--- a/AATree.st	Thu Jun 14 11:37:52 2018 +0200
+++ b/AATree.st	Fri Jun 15 12:12:11 2018 +0200
@@ -1,3 +1,5 @@
+"{ Encoding: utf8 }"
+
 "
  COPYRIGHT (c) 2009 by eXept Software AG
               All Rights Reserved
@@ -42,13 +44,14 @@
     AA trees are named for Arne Andersson, their inventor.
 
     AA trees are a variation of the red-black tree, which in turn is an enhancement to the 
-    binary search tree. One caveat with the implementation is that it needs an extra level instvar
-    in the treeNode; this results in 25% more storage overhead as compared to a Red/Black or plain Binary tree.
-    For performance data, see performance.
+    binary search tree. 
+    One caveat with the implementation is that it needs an extra level instvar in the treeNode,
+    which results in 25% more storage overhead as compared to a Red/Black or plain Binary trees.
+    For performance data, red the comment in the performance documentation method.
 
     Usage:
         As seen in the performance charts, AA trees offer better average and worst case
-        performance, with a slightly lower best case performance. 
+        performance compared to SortedCollection, with a slightly lower best case performance. 
         Thus providing a more predictable performance 
         (within a factor of 2, as opposed to a much wider range for sortedCollections)
 
@@ -305,7 +308,7 @@
     It is super fast, when adding in 'almost sorted' or almost reverse-sorted order, 
     or when only a few elements are to be added later.
     To create a big sorted collection, it is better to first collect them all unsorted in
-    an orderedCollection, then convert in one operation using asSortedCollection.
+    an OrderedCollection, then convert in one operation using #asSortedCollection.
 
         Time to insert random 100000 individually into SortedCollection: 6037ms
         Time to insert random 100000 en-bloque into SortedCollection: 172ms