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Message: <blockquote data-quote="imhotep" data-source="post: 24061989" data-attributes="member: 562115">You want to know why the binary search is ia O(log<img src="data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7" class="smilie smilie--sprite smilie--sprite23" alt="(n)" title="Thumbs down    (n)" loading="lazy" data-shortname="(n)" />)? It's mathematics. Bit difficult to post the proof here.An easier way to look at it is...Each recursion you halve the number of remaining items if you’ve not already found the item you seek for. You can only divide a number n recursively into halves at most log<img src="data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7" class="smilie smilie--sprite smilie--sprite23" alt="(n)" title="Thumbs down    (n)" loading="lazy" data-shortname="(n)" /> times - and it is from this that the term log<img src="data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7" class="smilie smilie--sprite smilie--sprite23" alt="(n)" title="Thumbs down    (n)" loading="lazy" data-shortname="(n)" /> comes into play.Note this is not log to the base 10 we are talking here.. but log to a base of 2.</blockquote>

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