Things to know about Stack & Heap

The JVM divided the memory into following sections.

  1. Heap
  2. Stack
  3. Code
  4. Static

This division of memory is required for its effective management.

The code section contains your bytecode.

The Stack section of memory contains methods, local variables and reference variables.

The Heap section contains Objects (may also contain reference variables).

The Static section contains Static data/methods.

Of all of the above 4 sections, you need to understand the allocation of memory in Stack & Heap the most, since it will affect your programming efforts

difference between instance variables and local variables

Instance variables are declared inside a class but not inside a method

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class Student{
int num; // num is  instance variable
public void showData{}

Local variables are declared inside a method including method arguments.

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public void sum(int a){
int x = int a +  3;
// a , x are local variables</strong>
}

the video demonstrates how memory is allocated in stack & heap.

Please be patient. The Video will load in some time. If you still face issue viewing video click here

Points to Remember:

  • When a method is called , a frame is created on the top of stack.
  • Once a method has completed execution , flow of control returns to the calling method and its corresponding stack frame is flushed.
  • Local variables are created in the stack
  • Instance variables are created in the heap & are part of the object they belong to.
  • Reference variables are created in the stack.

Point to Ponder: What if Object has a reference as its instance variable?

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public static void main(String args[]){ A parent = new A(); //more code } class A{ B child = new B(); int e; //more code } class B{ int c; int d; //more code }

In this case , the reference variable “child” will be created in heap ,which in turn will be pointing to its object, something like the diagram shown below.

When to use “static” keyword in Java

The static keyword can be used in 3 scenarios

  1. static variables
  2. static methods
  3. static blocks of code.

Lets look at static variables and static methods first.

static variable

  • It is a variable which belongs to the class and not toobject(instance)
  • Static variables are initialized only once , at the start of the execution . These variables will be initialized first, before the initialization of any instance variables
  • A single copy to be shared by all instances of the class
  • A static variable can be accessed directly by the class name and doesn’t need any object
  • Syntax : <class-name>.<variable-name>

static method

  • It is a method which belongs to the class and not to the object(instance)
  • A static method can access only static data. It can not access non-static data (instance variables)
  • A static method can call only other static methods and can not call a non-static method from it.
  • A static method can be accessed directly by the class name and doesn’t need any object
  • Syntax : <class-name>.<method-name>
  • A static method cannot refer to “this” or “super” keywords in anyway

Side Note:

  • main method is static , since it must be be accessible for an application to run , before any instantiation takes place.

Lets learn the nuances of the static keywords by doing some excercises!

Assignment: To Learn working of static variables & methods

Step 1) Copy the following code into a editor

public class Demo{
 public static void main(String args[]){
 Student s1 = new Student();
 s1.showData();
 Student s2 = new Student();
 s2.showData();
 //Student.b++;
 //s1.showData();
 }
}

class Student {
int a; //initialized to zero
static int b; //initialized to zero only when class is loaded not for each object created.

 Student(){
 //Constructor incrementing static variable b
 b++;
 }

 public void showData(){
 System.out.println("Value of a = "+a);
 System.out.println("Value of b = "+b);
 }
//public static void increment(){
//a++;
//}

}

This code is editable. Click Run to Compile + Execute

Step 2) Save & Compile the code. Run the code as, java Demo.

Step 3) Expected output show below

java-static-variable

Following diagram shows , how reference variables & objects are created and static variables are accessed by the different instances.

java-static

Step 4) It is possible to access a static variable from outside the class using the syntaxClassName.Variable_Name. Uncomment line # 7 & 8 . Save , Compile & Run . Observe the output.

Step 5) Uncomment line 25,26 & 27 . Save , Compile & Run.

Step 6) Error = ? This is because it is not possible to access instance variable “a” from static method “increment“.

static block

The static block, is a block of statement inside a Java class that will be executed when a class is first loaded in to the JVM

class Test{
  static{
  //code goes here
  }
}

A static block helps to initialize the static data members, just like constructors help to initialize instance members

Why Johnny Can’t Write Multithreaded Programs

Programming for multiple threads is not fundamentally different from writing an event-oriented GUI application or even a straight up sequential application. The important lessons of encapsulation, separation of concerns, loose coupling, etc. all apply. But developers get into trouble with multiple threads when they don’t apply those lessons; instead they try to apply the mostly-irrelevant bits of information they learned about threads and synchronization primitives from introductory multithreading texts.

