Computer Science Essay Example

Around 1885, Herman Hollering invented a tabulator that used punched cards to process statistical data, later becoming part of MM.

In 1937, Howard Keen convinced MM to create SACS/Harvard Mark l based on Babbage's analytical engine—a punched card programmable calculator—fulfilling "Babbage's dream." By the sass decade, as computing machines became more powerful, "computer" referred not only to the machines themselves but also expanded to include more than just mathematical calculations within computer science.

Computer science was officially recognized as an academic discipline during the 1950s and early 1960s.The University of Cambridge Computer Laboratory established the first computer science degree program in 1953, and Purdue University followed suit in the United States in 1962. Initially, there were doubts about computers becoming a field of study, but this perception gradually changed in the late fifties with IBM's contribution. IBM introduced widely utilized computers like the IBM 704 and later the IBM 709. However, these computers were sensitive to errors, making them challenging to work with. Even a single misplaced letter could cause a crash that required a complete restart. Despite these difficulties, computing technology has significantly improved over time in terms of usability and effectiveness.

Nowadays, computer technology is accessible to almost everyone and no longer limited to experts. Computers have become more affordable and user-friendly, reducing the need for professional assistance in everyday use. The Enigma machine used by the German military during World War II was decrypted at Bletchley Park, leading to victory for the Allies. Despite being a young academic discipline, computer science has made significant contributions to both science and society.Computer science is not only a field of study that focuses on electronics but also a

fundamental science in the Information Age. It has played a significant role in driving the Information Revolution, which is considered the third major leap in human technological progress after the Industrial Revolution and Agricultural Revolution. The contributions of computer science include sparking the "digital revolution" that characterizes our current Information Age and identifying computationally unsolvable problems that present challenges.

One important concept introduced by computer science is the idea of a formal language, which allows for precise expression of methodology at different levels of abstraction. For example, during World War II, breaking the Enigma code demonstrated how cryptography impacted Allied victory and showcased its significance. Additionally, scientific computing enables practical evaluation and experimentation through software alone, making complex process analysis feasible.

Advancements in computing have also made advanced studies on the human mind and mapping the human genome possible. Projects like Folding@home utilize distributed computing to explore protein folding, while algorithmic trading leverages artificial intelligence, machine learning, and statistical techniques to enhance financial market efficiency (though it may potentially increase volatility).

Moreover, computer-generated graphics have become prevalent across various forms of entertainment such as television, cinema, advertising, animation, and video games.Digital cameras and video editors are now widely used even in movies that do not explicitly include CGI. Computers enable simulations for various purposes, such as computational fluid dynamics and societal simulations like war games. Furthermore, modern computers allow for design optimization, including the creation of complete aircraft. In electrical and electronic circuit design, SPICE and software for physical realization play a crucial role. Artificial intelligence is increasingly significant with applications that range from robotic vacuum cleaners in homes to video games, drones, anti-missile systems, and squad support

robots on the modern battlefield.

Some computer scientists argue that there are three paradigms in computer science: science, technology, and mathematics; theory, abstraction (modeling), and design. The term "computer science" was first mentioned in a 1959 article in Communications of the ACM. Louis Feint argued for establishing a Graduate School in Computer Sciences by comparing it to the founding of Harvard Business School. He believed computer science to be an applied academic discipline similar to management science. This led universities, starting with Purdue University in 1962, to establish computer science programs.

However, despite its name, a significant portion of computer science does not solely focus on computers. Some universities prefer the term computing science to emphasize this distinction.Another term that has been suggested is daylong, which was proposed by Danish scientist Peter Near. This term reflects the focus on data and its treatment within the scientific field, which may not always involve computers. The Department of Daylong at the University of Copenhagen was established in 1969 as the first institution to adopt this term, primarily used in Scandinavian countries. In the early days, there were several terms proposed for computing practitioners such as turpentine's, trilogies, flow-charts-man, applied meta-mathematician, and applied epistemology. The term computing itself was also suggested. In Europe, contracted translations commonly use "automatic information" or "information and mathematics". As a well-known quote states: "computer science is no more about computers than astronomy is about telescopes." The design and deployment of computers and computer systems are considered separate domains from computer science, falling under fields like computer engineering, information technology, or information systems. There has been significant exchange of ideas between different computer-related disciplines. Computer science

