studying the properties of computation in general, while the principal focus of software engineering is the design of specific computations to achieve practical goals, making the two separate but complementary disciplines.<sup class="reference" id="_ref-13">[17]</sup></p>

<h2><span class="mw-headline">Fields of computer science</span></h2>

<p>Computer science searches for concepts and formal proofs to explain and describe computational systems of interest. As with all sciences, these theories can then be utilised to synthesize practical engineering applications, which in turn may suggest new systems to be studied and analysed. While the ACM Computing Classification System can be used to split computer science up into different topics of fields a more descriptive break down follows:</p>

<p><a id="Theory_of_computation" name="Theory_of_computation"></a></p>

<h3><span class="mw-headline">Theory of computation</span></h3>

<p><a id="Algorithms_and_data_structures" name="Algorithms_and_data_structures"></a></p>

<h3><span class="mw-headline">Algorithms and data structures</span></h3>

<dl><dt>Analysis of algorithms </dt><dd>Time and space complexity of algorithms. </dd><dt>Algorithms </dt><dd>Formal logical processes used for computation, and the efficiency of these processes. </dd><dt>Data structures </dt><dd>The organization of and rules for the manipulation of data. </dd></dl>

<h3><span class="mw-headline">Programming languages and compilers</span></h3>

<dl><dt>Compilers </dt><dd>Ways of translating computer programs, usually from higher level languages to lower level ones. </dd><dt>Interpreters </dt><dd>A program that takes in as input a computer program and executes it. </dd><dt>Programming languages </dt><dd>Formal language paradigms for expressing algorithms, and the properties of these languages (e.g. what problems they are suited to solve). </dd></dl>

<h3><span class="mw-headline">Concurrent, parallel, and distributed systems</span></h3>

<dl><dt>Concurrency </dt><dd>The theory and practice of simultaneous computation; data safety in any multitasking or multithreaded environment. </dd><dt>Distributed computing </dt><dd>Computing using multiple computing devices over a network to accomplish a common objective or task and thereby reducing the latency involved in single processor contributions for any task. </dd><dt>Parallel computing </dt><dd>Computing using multiple concurrent threads of execution. </dd></dl>

<h3><span class="mw-headline">Software engineering</span></h3>

<dl><dt>Algorithm design </dt><dd>Using ideas from algorithm theory to creatively design solutions to real tasks </dd><dt>Computer programming </dt><dd>The practice of using a programming language to implement algorithms </dd><dt>Formal methods </dt><dd>Mathematical approaches for describing and reasoning about software designs. </dd><dt>Reverse engineering </dt><dd>The application of the scientific method to the understanding of arbitrary existing software </dd><dt>Software development </dt><dd>The principles and practice of designing, developing, and testing programs, as well as proper engineering practices. </dd></dl>