Some people, when confronted with a problem, think, “I know, I’ll use regular expressions.” Now they have two problems. –Jaimie Zawinski

Some people, when confronted with a problem, think, “I know, I’ll use threads!” Now they have 10 problems. –Bill Schindler

Too many programmers writing multithreaded programs are like Mickey Mouse inThe Sorcerer’s Apprentice. They learn to create a bunch of threads and get them mostly working, but then the threads go completely out of control and the programmer doesn’t know what to do.

Unlike Mickey, those programmers don’t have the luxury of a kindly master wizard who can wave his magic wand and restore sanity. Instead, the programmer resorts to all manner of ugly hacks in an attempt to fix problems as they pop up. The result is invariably an overly complicated, restrictive, fragile, and unreliable application that’s prone to deadlocks and other multithreading hazards. Not to mention unexplained crashes, poor performance, and incomplete or incorrect results.

You’ve probably wondered why that is. Perhaps you’ve accepted the common fallacy that “Multithreading is hard.” It’s not. If a multithreaded program is unreliable it’s most likely due to the same reasons that single-threaded programs fail: The programmer didn’t follow basic, well known development practices. Multithreaded programs seem harder or more complex to write because two or more concurrent threads working incorrectly make a much bigger mess a whole lot faster than a single thread can.

The “multithreading is hard” fallacy is propagated by programmers who, out of their depth in a single-threaded world, jump feet first into multithreading – and drown. Rather than re-examine their development practices or preconceived notions, they stubbornly try to “fix” things, and use the “multithreading is hard” excuse to justify their unreliable programs and missed delivery dates.

Note that I’m talking here about the majority of programs that use multithreading. There are difficult multithreading scenarios, just as there are difficult scenarios in the single-threaded world. But those are relatively rare. For the majority of what most programmers do, the problems just aren’t that complicated. We move data around, transform it, perhaps do some calculations from time to time, and finally store the results in a database or display them on the screen.

Upgrading a typical single-threaded program so that it uses multiple threads isn’t (or shouldn’t be) very difficult. It becomes difficult for two reasons:

  • Developers fail to apply simple, well known development practices; and
  • Most of what they were taught in introductory multithreading materials is technically correct but completely irrelevant to the problems at hand.

The most important concepts in programming are universal; they apply equally to single-threaded and multithreaded programs. Programmers who drown in a sea of threads haven’t learned the important lessons from writing single-threaded programs. I know this because they make the same fundamental mistakes in their multithreaded programs as they do in their single-threaded programs.

Probably the most important lesson to be learned from the past 60 years of software development is that global mutable state is bad. Really bad. Programs that depend on global mutable state are harder to reason about and generally less reliable, because there are too many possible ways for the state to change. There is a huge amount of research to back up that generalization, and countless design patterns whose primary purpose is to implement some type of data hiding. The best thing you can do to make your programs easier to reason about is to eliminate as much global mutable state as possible.

In a single-threaded sequential program, the likelihood of data being mangled is proportional to the number of components that can modify that data.

It’s usually not possible to completely eliminate global state, but we developers have very effective tools for strictly controlling which parts of a program can modify it. In addition, we’ve learned to create restrictive API layers around primitive data structures so that we also control how those data structures are changed.

The problems of global mutable state became more apparent in the late ’80s and early ’90s with the widespread use of event-oriented programming. Programs no longer start at the beginning and follow a single predictable path to conclusion. Instead, the program has an initial state and events occur at unpredictable times in an unpredictable order. The code is still single-threaded, but it’s asynchronous. The likelihood of data being mangled increases because the order in which events can occur is a factor. It’s not uncommon to find that if event A occurs before event B, then everything’s fine. But if A follows B, especially if event C occurs in between, then the data is mangled beyond recognition.

