Programming language theoryProgramming language theory (PLT) is a branch of computer science that deals with the design, implementation, analysis, characterization, and classification of formal languages known as programming languages. Programming language theory is closely related to other fields including mathematics, software engineering, and linguistics. There are a number of academic conferences and journals in the area. History of programming languages and Programming language#History In some ways, the history of programming language theory predates even the development of programming languages themselves.
Computer programmingComputer programming is the process of performing particular computations (or more generally, accomplishing specific computing results), usually by designing and building executable computer programs. Programming involves tasks such as analysis, generating algorithms, profiling algorithms' accuracy and resource consumption, and the implementation of algorithms (usually in a particular programming language, commonly referred to as coding).
Theoretical computer scienceTheoretical computer science (TCS) is a subset of general computer science and mathematics that focuses on mathematical aspects of computer science such as the theory of computation, lambda calculus, and type theory. It is difficult to circumscribe the theoretical areas precisely. The ACM's Special Interest Group on Algorithms and Computation Theory (SIGACT) provides the following description: History of computer science While logical inference and mathematical proof had existed previously, in 1931 Kurt Gödel proved with his incompleteness theorem that there are fundamental limitations on what statements could be proved or disproved.
Computer engineeringComputer engineering (CoE or CpE) is a branch of electronic engineering and computer science that integrates several fields of computer science and electronic engineering required to develop computer hardware and software. Computer engineers require training in electronic engineering, computer science, hardware-software integration, software design, and software engineering. It uses the techniques and principles of electrical engineering and computer science, and can encompass areas such as artificial intelligence (AI), robotics, computer networks, computer architecture and operating systems.
Formal sciencesFormal science is a branch of science studying disciplines concerned with abstract structures described by formal systems, such as logic, mathematics, statistics, theoretical computer science, artificial intelligence, information theory, game theory, systems theory, decision theory, and theoretical linguistics. Whereas the natural sciences and social sciences seek to characterize physical systems and social systems, respectively, using empirical methods, the formal sciences use language tools concerned with characterizing abstract structures described by formal systems.
Applied sciencesThe following outline is provided as an overview of and topical guide to applied science: Applied science – the branch of science that applies existing scientific knowledge to develop more practical applications, including inventions and other technological advancements. Science itself is the systematic enterprise that builds and organizes knowledge in the form of testable explanations and predictions about the universe. Applied cryptography – applications of cryptography.
Academic disciplinesAn academic discipline or academic field is a subdivision of knowledge that is taught and researched at the college or university level. Disciplines are defined (in part) and recognized by the academic journals in which research is published, and the learned societies and academic departments or faculties within colleges and universities to which their practitioners belong. Academic disciplines are conventionally divided into the humanities, including language, art and cultural studies, and the scientific disciplines, such as physics, chemistry, and biology; the social sciences are sometimes considered a third category.
High-level programming languagesIn computer science, a high-level programming language is a programming language with strong abstraction from the details of the computer. In contrast to low-level programming languages, it may use natural language elements, be easier to use, or may automate (or even hide entirely) significant areas of computing systems (e.g. memory management), making the process of developing a program simpler and more understandable than when using a lower-level language. The amount of abstraction provided defines how "high-level" a programming language is.
