Dynamic programming languageIn computer science, a dynamic programming language is a class of high-level programming languages, which at runtime execute many common programming behaviours that static programming languages perform during compilation. These behaviors could include an extension of the program, by adding new code, by extending objects and definitions, or by modifying the type system. Although similar behaviors can be emulated in nearly any language, with varying degrees of difficulty, complexity and performance costs, dynamic languages provide direct tools to make use of them.
Comparison of programming languages (syntax)This comparison of programming languages compares the features of language syntax (format) for over 50 computer programming languages. Programming language expressions can be broadly classified into four syntax structures: prefix notation Lisp (* (+ 2 3) (expt 4 5)) infix notation Fortran (2 + 3) * (4 ** 5) suffix, postfix, or Reverse Polish notation Forth 2 3 + 4 5 ** * math-like notation TUTOR (2 + 3)(45) $$ note implicit multiply operator When a programming languages has statements, they typically have conventions for: statement separators; statement terminators; and line continuation A statement separator demarcates the boundary between two separate statements.
Desktop environmentIn computing, a desktop environment (DE) is an implementation of the desktop metaphor made of a bundle of programs running on top of a computer operating system that share a common graphical user interface (GUI), sometimes described as a graphical shell. The desktop environment was seen mostly on personal computers until the rise of mobile computing. Desktop GUIs help the user to easily access and edit files, while they usually do not provide access to all of the features found in the underlying operating system.
Computer algebraIn mathematics and computer science, computer algebra, also called symbolic computation or algebraic computation, is a scientific area that refers to the study and development of algorithms and software for manipulating mathematical expressions and other mathematical objects. Although computer algebra could be considered a subfield of scientific computing, they are generally considered as distinct fields because scientific computing is usually based on numerical computation with approximate floating point numbers, while symbolic computation emphasizes exact computation with expressions containing variables that have no given value and are manipulated as symbols.
Comparison of statistical packagesThe following tables compare general and technical information for a number of statistical analysis packages. Support for various ANOVA methods Support for various regression methods. Support for various time series analysis methods. Support for various statistical charts and diagrams.
Model checkingIn computer science, model checking or property checking is a method for checking whether a finite-state model of a system meets a given specification (also known as correctness). This is typically associated with hardware or software systems, where the specification contains liveness requirements (such as avoidance of livelock) as well as safety requirements (such as avoidance of states representing a system crash). In order to solve such a problem algorithmically, both the model of the system and its specification are formulated in some precise mathematical language.
Translator (computing)A translator or programming language processor is a generic term that can refer to a compiler, assembler, or interpreter—anything that converts code from one computer language into another. These include translations between high-level and human-readable computer languages such as C++ and Java, intermediate-level languages such as Java bytecode, low-level languages such as the assembly language and machine code, and between similar levels of language on different computing platforms, as well as from any of these to any other of these.
BytecodeBytecode (also called portable code or p-code) is a form of instruction set designed for efficient execution by a software interpreter. Unlike human-readable source code, bytecodes are compact numeric codes, constants, and references (normally numeric addresses) that encode the result of compiler parsing and performing semantic analysis of things like type, scope, and nesting depths of program objects. The name bytecode stems from instruction sets that have one-byte opcodes followed by optional parameters.
SNOBOLSNOBOL ("StriNg Oriented and symBOlic Language") is a series of programming languages developed between 1962 and 1967 at AT&T Bell Laboratories by David J. Farber, Ralph E. Griswold and Ivan P. Polonsky, culminating in SNOBOL4. It was one of a number of text-string-oriented languages developed during the 1950s and 1960s; others included COMIT and TRAC. SNOBOL4 stands apart from most programming languages of its era by having patterns as a first-class data type (i.e.
Shared memoryIn computer science, shared memory is memory that may be simultaneously accessed by multiple programs with an intent to provide communication among them or avoid redundant copies. Shared memory is an efficient means of passing data between programs. Depending on context, programs may run on a single processor or on multiple separate processors. Using memory for communication inside a single program, e.g. among its multiple threads, is also referred to as shared memory.