Adding concurrent threads complicates the problem even further because multiple methods can manipulate the global state at the same time. It becomes impossible to reason about how the global state is changing. Not only is the order of events unpredictable, but multiple threads of execution can be updating the state at the same time. At least in the asynchronous case you can guarantee that one event will complete its processing before any other event can start. In short, it is possible to say with certainty what the global state will be at the end of an event’s processing. With multiple threads it’s impossible in the general case to say which events will execute concurrently, and it’s therefore impossible to say what the global state is at any given point in time.

A multithreaded program with extensive global mutable state is one of the best demonstrations of the Heisenberg uncertainty principle I know of. It’s impossible to examine the state without changing the program’s behavior.

When I launch into my prepared rant about global mutable state (a somewhat expanded version of the last few paragraphs), programmers roll their eyes and tell me that they already know that. If they do know that, their programs don’t show it. The programs are filled with global mutable state, and the programmers wonder why their programs don’t work.

Not surprisingly, the most important part of creating a multithreaded program is design: figuring out what the program has to do, designing independent modules to perform those functions, clearly identifying what data each module needs, and defining the communications paths between modules. [Also: designing the project team’s t-shirt. Some things take priority. –Ed.] The fundamental process is no different from designing a single-threaded program. The key to success is, as with a single-threaded program, limiting interactions between the modules. If you eliminate shared mutable state, then data sharing problems are impossible.

You might think that you can’t afford the time to design your application so that it doesn’t use global state. In my opinion you can’t afford not to. Trying to manage global mutable state kills more multithreaded programs than anything else. The more you have to manage, the more likely it is that your program will crash and burn.

Most real world programs require some shared state that can be changed, and that’s where programmers most often get into trouble. Seeing the need for sharing state, programmers often reach into their multithreading toolbox and pull out the only tool they have: the all-purpose lock (critical section, mutex, or whatever it’s called in their particular language). They figure, I suppose, that they can eliminate the data sharing problems with mutual exclusion.

The number of problems you can encounter with a single lock is astounding. There are race conditions to think about, gating problems with an overly broad lock, and fairness issues, just to name a few. If you have multiple locks, especially nested locks, you have to worry about deadlock, livelock, lock convoys, and other concurrency hazards in addition to the problems associated with a single lock. Things get complicated in a hurry.

When writing or reviewing application code, I have a simple rule of thumb that rarely fails: If you used a lock, you probably did something wrong.

That statement can be taken two ways:

  1. If you need a lock, then you probably have global mutable state that has to be protected against concurrent updates. The existence of global mutable state indicates a flaw in the application’s design, which you should review and change.
  2. Locks are difficult to use correctly, and locking bugs can be incredibly difficult to isolate. The likelihood of there being an error in the way you used the lock is very high. If I see a lock, especially in a program that exhibits unusual behavior, the first place I look for the failure is the code that depends on the lock being used correctly. And that’s where I usually find it.

Both of those interpretations apply.

Multithreading isn’t hard. Properly using synchronization primitives, though, is really, really, hard. You probably aren’t qualified to use even a single lock properly. Locks and other synchronization primitives are systems level constructs. People who know a lot more about multithreading use those constructs to build concurrent data structures and higher level synchronization constructs that mere application programmers like you and I use in our programs. Application programmers should use the low-level synchronization primitives about as often as they make direct device driver calls: almost never.

Trying to solve a data sharing problem with locks is like trying to put out a fire by throwing liquid oxygen on it. As with fires, prevention is the best solution. If you eliminate shared state, you have no reason to misuse those synchronization primitives.

Most of what you know about multithreading is irrelevant

Introductory multithreading materials explain what threads are. Then they launch into discussions of how to make those threads work together in various ways, such as controlling access to shared data with locks and semaphores, and perhaps controlling when things happen with events. There’s detailed discussion of condition variables, memory barriers, critical sections, mutexes, volatile fields, and atomic operations. You’re given examples of how to use those low level constructs to do all manner of systems level things. By the time a programmer is halfway through that material, she thinks she knows how to use those primitives in her applications. After all, if you understand how to use something at the systems level, using it at the application level should be trivial, right?

This is like teaching a teenager how to build an internal combustion engine from discrete parts and then, without the benefit of any driving instruction, setting him behind the wheel of a car and turning him loose on the roads. The teenager understands how the car works internally, but he has no idea how to drive it from point A to point B.

