From 3e91d7006fc792367326ae5a259bde5f8aba89c3 Mon Sep 17 00:00:00 2001 From: William Pitcock Date: Sun, 2 Dec 2007 15:50:54 -0600 Subject: [PATCH] I was nuts when I wrote that comment, lets kill it off. --- src/irc_dictionary.c | 34 ---------------------------------- 1 file changed, 34 deletions(-) diff --git a/src/irc_dictionary.c b/src/irc_dictionary.c index b393e54b1..2c901e9ab 100644 --- a/src/irc_dictionary.c +++ b/src/irc_dictionary.c @@ -198,40 +198,6 @@ irc_dictionary_get_linear_index(struct Dictionary *dict, const char *key) * * Retunes the tree, self-optimizing for the element which belongs to key. * - * Tuning the tree structure is a very complex operation. Unlike - * 2-3-4 trees and BTree/BTree+ structures, this structure is a - * constantly evolving algorithm. - * - * Instead of maintaining a balanced tree, we constantly adapt the - * tree by nominating a new root nearby the most recently looked up - * or added data. We are constantly retuning ourselves instead of - * doing massive O(n) rebalance operations as seen in BTrees, - * and the level of data stored in a tree is dynamic, instead of being - * held to a restricted design like other trees. - * - * Moreover, we are different than a radix/patricia tree, because we - * don't statically allocate positions. Radix trees have the advantage - * of not requiring tuning or balancing operations while having the - * disadvantage of requiring a large amount of memory to store - * large trees. Our efficiency as far as speed goes is not as - * fast as a radix tree; but is close to it. - * - * The retuning algorithm uses the comparison callback that is - * passed in the initialization of the tree container. If the - * comparator returns a value which is less than zero, we push the - * losing node out of the way, causing it to later be reparented - * with another node. The winning child of this comparison is always - * the right-most node. - * - * Once we have reached the key which has been targeted, or have reached - * a deadend, we nominate the nearest node as the new root of the tree. - * If an exact match has been found, the new root becomes the node which - * represents key. - * - * This results in a tree which can self-optimize for both critical - * conditions: nodes which are distant and similar and trees which - * have ordered lookups. - * * Inputs: * - node to begin search from *