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In addition to support for vectorized arithmetic and relational operations, these languages also vectorize common mathematical functions such as sine. For example, if x is an array, then y = sin (x) will result in an array y whose elements are sine of the corresponding elements of the array x. Vectorized index operations are also supported.
The OptimJ programming language is an extension of Java 5. As does Java, Optimj provides maps; but OptimJ also provides true associative arrays. Java arrays are indexed with non-negative integers; associative arrays are indexed with any type of key.
This article compares a large number of programming languages by tabulating their data types, their expression, statement, and declaration syntax, and some common operating-system interfaces. Conventions of this article
Matrix Toolkit Java is a linear algebra library based on BLAS and LAPACK. ojAlgo is an open source Java library for mathematics, linear algebra and optimisation. exp4j is a small Java library for evaluation of mathematical expressions. SuanShu is an open-source Java math library. It supports numerical analysis, statistics and optimization.
Like natural languages, programming languages follow rules for syntax and semantics. There are thousands of programming languages [ 1 ] and new ones are created every year. Few languages ever become sufficiently popular that they are used by more than a few people, but professional programmers may use dozens of languages in a career.
Reflective programming languages let programs examine and possibly modify their high-level structure at runtime or compile-time. This is most common in high-level virtual machine programming languages like Smalltalk, and less common in lower-level programming languages like C. Languages and platforms supporting reflection:
This comparison of programming languages compares how object-oriented programming languages such as C++, Java, Smalltalk, Object Pascal, Perl, Python, and others manipulate data structures. Object construction and destruction
Only Java has a data type for arbitrary precision decimal point calculations. Only C# has a type for working with complex numbers. In both languages, the number of operations that can be performed on the advanced numeric types is limited compared to the built-in IEEE 754 floating point types.