Knowing how threads work at the systems level is mostly irrelevant to understanding how to use them in an application program. I’m not saying that programmers shouldn’t know how things work under the hood, just that they shouldn’t expect that knowledge to be directly applicable to the design or implementation of a business application. After all, knowing the details of the intake, compression, combustion, and exhaust cycle doesn’t help you in getting from home to the grocery store and back.

Introductory multithreading textbooks (and computer science courses) shouldn’t be teaching those low level constructs. Rather, they should concentrate on common classes of problems and show developers how to use higher level constructs to solve those problems. For example, a large number of business applications are in concept extremely simple programs: They read data from one or more input devices, apply some arbitrarily complex processing to that data (perhaps querying some other stored data in the process), and then output the results.

These programs very often fit nicely into a producer-consumer model with three threads:

  • The input thread reads data and places it on the input queue.
  • The processing thread reads records from the input queue, processes them, and puts them on the output queue.
  • The output thread reads records from the output queue and stores them.

The three threads operate independently and communicate through the queues. Although technically those queues are shared state, in practice they are communications channels with their own internal, synchronization. The queues support multiple producers and consumers, all adding or removing items concurrently.

Because the input, processing, and output are each isolated, it’s easy to change their implementations without affecting the rest of the program. As long as the queue data types remain unchanged, the individual pieces can be refactored at will. In addition, because the queues handle an arbitrary number of producers and consumers, adding more producers or consumers is no problem. There could be a dozen input threads all writing to the same queue, or multiple processing threads removing input items and crunching the data. Within the confines of a single computer, this model scales well.

Perhaps most importantly, modern programming languages and libraries make it easy to create a producer-consumer application. In .NET you have concurrent collections and TPL Dataflow. Java has the Executer service, BlockingQueue, and other classes in the java.util.concurrent namespace. In C++ you have the Boost threading library and Intel’s Thread Building Blocks. Microsoft introduced its Asynchronous Agents with Visual Studio 2013. Similar libraries are available for Python, Javascript, Ruby, PHP, and for all I know many other languages. You can create a producer-consumer application with any of those packages without ever having to use a lock, semaphore, condition variable, or any other synchronization primitive.

Granted, those libraries likely make liberal use of many different synchronization primitives. That’s okay. Those libraries were written by people who know multithreading a whole lot better than does your average application programmer. Using a library like that is no different from using a language’s runtime library, or writing in a high level language rather than Assembly language.

The producer-consumer model is just one example. The libraries I mentioned above include classes with which you can implement many common multithreading design patterns without once dipping into low-level multithreading. It’s possible to create extensive multithreading applications without knowing a thing about how threads and synchronization work under the hood.

Use the libraries

Writing programs that use multiple threads is not fundamentally different from writing single-threaded synchronous programs. The important lessons of encapsulation and data hiding are universal, and become even more important when multiple concurrent threads are involved. If you ignore those important lessons, then no amount of low level threading knowledge can save you.

Programmers today have plenty to worry about at the application level without having to think about systems-level things. As applications become more involved, we increasingly hide complexity behind API layers. We’ve been doing this for decades. One could make a good argument that hiding complexity from programmers is the primary reason they are able to create complex applications. After all, don’t we already hide the complexities of the file system, the UI message loop, low-level communication protocols, etc.?

Multithreading concepts should be no different. The majority of multithreading scenarios business programmers are likely encounter are well known and implemented in libraries that hide the bewildering complexity of dealing with concurrency. We should use those libraries in the same way that we use libraries of user interface controls, communications protocols, and the countless other tools that simplify our jobs. Leave low level multithreading to the people who know what they’re doing: the ones who write the libraries we use to build real programs.

Jim Mischel is a developer with Professional Datasolutions, Inc., a leading provider of software, hardware, and professional services to convenience retailers and wholesale petroleum marketers. When he’s not banging out code or writing about his experiences, he’s probably putting in miles on his bike or working on his latest wood carving project. Keep up with Jim on his blog.

