散列表的设计-->线性探查法

性能分析:
散列表中条目数的比例较小时，使用线性探查法的效率较高.

package Hash;
import java.nio.BufferOverflowException;

/**
 * 散列表的设计
 * 线性探查法(linear probing)
 * @author baby69yy2000
 */
public class LinearProbingHash<T> {
	private T[] table;
	private int tableCapacity;
	private int size;
	
	public LinearProbingHash(int tableSize) {
		table = (T[]) new Object[tableSize];  
        this.tableCapacity = tableSize;
        size = 0;
	}
	
	public void add(T item) {
		int index, origIndex;
		index = (item.hashCode() & 0x7FFFFFFF) % tableCapacity;
		origIndex = index;
		do {
			if(table[index] == null) {
				table[index] = item;
				size++;
				return;
			}else
				index = (index + 1) % tableCapacity;
		} while(index != origIndex);
		throw new BufferOverflowException();
	}
	
	public boolean contains(T item) {
		return (find(item) < 0)? false: true;
	}
	
	public int size() {
		return size;
	}
	
	private int find(T item) {
		int index, origIndex;
		index = (item.hashCode() & 0x7FFFFFFF) % tableCapacity;
		origIndex = index;
		do {
			if(item.equals(table[index]))
				return index;
			else
				index = (index + 1) % tableCapacity;
			if(index == origIndex)
				return -1;
		} while(index != origIndex);
		return -1;
	}
	
	public String toString() {
		int max = tableCapacity - 1;
		StringBuffer buf = new StringBuffer();
		buf.append("[");
		for(int i = 0; i < tableCapacity; i++) {
			if(table[i] != null) {
				buf.append(table[i]);
				if(i < max)
					buf.append(", ");
			}
		}
		buf.append("]");
		return buf.toString();
	}

	public static void main(String[] args) {
		LinearProbingHash<Integer> lp = new LinearProbingHash<Integer>(10);
		lp.add(new Integer(54));
		lp.add(new Integer(77));
		lp.add(new Integer(94));
		lp.add(new Integer(89));
		lp.add(new Integer(14));
		lp.add(new Integer(45));
		lp.add(new Integer(35));
		lp.add(new Integer(76));
		
		System.out.println(lp); // [35, 76, 54, 94, 14, 77, 45, 89]
		System.out.println(lp.contains(new Integer(45))); // true
		System.out.println(lp.size()); // 8
	}

	

}