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
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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
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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
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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：
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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)
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/* * 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()); } } } |
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/* * 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(); } } |
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/* * 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); } } |
