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Generic programming pioneer Alexander Stepanov wrote, Generic programming is about abstracting and classifying algorithms and data structures. It gets its inspiration from Knuth and not from type theory. Its goal is the incremental construction of systematic catalogs of useful, efficient and abstract algorithms and data structures.
The hyphen is used by nearly all programmers writing COBOL (1959), Forth (1970), and Lisp (1958); it is also common in Unix for commands and packages, and is used in CSS. [5] This convention has no standard name, though it may be referred to as lisp-case or COBOL-CASE (compare Pascal case ), kebab-case , brochette-case , or other variants.
For example, suppose that a program defines two types, A and B, where B is a subtype of A. If the program tries to convert a value of type A to type B, which is known as downcasting, then the operation is legal only if the value being converted is actually a value of type B. Thus, a dynamic check is needed to verify that the operation is safe.
Positive numbers: Real numbers that are greater than zero. Negative numbers: Real numbers that are less than zero. Because zero itself has no sign, neither the positive numbers nor the negative numbers include zero. When zero is a possibility, the following terms are often used: Non-negative numbers: Real numbers that are greater than or equal ...
Impredicative polymorphism (also called first-class polymorphism) is the most powerful form of parametric polymorphism. [ 1 ] : 340 In formal logic , a definition is said to be impredicative if it is self-referential; in type theory, it refers to the ability for a type to be in the domain of a quantifier it contains.
Generics are checked at compile-time for type-correctness. [7] The generic type information is then removed in a process called type erasure. [6] For example, List<Integer> will be converted to the non-generic type List, which ordinarily contains arbitrary objects. The compile-time check guarantees that the resulting code uses the correct type.
Flow diagram. In computing, serialization (or serialisation, also referred to as pickling in Python) is the process of translating a data structure or object state into a format that can be stored (e.g. files in secondary storage devices, data buffers in primary storage devices) or transmitted (e.g. data streams over computer networks) and reconstructed later (possibly in a different computer ...
In computer science, a literal is a textual representation (notation) of a value as it is written in source code. [1] [2] Almost all programming languages have notations for atomic values such as integers, floating-point numbers, and strings, and usually for Booleans and characters; some also have notations for elements of enumerated types and compound values such as arrays, records, and objects.