Java模拟栈和队列数据结构的基本示例讲解

栈和队列：
一般是作为程序员的工具，用于辅助构思算法，生命周期较短，运行时才被创建；
访问受限，在特定时刻，只有一个数据可被读取或删除；
是一种抽象的结构，内部的实现机制，对用户不可见，比如用数组、链表来实现栈。

模拟栈结构
同时，只允许一个数据被访问，后进先出
对于入栈和出栈的时间复杂度都为O(1),即不依赖栈内数据项的个数，操作比较快
例，使用数组作为栈的存储结构

public class StackS<T> {
  private int max;
  private T[] ary;
  private int top;  //指针，指向栈顶元素的下标

  public StackS(int size) {
    this.max = size;
    ary = (T[]) new Object[max];
    top = -1;
  }

  // 入栈
  public void push(T data) {
    if (!isFull())
      ary[++top] = data;
  }

  // 出栈
  public T pop() {
    if (isEmpty()) {
      return null;
    }
    return ary[top--];
  }

  // 查看栈顶
  public T peek() {
    return ary[top];
  }

  //栈是否为空
  public boolean isEmpty() {
    return top == -1;
  }

  //栈是否满
  public boolean isFull() {
    return top == max - 1;
  }

  //size
  public int size() {
    return top + 1;
  }

  public static void main(String[] args) {
    StackS<Integer> stack = new StackS<Integer>(3);
    for (int i = 0; i < 5; i++) {
      stack.push(i);
      System.out.println("size:" + stack.size());
    }
    for (int i = 0; i < 5; i++) {
      Integer peek = stack.peek();
      System.out.println("peek:" + peek);
      System.out.println("size:" + stack.size());
    }
    for (int i = 0; i < 5; i++) {
      Integer pop = stack.pop();
      System.out.println("pop:" + pop);
      System.out.println("size:" + stack.size());
    }

    System.out.println("----");

    for (int i = 5; i > 0; i--) {
      stack.push(i);
      System.out.println("size:" + stack.size());
    }
    for (int i = 5; i > 0; i--) {
      Integer peek = stack.peek();
      System.out.println("peek:" + peek);
      System.out.println("size:" + stack.size());
    }
    for (int i = 5; i > 0; i--) {
      Integer pop = stack.pop();
      System.out.println("pop:" + pop);
      System.out.println("size:" + stack.size());
    }
  }
}

上面的例子，有一个maxSize的规定，因为数组是要规定大小的，若想无限制，可以使用其他结构来做存储，当然也可以new一个新的长度的数组。
例，使用LinkedList存储来实现栈

public class StackSS<T> {
  private LinkedList<T> datas;

  public StackSS() {
    datas = new LinkedList<T>();
  }

  // 入栈
  public void push(T data) {
    datas.addLast(data);
  }

  // 出栈
  public T pop() {
    return datas.removeLast();
  }

  // 查看栈顶
  public T peek() {
    return datas.getLast();
  }

  //栈是否为空
  public boolean isEmpty() {
    return datas.isEmpty();
  }

  //size
  public int size() {
    return datas.size();
  }

  public static void main(String[] args) {
    StackS<Integer> stack = new StackS<Integer>(3);
    for (int i = 0; i < 5; i++) {
      stack.push(i);
      System.out.println("size:" + stack.size());
    }
    for (int i = 0; i < 5; i++) {
      Integer peek = stack.peek();
      System.out.println("peek:" + peek);
      System.out.println("size:" + stack.size());
    }
    for (int i = 0; i < 5; i++) {
      Integer pop = stack.pop();
      System.out.println("pop:" + pop);
      System.out.println("size:" + stack.size());
    }

    System.out.println("----");
    for (int i = 5; i > 0; i--) {
      stack.push(i);
      System.out.println("size:" + stack.size());
    }
    for (int i = 5; i > 0; i--) {
      Integer peek = stack.peek();
      System.out.println("peek:" + peek);
      System.out.println("size:" + stack.size());
    }
    for (int i = 5; i > 0; i--) {
      Integer pop = stack.pop();
      System.out.println("pop:" + pop);
      System.out.println("size:" + stack.size());
    }
  }
}

例，单词逆序，使用Statck结构

public class WordReverse {

  public static void main(String[] args) {
    reverse("株式会社");
  }

  static void reverse(String word) {
    if (word == null) return;
    StackSS<Character> stack = new StackSS<Character>();
    char[] charArray = word.toCharArray();
    int len = charArray.length;
    for (int i = 0; i <len; i++ ) {
      stack.push(charArray[i]);
    }
    StringBuilder sb = new StringBuilder();
    while (!stack.isEmpty()) {
      sb.append(stack.pop());
    }
    System.out.println("反转后：" + sb.toString());
  }
}

