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Simultaneous coding: When same parts of the data have different meanings and two or more codes are applied to the same parts, then this kind of coding is called simultaneous coding. [3] The process can be done manually, which can be as simple as highlighting different concepts with different colours, or fed into a software package.
Coding conventions allow programmers to have simple scripts or programs whose job is to process source code for some purpose other than compiling it into an executable. It is common practice to count the software size ( Source lines of code ) to track current project progress or establish a baseline for future project estimates .
Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession. [4] Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. [5]
The purpose of channel coding theory is to find codes which transmit quickly, contain many valid code words and can correct or at least detect many errors. While not mutually exclusive, performance in these areas is a trade-off.
Literate Programming by Donald Knuth is the seminal book on literate programming.. Literate programming is a programming paradigm introduced in 1984 by Donald Knuth in which a computer program is given as an explanation of how it works in a natural language, such as English, interspersed (embedded) with snippets of macros and traditional source code, from which compilable source code can be ...
MODIFIER words were used for additional refinement, qualification and readability. CLASS words ideally would be a very short list of data types relevant to a particular application. Common CLASS words might be: NO (number), ID (identifier), TXT (text), AMT (amount), QTY (quantity), FL (flag), CD (code), W (work) and so forth.
While data-driven design does prevent coupling of data and functionality, in some cases, data-driven programming has been argued to lead to bad object-oriented design, especially when dealing with more abstract data. This is because a purely data-driven object or entity is defined by the way it is represented. Any attempt to change the ...
The NIST Dictionary of Algorithms and Data Structures [1] is a reference work maintained by the U.S. National Institute of Standards and Technology. It defines a large number of terms relating to algorithms and data structures. For algorithms and data structures not necessarily mentioned here, see list of algorithms and list of data structures.