Now I know there have been previous questions regarding this algorithm, however I honestly haven't come across a simple java implementation. Many people have copied and pasted the same code in their GitHub profiles, and its irritating me.
So for the purpose of interview exercise, I've planned to set out and implement the algorithm using a different approach.
The algorithm tend out to be very very challenging. I honestly am lost on how to go about it. The logic just doesn't make sense. I've nearly spent 4 days straight sketching the approach, but to no avail.
Therefore please enlighten us with your wisdom.
I'm primarily doing the algorithm based on this information Intuition behind the Aho-Corasick string matching algorithm
It would be a big bonus if one can implement their own solution here.
But here's the following incomplete and not working solution which I got really stuck at:
If your overwhelemed with the code, the main problem lies at the main algorithm of Aho-Corasick. We already have created the trie tree of dictionaries well.
But the issue is, that now that we have the trie strcuture, how do we actually start implementing.
None of the resources were helpful.
public class DeterminingDNAHealth {
private Trie tree;
private String[] dictionary;
private Node FailedNode;
private DeterminingDNAHealth() {
}
private void buildMatchingMachine(String[] dictionary) {
this.tree = new Trie();
this.dictionary = dictionary;
Arrays.stream(dictionary).forEach(tree::insert);
}
private void searchWords(String word, String[] dictionary) {
buildMatchingMachine(dictionary);
HashMap < Character, Node > children = tree.parent.getChildren();
String matchedString = "";
for (int i = 0; i < 3; i++) {
char C = word.charAt(i);
matchedString += C;
matchedChar(C, matchedString);
}
}
private void matchedChar(char C, String matchedString) {
if (tree.parent.getChildren().containsKey(C) && dictionaryContains(matchedString)) {
tree.parent = tree.parent.getChildren().get(C);
} else {
char suffix = matchedString.charAt(matchedString.length() - 2);
if (!tree.parent.getParent().getChildren().containsKey(suffix)) {
tree.parent = tree.parent.getParent();
}
}
}
private boolean dictionaryContains(String word) {
return Arrays.asList(dictionary).contains(word);
}
public static void main(String[] args) {
DeterminingDNAHealth DNA = new DeterminingDNAHealth();
DNA.searchWords("abccab", new String[] {
"a",
"ab",
"bc",
"bca",
"c",
"caa"
});
}
}I have setup a trie data structure which works fine. So no problem here
trie.java
public class Trie {
public Node parent;
public Node fall;
public Trie() {
parent = new Node('⍜');
parent.setParent(new Node());
}
public void insert(String word) {...}
private boolean delete(String word) {...}
public boolean search(String word) {...}
public Node searchNode(String word) {...}
public void printLevelOrderDFS(Node root) {...}
public static void printLevel(Node node, int level) {...}
public static int maxHeight(Node root) {...}
public void printTrie() {...}
}Same thing for Node.
Node.java
public class Node {
private char character;
private Node parent;
private HashMap<Character, Node> children = new HashMap<Character, Node>();
private boolean leaf;
// default case
public Node() {}
// constructor accepting the character
public Node(char character) {
this.character = character;
}
public void setCharacter(char character) {...}
public char getCharacter() {...}
public void setParent(Node parent) {...}
public Node getParent() {...}
public HashMap<Character, Node> getChildren() {...}
public void setChildren(HashMap<Character, Node> children) {...}
public void resetChildren() {...}
public boolean isLeaf() {...}
public void setLeaf(boolean leaf) {...}
}
