Refactor in WriteAwareBruteSolver, add javadoc
Refactor WriteAwareBruteSolver constructor to guard against a situation in which the class could have an inconsistent internal state
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@ -7,21 +7,72 @@ import org.apache.commons.text.similarity.LevenshteinDistance;
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/**
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* This is a write-aware brute solver implementation that uses the levenshtein distance to sort passcode permutations
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* into a tree. Walking the tree in-order (Likely a depth-first traversal internally) results in a naive nearest-neighbor
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* optimization that generally performs well, but may perform poorly in some cases.
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* optimization that generally performs well, but may perform poorly in some cases. Heuristic solutions exist that have
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* acceptable performance, and this is a more naive heuristic implementation.
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*
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* This permutation optimization problem is NP-hard and a perfect brute-force solution has a worst-case running time that
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* is super-polynomial. Heuristic solutions exist that have acceptable performance, and this is a more naive heuristic
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* implementation.
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* This permutation optimization problem is NP-hard and can be represented as the traveling salesperson problem.
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* Representing passcode permutations as vertices and the levenshtein distance as edges in an undirected, weighted graph,
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* an optimal solution is the shortest path satisfying a tour of the entire graph.
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*
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* A more advanced solution (based on Christofides, or another TSP heuristic) may result in more performance gains, but
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* the performance of this nearest-neighbor solution is adequate for the keypad sizes under test. A keypad size of 9
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* results in a graph of vertex-count 9!. It's unlikely performance gains from a more intelligent TSP solver would
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* offset the performance cost of building a graph and optimizing traversal.
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*/
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public class WriteAwareBruteSolver extends DumbBruteSolver {
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private final TreeSet<IntegerLevenshtein> orderedTree;
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private final Integer numpadSize;
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private Integer numpadSize;
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/**
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* Creates an ordered tree on instantiation to be used as a cache for subsequent brute-force solves.
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* @param numpadSize The size of the padlock's numpad, used in generation of the internal ordered tree
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*/
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public WriteAwareBruteSolver(int numpadSize) {
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orderedTree = new TreeSet<IntegerLevenshtein>();
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this.numpadSize = numpadSize;
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this.createOrderedTree(numpadSize);
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}
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/**
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* Solves the padlock passed in to the method. The padlock's internal state should be correct after this method
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* runs.
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* @param padlockAdapter A padlock conforming to the PadlockAdapter contract
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*/
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@Override
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public void solve(PadlockAdapter padlockAdapter) {
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int padlockNumpadSize = padlockAdapter.getNumpadSize();
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if (this.numpadSize != padlockNumpadSize) {
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this.createOrderedTree(padlockNumpadSize);
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}
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for (IntegerLevenshtein integerLevenshtein : orderedTree) {
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if (this.checkPermutation(integerLevenshtein.getIntegerData(), padlockAdapter)) {
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return;
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}
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}
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}
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/**
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* Returns the size of the tree (the number of possible permutations)
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* @return the size of the ordered tree
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*/
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public Integer getTreeSize() {
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return this.orderedTree.size();
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}
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/**
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* Creates an ordered tree of possible passcode permutations
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* @param size The number of keys on the numpad
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*/
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protected void createOrderedTree(int size) {
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if(this.numpadSize != size) {
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this.numpadSize = size;
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orderedTree.clear();
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}
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Integer[] currentPermutation = new Integer[numpadSize];
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for(int i = 0; i < numpadSize; i++) {
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currentPermutation[i] = i;
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@ -36,20 +87,4 @@ public class WriteAwareBruteSolver extends DumbBruteSolver {
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morePermutationsExist = this.calculateNextPermutation(currentPermutation, numpadSize);
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} while(morePermutationsExist);
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}
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public void solve(PadlockAdapter padlockAdapter) {
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int numpadSize = padlockAdapter.getNumpadSize();
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Iterator<IntegerLevenshtein> iterator = orderedTree.iterator();
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while(iterator.hasNext()) {
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if(this.checkPermutation(iterator.next().getIntegerData(), padlockAdapter)) {
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return;
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}
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}
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}
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public Integer getTreeSize() {
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return this.orderedTree.size();
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}
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}
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