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Most preprocessors are specific to a particular data processing task (e.g., compiling the C language). A preprocessor may be promoted as being general purpose , meaning that it is not aimed at a specific usage or programming language, and is intended to be used for a wide variety of text processing tasks.
Traditionally, the C preprocessor was a separate development tool from the compiler with which it is usually used. In that case, it can be used separately from the compiler. Notable examples include use with the (deprecated) imake system and for preprocessing Fortran.
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.
Intel oneAPI DPC++/C++ Compiler is available for Windows and Linux and supports compiling C, C++, SYCL, and Data Parallel C++ (DPC++) source, targeting Intel IA-32, Intel 64 (aka x86-64), Core, Xeon, and Xeon Scalable processors, as well as GPUs including Intel Processor Graphics Gen9 and above, Intel X e architecture, and Intel Programmable Acceleration Card with Intel Arria 10 GX FPGA. [5]
Preprocessing can refer to the following topics in computer science: Preprocessor , a program that processes its input data to produce output that is used as input to another program like a compiler Data pre-processing , used in machine learning and data mining to make input data easier to work with
Given the variety of data sources (e.g. databases, business applications) that provide data and formats that data can arrive in, data preparation can be quite involved and complex. There are many tools and technologies [5] that are used for data preparation. The cost of cleaning the data should always be balanced against the value of the ...
Semantic data mining is a subset of data mining that specifically seeks to incorporate domain knowledge, such as formal semantics, into the data mining process.Domain knowledge is the knowledge of the environment the data was processed in. Domain knowledge can have a positive influence on many aspects of data mining, such as filtering out redundant or inconsistent data during the preprocessing ...
In computer science, a compiler-compiler or compiler generator is a programming tool that creates a parser, interpreter, or compiler from some form of formal description of a programming language and machine. The most common type of compiler-compiler is called a parser generator. [1] It handles only syntactic analysis.