Thread Interference

Consider a simple class called Counter

class Counter {
    private int c = 0;

    public void increment() {
        c++;
    }

    public void decrement() {
        c--;
    }

    public int value() {
        return c;
    }

}

Counter is designed so that each invocation of increment will add 1 to c, and each invocation of decrement will subtract 1 from c. However, if a Counter object is referenced from multiple threads, interference between threads may prevent this from happening as expected.

Interference happens when two operations, running in different threads, but acting on the same data, interleave. This means that the two operations consist of multiple steps, and the sequences of steps overlap.

It might not seem possible for operations on instances of Counter to interleave, since both operations on c are single, simple statements. However, even simple statements can translate to multiple steps by the virtual machine. We won’t examine the specific steps the virtual machine takes — it is enough to know that the single expression c++ can be decomposed into three steps:

  1. Retrieve the current value of c.
  2. Increment the retrieved value by 1.
  3. Store the incremented value back in c.

The expression c-- can be decomposed the same way, except that the second step decrements instead of increments.

Suppose Thread A invokes increment at about the same time Thread B invokes decrement. If the initial value of c is 0, their interleaved actions might follow this sequence:

  1. Thread A: Retrieve c.
  2. Thread B: Retrieve c.
  3. Thread A: Increment retrieved value; result is 1.
  4. Thread B: Decrement retrieved value; result is -1.
  5. Thread A: Store result in c; c is now 1.
  6. Thread B: Store result in c; c is now -1.

Thread A’s result is lost, overwritten by Thread B. This particular interleaving is only one possibility. Under different circumstances it might be Thread B’s result that gets lost, or there could be no error at all. Because they are unpredictable, thread interference bugs can be difficult to detect and fix.

Design Pattern – Singleton Pattern

Singleton pattern is one of the simplest design patterns in Java. This type of design pattern comes under creational pattern as this pattern provides one of the best ways to create an object.

This pattern involves a single class which is responsible to create an object while making sure that only single object gets created. This class provides a way to access its only object which can be accessed directly without need to instantiate the object of the class.

Implementation

We’re going to create a SingleObject class. SingleObject class have its constructor as private and have a static instance of itself.

SingleObject class provides a static method to get its static instance to outside world. SingletonPatternDemo, our demo class will use SingleObjectclass to get a SingleObject object.

Singleton Pattern UML Diagram

Step 1

Create a Singleton Class.

SingleObject.java

public class SingleObject {

   //create an object of SingleObject
   private static SingleObject instance = new SingleObject();

   //make the constructor private so that this class cannot be
   //instantiated
   private SingleObject(){}

   //Get the only object available
   public static SingleObject getInstance(){
      return instance;
   }

   public void showMessage(){
      System.out.println("Hello World!");
   }
}

Step 2

Get the only object from the singleton class.

SingletonPatternDemo.java

public class SingletonPatternDemo {
   public static void main(String[] args) {

      //illegal construct
      //Compile Time Error: The constructor SingleObject() is not visible
      //SingleObject object = new SingleObject();

      //Get the only object available
      SingleObject object = SingleObject.getInstance();

      //show the message
      object.showMessage();
   }
}

Step 3

Verify the output.

Hello World!

Wifi Direct:群组问题

1.在 4.2 以上版本,如果直连配对成功过,设置里会显示已保存的群组,以后这两台手机连接就无需确认,可以直接连上,不会弹出对话框让用户选择同意或是拒绝。4.0 里还没有群组这个东西。

2.4.2版本的 WifiP2pSettings 源码中,连接成功后,会默认自动记下这个群组。

在 WifiPpManager 中,当有两设备连成功构成组后:

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case WifiP2pManager.RESPONSE_PERSISTENT_GROUP_INFO:
    WifiP2pGroupList groups = (WifiP2pGroupList) message.obj;
    if (listener != null) {
        ((PersistentGroupInfoListener) listener).onPersistentGroupInfoAvailable(groups);
    }
break;

而 onPersistentGroupInfoAvailable(groups) 是这个类中的内部接口中定义的方法,在 WifiP2pSettings 中实现了这个接口,重写了方法

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public void onPersistentGroupInfoAvailable(WifiP2pGroupList groups) {
    mPersistentGroup.removeAll();
    for (WifiP2pGroup group: groups.getGroupList()) {
        if (DBG)     Log.d(TAG, " group " + group);
        mPersistentGroup.addPreference(new WifiP2pPersistentGroup(getActivity(), group));
    }
}

