Added assessment of ancestor pointers to optimization_ideas.txt

This adds my assessment of the performance of the ancestor pointers optimization in practice to optimization_ideas.txt.

optimization_ideas.txt

@@ -27,8 +27,9 @@ Thoughts concerning optimization:
   a node's parent, we have to change the pointers for all of the descendants
   that are less than k levels below the node - up to 2^k - 1 nodes. Since there
   are O(log N) parent pointer changes per update, and updates already take
-  O(log^2 N) amortized time, we can afford a k value of up to lg lg N + c (but
-  interestingly, not O(log log N)).
+  O(log^2 N) amortized time, we can afford a k value of up to lg lg N + O(1)
+  (but interestingly, not O(log log N)). However, I think this would be
+  significantly slower than a B-tree in practice.
 - If I don't implement the B-tree optimization, there are a couple of small
   optimizations I could try. First, I could move the field
   EulerTourNode.augmentationFunc to EulerTourVertex, in order to save a little

src/main/java/com/github/btrekkie/connectivity/ConnGraph.java

@@ -39,8 +39,8 @@ import java.util.Map;
  * take O(log N) time rather than O(log N / log log N) time.
  *
  * This implementation is actually based on a slightly modified description of the data structure given in
- * http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-851-advanced-data-structures-spring-2012/lecture-videos/session-20-dynamic-graphs-ii/ .
- * The description in the video differs from the data structure in the paper in that the levels are numbered in reverse
+ * https://ocw.mit.edu/courses/6-851-advanced-data-structures-spring-2012/resources/session-20-dynamic-graphs-ii/ . The
+ * description in the video differs from the data structure in the paper in that the levels are numbered in reverse
  * order, the constraint on tree sizes is different, and the augmentation uses booleans in place of edges. In addition,
  * the video defines subgraphs G_i. The change in the constraint on tree sizes is beneficial because it makes it easier
  * to delete vertices.