research often intersects with philosophy, cognitive science, linguistics, mathematics, physics statistics and logic.Some consider computer science to have a closer relationship with mathematics compared to other scientific disciplines since they view computing as a mathematical science.Early computer science was influenced by mathematicians like Kurt Godel and Alan Turing.The fields of computer science and mathematics have ongoing exchanges in areas such as mathematical logic, category theory, domain theory, and algebra. The relationship between computer science and software engineering is complex due to disputes over the definition of "software engineering" and how computer science is defined. According to David Parkas, computer science focuses on studying the properties of computation while software engineering is a related but distinct field. Various factors such as academia, politics, and funding can influence the field of computer science. The emphasis on mathematics or engineering within a department plays a significant role in these aspects. Some computer science departments prioritize mathematics with a numerical focus, aiming to align themselves with computational sciences. However, both types of departments strive to bridge the field educationally regardless of their focus. Computer science encompasses various topics including theoretical studies on algorithms and computation limits as well as practical concerns regarding hardware and software implementation of computing systems.The SCAB, consisting of representatives from ACM and IEEE-CSS, recognizes key areas crucial to computer science. These include theory of computation, algorithms and data structures, programming methodology and languages, as well as computer elements and architecture. The SCAB also acknowledges other vital fields like software engineering, artificial intelligence, computer networking and communication, database systems, parallel computation,distributed computation ,computer-human interaction ,computer graphics , operating systems,and numerical- symbolic computation.

Theoretical computer science specifically focuses

on abstract concepts related to computing itself. This area explores different models of computation to determine efficient automation of tasks. Computational complexity theory studies the resources required for solving computational problems in terms of time and space costs associated with various approaches. It combines different areas such as Automata theory, Computability theory, Computational complexity theory,Cryptography, Quantum computing theory,and Information and coding theory.

One famous open problem in this field is the "P=NP?" problem under the Millennium Prize Problems. Claude E.Shannon's work on Information theory and Codingtheory aims at determining limits on signal processing operations like data compression along with reliable storage and communication of data.Coding theory examines codes used for tasks such as data compression, cryptography, error detection and correction, and network coding. The study of codes helps develop efficient and reliable methods for transmitting data. Algorithms and data structures are studied in relation to the analysis of algorithms, computational geometry, and programming language theory. Programming language theory focuses on designing, implementing, analyzing programming languages along with their features classification within computer science that intersects with mathematics, software engineering, and linguistics. Formal methods involve using mathematically based techniques to specify development processes while verifying software and hardware systems. Formal methods in software engineering aim to enhance reliability and stability through mathematical analysis for safety and security purposes but are often limited due to cost constraints to high-integrity and life-critical systems. They encompass theoretical computer science fundamentals such as logic calculi, formal languages, automata theory program semantics type systems algebraic data types applicable to both software and hardware specification verification tasks. Practical industrial implementation relies on tool support.Applied Computer Science, also known as artificial intelligence (AI), involves

using concepts from Computer Science to solve real-world problems. The field of AI originated from cybernetics and the Dartmouth Conference in 1956. It draws upon various disciplines such as applied mathematics, symbolic logic, semiotics, electrical engineering, philosophy of mind, neurophysiology, and social intelligence. Apart from robotic development, AI also has practical applications in software development for computational understanding and modeling across fields like finance, economics, data mining, and the physical sciences.

