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Groupthink (talk | contribs) →Efficiency and Scalability: bad revert |
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::::::So by the very nature of the big O terminology, I would argue that complexity is a measure of how an algorithm's requirements grow as the input grows, i.e., how it scales. This idea is how someone new to the field would understand it. On the other hand, big O notation deliberately ignores multiplying factors, which relates to efficiency. An algorithm can run 100 times slower than another, and hence have 1% of the efficiency, and still have the same complexity. If you have citations where the term "efficiency" is used, then I am sure they meant some looser meaning of the term, but that does not mean it belongs in an encyclopedia. [[User:Scottcraig|Scottcraig]] ([[User talk:Scottcraig|talk]]) 00:29, 15 January 2008 (UTC)
:::::::The meaning of given terminology can vary depending on context, and with all due respect, you do not have a good grasp of the proper meaning of the terminology in question in the context of this subject, and your rewrite is poor. Before reverting or rewriting again, please do some reading about this material and get a better grasp on technical definitions before barging in here and erroneously rewriting this article. [[User:Groupthink|Groupthink]] ([[User talk:Groupthink|talk]]) 06:19, 15 January 2008 (UTC)
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