In computer science, strictness analysis refers to any algorithm used to prove that a function in a non-strict functional programming language is strict in one or more of its arguments. This information is useful to compilers because strict functions can be compiled more efficiently. Thus, if a function is proven to be strict (using strictness analysis) at compile time, it can be compiled to use a more efficient calling convention without changing the meaning of the enclosing program.
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Abstract interpretation
In computer science, abstract interpretation is a theory of sound approximation of the semantics of computer programs, based on monotonic functions over ordered sets, especially lattices. It can be viewed as a partial execution of a computer program which gains information about its semantics without performing all the calculations.
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In computer science, functional programming is a programming paradigm that treats computation as the evaluation of mathematical functions and avoids state and mutable data. It emphasizes the application of functions, in contrast to the imperative programming style, which emphasizes changes in state. Functional programming has its roots in lambda calculus, a formal system developed in the 1930s to investigate function definition, function application, and recursion.
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Abstraction (computer science)
In computer science, abstraction is the process by which data and programs are defined with a representation similar in form to its meaning, while hiding away the implementation details. Abstraction tries to reduce and factor out details so that the programmer can focus on a few concepts at a time. A system can have several abstraction layers whereby different meanings and amounts of detail are exposed to the programmer.
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Projection (mathematics)
Generally speaking, in mathematics, a projection is a mapping of a set (or of a mathematical structure) which is idempotent, which means that a projection is equal to its composition with itself. A projection may also refer to a mapping which has a left inverse. Both notions are strongly related, as follows. Let p be an idempotent map from a set E into itself (thus p¿p = p) and F = p(E) be the image of p.
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Data structure
In computer science, a data structure is a particular way of storing and organizing data in a computer so that it can be used efficiently. Different kinds of data structures are suited to different kinds of applications, and some are highly specialized to specific tasks. For example, B-trees are particularly well-suited for implementation of databases, while compiler implementations usually use hash tables to look up identifiers.
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