Policy-based design, also known as policy-based class design or policy-based programming, is the term used in Modern C++ Design for a design approach based on an idiom for C++ known as policies. It has been described as a compile-time variant of the strategy pattern, and has connections with C++ template metaprogramming. It was first popularized in C++ by Andrei Alexandrescu with Modern C++ Design and with his column Generic<Programming> in the C/C++ Users Journal, and it is currently closely associated with C++ and D as it requires a compiler with highly robust support for templates, which was not common before about 2003. Previous examples of this design approach, based on parameterized generic code, include parametric modules (functors) of the ML languages,and C++ allocators for memory management policy. The central idiom in policy-based design is a class template (called the host class), taking several type parameters as input, which are instantiated with types selected by th...
Programming language theory (PLT) is a branch of computer science that deals with the design, implementation, analysis, characterization, and classification of programming languages and of their individual features. It falls within the discipline of computer science, both depending on and affecting mathematics, software engineering, linguistics and even cognitive science. It has become a well-recognized branch of computer science, and an active research area, with results published in numerous journals dedicated to PLT, as well as in general computer science and engineering publications.
Numerical analysis is the study of algorithms that use numerical approximation (as opposed to symbolic manipulations) for the problems of mathematical analysis (as distinguished from discrete mathematics). Numerical analysis naturally finds application in all fields of engineering and the physical sciences, but in the 21st century also the life sciences, social sciences, medicine, business and even the arts have adopted elements of scientific computations. The growth in computing power has revolutionized the use of realistic mathematical models in science and engineering, and subtle numerical analysis is required to implement these detailed models of the world. For example, ordinary differential equations appear in celestial mechanics (predicting the motions of planets, stars and galaxies); numerical linear algebra is important for data analysis; stochastic differential equations and Markov chains are essential in simulating living cells for medicine and biology.
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