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The smart BASIC for iOS naturally supports complex numbers in notation a + bi. Any variable, math operation or function can accept both real and complex numbers as arguments and return real or complex numbers depending on result. For example the square root of -4 is a complex number:
Can 3SUM be solved in strongly sub-quadratic time, that is, in time O(n 2−ϵ) for some ϵ>0? Can the edit distance between two strings of length n be computed in strongly sub-quadratic time? (This is only possible if the strong exponential time hypothesis is false.) Can X + Y sorting be done in o(n 2 log n) time?
C++ began as a fork of an early, pre-standardized C, and was designed to be mostly source-and-link compatible with C compilers of the time. [1] [2] Due to this, development tools for the two languages (such as IDEs and compilers) are often integrated into a single product, with the programmer able to specify C or C++ as their source language.
An early example of answer set programming was the planning method proposed in 1997 by Dimopoulos, Nebel and Köhler. [3] [4] Their approach is based on the relationship between plans and stable models. [5] In 1998 Soininen and Niemelä [6] applied what is now known as answer set programming to the problem of product configuration. [4]
Note that C99 and C++ do not implement complex numbers in a code-compatible way – the latter instead provides the class std:: complex. All operations on complex numbers are defined in the <complex.h> header. As with the real-valued functions, an f or l suffix denotes the float complex or long double complex variant of the function.
Examples of this are the x86 calling conventions. Adhering to an ABI (which may or may not be officially standardized) is usually the job of a compiler , operating system, or library author. However, an application programmer may have to deal with an ABI directly when writing a program in a mix of programming languages, or even compiling a ...
The technique was formalized in 1989 as "F-bounded quantification."[2] The name "CRTP" was independently coined by Jim Coplien in 1995, [3] who had observed it in some of the earliest C++ template code as well as in code examples that Timothy Budd created in his multiparadigm language Leda. [4]
A decision problem is a computational problem where the answer for every instance is either yes or no. An example of a decision problem is primality testing: "Given a positive integer n, determine if n is prime." A decision problem is typically represented as the set of all instances for which the answer is yes. For example, primality testing ...