打印：

反转后：社会式株

模拟队列(一般队列、双端队列、优先级队列)
队列：
先进先出，处理类似排队的问题，先排的，先处理，后排的等前面的处理完了，再处理
对于插入和移除操作的时间复杂度都为O(1)，从后面插入，从前面移除
双端队列：
即在队列两端都可以insert和remove：insertLeft、insertRight，removeLeft、removeRight
含有栈和队列的功能，如去掉insertLeft、removeLeft，那就跟栈一样了；如去掉insertLeft、removeRight，那就跟队列一样了
一般使用频率较低，时间复杂度 O(1)
优先级队列：
内部维护一个按优先级排序的序列。插入时需要比较查找插入的位置，时间复杂度O(N)， 删除O(1)
 

/*
 * 队列  先进先出，一个指针指示插入的位置，一个指针指示取出数据项的位置
 */
public class QueueQ<T> {
  private int max;
  private T[] ary;
  private int front; //队头指针 指示取出数据项的位置
  private int rear; //队尾指针 指示插入的位置
  private int nItems; //实际数据项个数

  public QueueQ(int size) {
    this.max = size;
    ary = (T[]) new Object[max];
    front = 0;
    rear = -1;
    nItems = 0;
  }
  //插入队尾
  public void insert(T t) {
    if (rear == max - 1) {//已到实际队尾，从头开始
      rear = -1;
    }
    ary[++rear] = t;
    nItems++;
  }
  //移除队头
  public T remove() {
    T temp = ary[front++];
    if (front == max) {//列队到尾了，从头开始
      front = 0;
    }
    nItems--;
    return temp;
  }
  //查看队头
  public T peek() {
    return ary[front];
  }

  public boolean isEmpty() {
    return nItems == 0;
  }

  public boolean isFull() {
    return nItems == max;
  }

  public int size() {
    return nItems;
  }

  public static void main(String[] args) {
    QueueQ<Integer> queue = new QueueQ<Integer>(3);
    for (int i = 0; i < 5; i++) {
      queue.insert(i);
      System.out.println("size:" + queue.size());
    }
    for (int i = 0; i < 5; i++) {
      Integer peek = queue.peek();
      System.out.println("peek:" + peek);
      System.out.println("size:" + queue.size());
    }
    for (int i = 0; i < 5; i++) {
      Integer remove = queue.remove();
      System.out.println("remove:" + remove);
      System.out.println("size:" + queue.size());
    }

    System.out.println("----");

    for (int i = 5; i > 0; i--) {
      queue.insert(i);
      System.out.println("size:" + queue.size());
    }
    for (int i = 5; i > 0; i--) {
      Integer peek = queue.peek();
      System.out.println("peek:" + peek);
      System.out.println("size:" + queue.size());
    }
    for (int i = 5; i > 0; i--) {
      Integer remove = queue.remove();
      System.out.println("remove:" + remove);
      System.out.println("size:" + queue.size());
    }
  }

}

/*
 * 双端队列<span style="white-space:pre"> </span>两端插入、删除
 */
public class QueueQT<T> {
  private LinkedList<T> list;

  public QueueQT() {
    list = new LinkedList<T>();
  }

  // 插入队头
  public void insertLeft(T t) {
    list.addFirst(t);
  }

  // 插入队尾
  public void insertRight(T t) {
    list.addLast(t);
  }

  // 移除队头
  public T removeLeft() {
    return list.removeFirst();
  }

  // 移除队尾
  public T removeRight() {
    return list.removeLast();
  }

  // 查看队头
  public T peekLeft() {
    return list.getFirst();
  }

  // 查看队尾
  public T peekRight() {
    return list.getLast();
  }

  public boolean isEmpty() {
    return list.isEmpty();
  }

  public int size() {
    return list.size();
  }

}

/*
 * 优先级队列  队列中按优先级排序，是一个有序的队列
 */
public class QueueQP {
  private int max;
  private int[] ary;
  private int nItems; //实际数据项个数

  public QueueQP(int size) {
    this.max = size;
    ary = new int[max];
    nItems = 0;
  }
  //插入队尾
  public void insert(int t) {
    int j;
    if (nItems == 0) {
      ary[nItems++] = t;
    } else {
      for (j = nItems - 1; j >= 0; j--) {
        if (t > ary[j]) {
          ary[j + 1] = ary[j]; //前一个赋给后一个 小的在后    相当于用了插入排序，给定序列本来就是有序的，所以效率O(N)
        } else {
          break;
        }
      }
      ary[j + 1] = t;
      nItems++;
    }
    System.out.println(Arrays.toString(ary));
  }
  //移除队头
  public int remove() {
    return ary[--nItems]; //移除优先级小的
  }
  //查看队尾 优先级最低的
  public int peekMin() {
    return ary[nItems - 1];
  }

  public boolean isEmpty() {
    return nItems == 0;
  }

  public boolean isFull() {
    return nItems == max;
  }

  public int size() {
    return nItems;
  }

  public static void main(String[] args) {
    QueueQP queue = new QueueQP(3);
    queue.insert(1);
    queue.insert(2);
    queue.insert(3);
    int remove = queue.remove();
    System.out.println("remove:" + remove);

  }

}