Javadoc clean-up

Author: phishman3579

src/com/jwetherell/algorithms/data_structures/AVLTree.java

@@ -12,9 +12,9 @@
  * trees are more rigidly balanced, they are faster than red-black trees for
  * lookup intensive applications. However, red-black trees are faster for
  * insertion and removal.
- * 
- * http://en.wikipedia.org/wiki/AVL_tree
- * 
+ * <p>
+ * @see <a href="https://en.wikipedia.org/wiki/AVL_tree">AVL Tree (Wikipedia)</a>
+ * <br>
  * @author Justin Wetherell <[email protected]>
  */
 public class AVLTree<T extends Comparable<T>> extends BinarySearchTree<T> {

src/com/jwetherell/algorithms/data_structures/BTree.java

@@ -14,9 +14,9 @@
  * two children. Unlike self-balancing binary search trees, the B-tree is
  * optimized for systems that read and write large blocks of data. It is
  * commonly used in databases and file-systems.
- * 
- * http://en.wikipedia.org/wiki/B-tree
- * 
+ * <p>
+ * @see <a href="https://en.wikipedia.org/wiki/B-tree">B-Tree (Wikipedia)</a>
+ * <br>
  * @author Justin Wetherell <[email protected]>
  */
 @SuppressWarnings("unchecked")

src/com/jwetherell/algorithms/data_structures/BinaryHeap.java

@@ -16,9 +16,9 @@
  * the tree is not complete, the nodes of that level are filled from left to
  * right. 2) The heap property: each node is right than or equal to each of its
  * children according to a comparison predicate defined for the data structure.
- * 
- * http://en.wikipedia.org/wiki/Binary_heap
- * 
+ * <p>
+ * @see <a href="https://en.wikipedia.org/wiki/Binary_heap">Binary Heap (Wikipedia)</a>
+ * <br>
  * @author Justin Wetherell <[email protected]>
  */
 @SuppressWarnings("unchecked")

src/com/jwetherell/algorithms/data_structures/BinarySearchTree.java

@@ -19,9 +19,9 @@
  * keys less than the node's key. 2) The right subtree of a node contains only
  * nodes with keys greater than the node's key. 3) Both the left and right
  * subtrees must also be binary search trees.
- * 
- * http://en.wikipedia.org/wiki/Binary_search_tree
- * 
+ * <p>
+ * @see <a href="https://en.wikipedia.org/wiki/Binary_search_tree">Binary Search Tree (Wikipedia)</a>
+ * <br>
  * @author Justin Wetherell <[email protected]>
  */
 @SuppressWarnings("unchecked")

src/com/jwetherell/algorithms/data_structures/CompactSuffixTrie.java

@@ -8,9 +8,9 @@
  * string in a way that allows for a particularly fast implementation of many
  * important string operations. This implementation is based upon a patricia
  * trie which IS a compact trie.
- * 
- * http://en.wikipedia.org/wiki/Suffix_trie
- * 
+ * <p>
+ * @see <a href="https://en.wikipedia.org/wiki/Suffix_trie">Suffix Trie (Wikipedia)</a>
+ * <br>
  * @author Justin Wetherell <[email protected]>
  */
 @SuppressWarnings("unchecked")

src/com/jwetherell/algorithms/data_structures/DisjointSet.java

@@ -3,14 +3,14 @@
 /**
  * In computer science, a disjoint-set data structure, also called a union–find data structure or merge–find set, is a data structure that keeps track of a set of 
  * elements partitioned into a number of disjoint (non-overlapping) subsets. 
- * 
- * It supports two useful operations:
+ * <p>
+ * It supports two useful operations:<br>
  *     Find: Determine which subset a particular element is in. Find typically returns an item from this set that serves as its "representative"; by comparing the 
- *           result of two Find operations, one can determine whether two elements are in the same subset.
- *     Union: Join two subsets into a single subset.
- * 
- * http://en.wikipedia.org/wiki/Disjoint-set_data_structure
- * 
+ *           result of two Find operations, one can determine whether two elements are in the same subset.<br>
+ *     Union: Join two subsets into a single subset.<br>
+ * <p>
+ * @see <a href="https://en.wikipedia.org/wiki/Disjoint-set_data_structure">Disjoint Set (Wikipedia)</a>
+ * <br>
  * @author Justin Wetherell <[email protected]>
  */
 @SuppressWarnings("unchecked")

src/com/jwetherell/algorithms/data_structures/FenwickTree.java

@@ -10,13 +10,13 @@
  * for calculation and manipulation of the prefix sums of a table of values. Fenwick trees 
  * primarily solve the problem of balancing prefix sum calculation efficiency with element 
  * modification efficiency. 
- * 
- * http://en.wikipedia.org/wiki/Fenwick_tree
- * 
+ * <p>
  * This class is meant to be somewhat generic, all you'd have to do is extend
  * the Data abstract class to store your custom data. I've included a range sum
  * implementations.
- * 
+ * <p>
+ * @see <a href="https://en.wikipedia.org/wiki/Fenwick_tree">Fenwick Tree (Wikipedia)</a>
+ * <br>
  * @author Justin Wetherell <[email protected]>
  */
 @SuppressWarnings("unchecked")

src/com/jwetherell/algorithms/data_structures/Graph.java

@@ -10,9 +10,9 @@
  * Graph. Could be directed or undirected depending on the TYPE enum. A graph is
  * an abstract representation of a set of objects where some pairs of the
  * objects are connected by links.
- * 
- * http://en.wikipedia.org/wiki/Graph_(mathematics)
- * 
+ * <p>
+ * @see <a href="https://en.wikipedia.org/wiki/Graph_(mathematics)">Graph (Wikipedia)</a>
+ * <br>
  * @author Justin Wetherell <[email protected]>
  */
 @SuppressWarnings("unchecked")

src/com/jwetherell/algorithms/data_structures/HashArrayMappedTrie.java

@@ -10,12 +10,12 @@
  * A hash array mapped trie (HAMT) is an implementation of an associative 
  * array that combines the characteristics of a hash table and an array mapped 
  * trie. It is a refined version of the more general notion of a hash tree.
- * 
+ * <p>
  * This implementation is 32-bit and steps in 5-bit intervals, maximum tree
  * height of 7.
- * 
- * http://en.wikipedia.org/wiki/Hash_array_mapped_trie
- * 
+ * <p>
+ * @see <a href="https://en.wikipedia.org/wiki/Hash_array_mapped_trie">Hash Array Mapped Trie (Wikipedia)</a>
+ * <br>
  * @author Justin Wetherell <[email protected]>
  */
 @SuppressWarnings("unchecked")

src/com/jwetherell/algorithms/data_structures/HashMap.java

@@ -9,9 +9,9 @@
  * Hash Map using either chaining or probing. hash map is a data structure that
  * uses a hash function to map identifying values, known as keys, to their
  * associated values.
- * 
- * http://en.wikipedia.org/wiki/Hash_table
- * 
+ * <p>
+ * @see <a href="https://en.wikipedia.org/wiki/Hash_table">Hash Map/Table (Wikipedia)</a>
+ * <br>
  * @author Justin Wetherell <[email protected]>
  */
 @SuppressWarnings("unchecked")