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"Don't repeat yourself" (DRY), also known as "duplication is evil", is a principle of software development aimed at reducing repetition of information which is likely to change, replacing it with abstractions that are less likely to change, or using data normalization which avoids redundancy in the first place.
In computer programming, duplicate code is a sequence of source code that occurs more than once, either within a program or across different programs owned or maintained by the same entity. Duplicate code is generally considered undesirable for a number of reasons. [ 1 ]
A quine's output is exactly the same as its source code. A quine is a computer program that takes no input and produces a copy of its own source code as its only output. The standard terms for these programs in the computability theory and computer science literature are "self-replicating programs", "self-reproducing programs", and "self-copying programs".
Following is a list of code names that have been used to identify computer hardware and software products while in development. In some cases, the code name became the completed product's name, but most of these code names are no longer used once the associated products are released.
In software engineering and programming language theory, the abstraction principle (or the principle of abstraction) is a basic dictum that aims to reduce duplication of information in a program (usually with emphasis on code duplication) whenever practical by making use of abstractions provided by the programming language or software libraries. [1]
It states that two instances of similar code do not require refactoring, but when similar code is used three times, it should be extracted into a new procedure. The rule was popularised by Martin Fowler in Refactoring [1] and attributed to Don Roberts. Duplication is considered a bad practice in programming because it makes the code harder to ...
In computing, data deduplication is a technique for eliminating duplicate copies of repeating data. Successful implementation of the technique can improve storage utilization, which may in turn lower capital expenditure by reducing the overall amount of storage media required to meet storage capacity needs.
This is a list of well-known data structures. For a wider list of terms, see list of terms relating to algorithms and data structures. For a comparison of running times for a subset of this list see comparison of data structures.