In the late 1900s, Alan Turing raised the question of whether computers can exhibit thinking. This question remains unanswered but has been evaluated through the "Turing Test," which compares computer output to human intelligence. Automation has successfully replaced human monitoring and intervention in complex computer applications involving evaluative and predictive tasks. These applications include machine learning, computer vision, image processing, pattern recognition,cognitive science,data mining,evolutionary computation,and information retrieval.The field of computer science encompasses various areas, including knowledge representation, natural language processing, robotics, medical image computing, computer architecture, and computer engineering. Computer architecture focuses on the conceptual design and operational structure of a computer system. It deals with the internal functioning of the central processing unit and its access to memory addresses. This field combines aspects of computer engineering and electrical engineering to select and connect hardware components that meet performance and cost objectives. Computer graphics, computer security, cryptography, and computational science are all important disciplines within computer science. Computer graphics involves studying digital visual contents such as image data synthesis and manipulation. It is closely associated with computer vision, image processing, and computational meter used in special effects and video games. Computer security aims to protect information against unauthorized access or alteration. Cryptography involves concealing and

decoding information through encryption algorithms influenced by computer science advancements.Computational science, also referred to as scientific computing, focuses on utilizing computers to construct mathematical models for the analysis and resolution of scientific problems. Its objective is to develop quantitative analysis techniques that can effectively tackle complex scientific challenges. In practical applications, computer simulation and other computation methods are often used in various scientific disciplines. Subfields within computational science include numerical analysis, computational physics, computational chemistry, bioinformatics, and computer networks. Computer networks specifically deal with managing global networks between computers. Concurrent, parallel, and distributed systems involve simultaneous computations that may interact with each other. Mathematical models such as Petri nets, process calculi, and the Parallel Random Access Machine model have been developed for general concurrent computation. Distributed systems establish connections between multiple computers through a network to enhance concurrency by allowing connected computers to have their own private memory and exchange information towards achieving a shared objective. In databases and information retrieval fields, the primary focus is on efficiently organizing, storing, and retrieving large amounts of data.Database management systems are utilized for the management of digital databases, making tasks such as data storage, creation, maintenance, and searching feasible across various database models and query languages. Health Informatics applies computational techniques to address healthcare problems. Information science encompasses multiple areas including information retrieval, knowledge representation, natural language processing (NLP), human-computer interaction (HCI), and software engineering. The primary concern of software engineering is the design of affordable high-quality software solutions that can be developed, maintained, debugged, tested, extended, deployed efficiently over time without excessive effort/costs/risks/dependencies/complexity/etc., while also meeting desired response times/user expectations/resource constraints/etc. In order for users to

effectively utilize software and achieve productivity, success, delight, enjoyment with stress-free operation along with confidence in reliability/security/flexibility/configurability/scalability/portability/adaptability/customizability/extensibility/migratability/divisibility/pluggability/composability/reusability/rescalability/refactorability/modularity/hack-ability/hobbyist-friendliness/community support/institutional acceptance/commercial viability/political stability and more.The process includes creating and analyzing software, both new and existing. Both computer applications software engineers and computer systems software engineers attend conferences that are important for academic research in computer science. These conferences bring together researchers from different sectors to present their recent work and engage with each other. The conference proceedings contribute significantly to the literature of computer science.

Some universities prioritize theoretical computation and algorithmic reasoning in their computer science programs. These programs cover various topics such as computation theory, algorithm analysis, formal methods, concurrency theory, databases, computer graphics, and systems analysis. Programming is taught alongside these subjects to complement other areas within computer science instead of being the sole focus. The ACM/IEEE-CSS Joint Curriculum Task Force provides curriculum guidelines for universities.

On the other hand, certain educational institutions prioritize advanced programming skills over algorithm theory and computation in their computer science curricula. These institutions include colleges, universities, secondary schools, and vocational programs known as software engineering programs that aim to equip students with the necessary skills for a career in the software industry.Despite the importance of computer science professions to the U.S. economy, most American K-12 curricula lack education on this subject. The Association for Computing Machinery (ACM) and the Computer Science Teachers Association (CAST) released a report in October 2010 titled "Running on Empty: The Failure to Teach K-12 Computer Science in the Digital Age", which revealed that only 14 states have implemented significant education standards for high school computer science. Furthermore, only nine states consider high school computer science

courses as a core academic subject for graduation requirements. To address this issue, Computing in the Core (Zinc), a non-partisan advocacy coalition, was established alongside "Running on Empty" to influence federal and state policies related to computer science education. One important policy is the Computer Science Education Act that aims to provide grants to states for improving computer science education and supporting computer science teachers. Additionally, there is also an observed gender gap within the United States' computer science education system.