If someone do completely correct, i will give %100 thumbs up and DON'T COPY AND PASTE MY CODE!!

Key and Value are the elements in the Hash Table, it is the basic topic in the HASH TABLE

public class HashST { private int N; // number of key-value pairs in the table private int M; // size of linear-probing table private Key[] keys; // the keys private Value[] vals; // the values public HashST() { this(16); } public HashST(int M) { this.M = M; keys = (Key[]) new Object[M]; vals = (Value[]) new Object[M]; } private void resize(int cap) { HashST t; t = new HashST(cap); for (int i = 0; i = M / 2) { resize(2 * M);} // double M (see text) int i; //uses empty spaces (marked by null) to terminate clusters of keys. If for (i = hash(key); keys[i] != null; i = (i + 1) % M) { if (keys[i].equals(key)) { vals[i] = val; return; } } keys[i] = key; vals[i] = val; N++; } public Value get(Key key) { for (int i = hash(key); keys[i] != null; i = (i + 1) % M) { if (keys[i].equals(key)) { return vals[i]; } } return null; } public void delete(Key key) { if (get(key) == null) {return;} int i = hash(key); while (!key.equals(keys[i])) { i = (i + 1) % M; } keys[i] = null; vals[i] = null; i = (i + 1) % M; while (keys[i] != null) { Key keyToRedo = keys[i]; Value valToRedo = vals[i]; keys[i] = null; vals[i] = null; N--; put(keyToRedo, valToRedo); i = (i + 1) % M; } N--; if (N > 0 && N == M / 8) resize(M / 2); } } 

public class SparseVector { // Implement Sparse Vector Class as an Hash Table // This provides constant time search and insertion private HashST st; // 1- constructor // 2- size // 3- put // 4- get public double dot(double[] that) { double sum = 0.0; // 5- USE: Object[] keys = st.keys(); // USE: get((int)keys[i]); return sum; } public static void show(double[] that){ for (int i = 0; i   Data Structures and Algorithms Hash Table Implementation of Sparse Vectors You are given the code for a linear probing hash table in HashST.java. Use this code to represent a sparse vector, where keys of HashST correspond to index of a sparse vector. The code for SparseVector is also given to you, but its constructor, size, put, get methods are missing. Also fill the missing parts of the dot-product method. 1. In the main method, create a sparse matrix as an array of SparseVector's. This sparse vector will have the same values as this matrix, 8 4 0 0 0 0 0 A-0 0 0 0 0 0 0 2. Write an array of type double r0.1 0.1 0.1 0.1 0. 0.25 0.25 3. Calulate and show the result of