symbolic programming

In various other parts of symbolic programming there are only so many symbols.

An "assembler" program then translated, or assembled, these symbolic programming instructions into binary.

When doing symbolic programming from a formal mathematical specification the use of indirection can be quite helpful.

Through symbolic programming, complex processes can be developed that build other more intricate processes by dynamically combining smaller units of functionality.

"Symbolic programming language" and assembler (called "autocoder")

Symbolic programming is a conceptual framework for developing algorithms based on the idea that formulas and program components can be manipulated as if they themselves are data.

Experiments demonstrated that Edinburgh Prolog could compete with the processing speed of other symbolic programming languages such as Lisp.

In languages such as LISP and Prolog that support the symbolic programming paradigm, variables may reference portions of programmed functionality in addition to static data.

The power requirements of AI research were exacerbated by the Lisp symbolic programming language, when commercial hardware was designed and optimized for assembly- and Fortran-like programming languages.

This computer, with 20,000 BCD words of memory, was quite advanced for the time, and classes were taught in assembly language, symbolic programming, Fortran, Cobol, and numerical analysis.

It is often used to introduce symbolic programming techniques to programmers of more conventional languages like Pascal, who find POP syntax more familiar than that of Lisp.