Isthere some "derived data structure" in computer science "a data structure that multiplies itself
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Ever heard of trees? They are just one example of a dynamic memory structure, although don't be mistaken - they don't populate themselves, it's your job as the programmer to make them do that.\n\nRawlyn.
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You can make such a program by following the links given below :\n\nhttp://www.apollowebworks.com/russell/java/lattice.html\nhttp://www.mathsteacher.com.au/year7/ch01_whole/04_mult/mult.htm\n\nAlso, there is a program in the book Programming in C by Brian Tussle
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Systems Applications and Products in Data Processing.
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I'm not sure if I understood correctly but check out the pigeonhole principle
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Something that calculates numbers in rapid succession.
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You can turn these into proper C++ statements:\n\nread a, b\n\nlet max = a\n\nif max < b\n  let max = b\nendif\n\nprint max\n\nThis program assumes that a <> b.
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Centralized data processing & Decentralized data processing
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You can.  Use the mapping (x, y, z) -> x.  Of course, that is a many-to-one mapping, and kind of useless.
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a variable quantity that can be resolved into components
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Commutative operation.
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Generically, it is an array of pointers that can change in size.  So you have a number of pointers refering to some data locations in memory, and you add and subtract pointers from the list as the program goes.
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There's not enough information, what type of list, I don't think you mean an Enumerated List, and into what type of split, are you talking about linked lists, or something like indexing using trees to navigate or manage keys?
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If you are really serious about programming, you should learn about data structures and algorithms independent of a programming language. Languages come and go, but the underlying principals remain the same.\n\nThey are a little hard to read and you can't cut and past any examples, but the definitive references for data structures and algorithms are Donald Knuth's "The Art of Computer Programming," volumes 1, 2, and 3.
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just think in terms of 0's and 1's, programming logic, and error-correcting codes.  add to that cryptography and cryptanalysis, as well as algorithms and -- well -- flowcharts!  all of these had their roots in one mathematical idea or another, and they can be seen in almost every computer science discipline.
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(m)\n\nThe fundamental components of a general-purpose computer are arithmetic and logic unit, control circuitry, storage space, and input/output devices. If storage was removed, the device we had would be a simple calculator instead of a computer. The ability to store instructions that form a computer program, and the information that the instructions manipulate is what makes stored program architecture computers versatile.\n\nDigital computer represents all information using the binary numeral system. Text, numbers, pictures, audio, and nearly any other form of information can be converted into a string of bits, or binary digits, each of which has a value of 1 or 0. A piece of information can be manipulated by any computer whose storage space is large enough to accommodate the corresponding data, or the binary representation of the piece of information. For example, a computer with a storage space of eight million bits, or one megabyte, could be used to edit a small novel.\n\n \nVarious forms of storage, divided according to their distance from the central processing unit.Various forms of storage, based on various natural phenomenon, have been invented. So far, no practical universal storage medium exists, and all forms of storage have some drawbacks. Therefore a computer system usually contains several kinds of storage, each with an individual purpose
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For a carefully structured, coherent, and comprehensive course of discrete mathematics, the approach is traditional, deductive, and straightforward, with no unnecessary abstraction. It is self-contained including all the fundamental ideas in the field. It can be approached by anyone with basic competence in arithmetic and experience of simple algebraic manipulations. Students of computer science whose curriculum may not allow the study of many ancillary mathematics courses will find it particularly useful. Mathematics students seeking a first approach to courses such as graph theory, combinatorics, number theory, coding theory, combinatorial optimization, and abstract algebra will also enjoy a clear introduction to these more specialized fields. You will want to present descriptions of numerous algorithms on a form close to that of a real programming language. To enable students to develop practical programs from the design of algorithms. Students of mathematics and computer science seeking an eloquent introduction to discrete mathematics should see the the source for further information.
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well, since you're using 1, i'm pretty sure the property you're looking for the multiplication property of identity, which basically states that anything multiplied by one is itself.