得到组的列表,然后将组添加到界面上

3.群组封装的对象

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public class WifiP2pPersistentGroup extends Preference {
    public WifiP2pGroup mGroup;
    public WifiP2pPersistentGroup(Context context, WifiP2pGroup group) {
        super(context);
        mGroup = group;
    }
    @Override
    protected void onBindView(View view) {
        setTitle(mGroup.getNetworkName());
        super.onBindView(view);
    }
    int getNetworkId() {
        return mGroup.getNetworkId();
    }
    String getGroupName() {
        return mGroup.getNetworkName();
    }
}
// 如果点击了群组,弹出对话框问是否要删除群组
else if (preference instanceof WifiP2pPersistentGroup) {
    mSelectedGroup = (WifiP2pPersistentGroup) preference;
    showDialog(DIALOG_DELETE_GROUP);
}
else if (id == DIALOG_DELETE_GROUP) {
    int stringId = R.string.wifi_p2p_delete_group_message;
    AlertDialog dialog = new AlertDialog.Builder(getActivity())
        .setMessage(getActivity().getString(stringId))
        .setPositiveButton(getActivity().getString(R.string.dlg_ok), mDeleteGroupListener)
        .setNegativeButton(getActivity().getString(R.string.dlg_cancel), null)
        .create();
    return dialog;
}

4.删除群组

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//delete persistent group dialog listener
mDeleteGroupListener = new OnClickListener() {
@Override
public void onClick(DialogInterface dialog, int which) {
    if (which == DialogInterface.BUTTON_POSITIVE) {
        if (mWifiP2pManager != null) {
            mWifiP2pManager.deletePersistentGroup(mChannel,
                mSelectedGroup.getNetworkId(),
                new WifiP2pManager.ActionListener() {
                    public void onSuccess() {
                        if (DBG) Log.d(TAG, " delete group success");
                    }
                    public void onFailure(int reason) {
                        if (DBG) Log.d(TAG, " delete group fail " + reason);
                    }
                });
            }
        }
    }
};

5.manager.requestGroupInfo(channel, activity) 会调用 GroupInfoListener 接口里的 onGroupInfoAvailable 方法,得到组的信息。GroupInfoListener 这个接口要实现 onGroupInfoAvailable(WifiP2pGroup group) 方法,group 里包含一个 Group Owner 和多个 Group Client 的信息。

Wifi Direct:功能测试

1.WiFi 直连中收到 WIFI_P2P_STATE_CHANGED_ACTION 广播时,更改直连状态,根据状态不同执行相应操作。如果 WiFi 未开启,要跳到设置界面去设置,本来想如果设置返回还要判断执行,所以放到 onResum 方法里执行,但这样有问题,这个界面还可能跳到其它界面,状态可能没改变,而且 onResume 比广播接收者要调用的方法执行的更早,所以 onResume 里用到的 isWifiP2pEnabled 并不是最新的。所以后来放在更改状态之后执行,这样只要更改状态就执行。

        广播接收者收到广播调用Activity中的方法,设置状态后,把自己想要紧接着做的封装到一个方法。
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public void setIsWifiP2pEnabled(boolean isWifiP2pEnabled) {
    this.isWifiP2pEnabled = isWifiP2pEnabled;
    // 状态变化了,调用这个方法
    testAndDiscover();
}
// 看WiFi功能是否开启,若开启,去发现设备
private void testAndDiscover() {
 
    if(!isWifiP2pEnabled) {
        AlertDialog.Builder builder = new Builder(this);
        builder.setTitle("提示")
        .setMessage("请先确认您的设备支持WiFi直连功能。如果支持,请先在设置中开启WiFi")
        .setPositiveButton("去设置"new DialogInterface.OnClickListener() {
 
            @Override
            public void onClick(DialogInterface dialog, int which) {
                startActivity(new Intent(Settings.ACTION_WIRELESS_SETTINGS));
            }
        })
        .setNegativeButton("不弄了"new DialogInterface.OnClickListener() {
 
            @Override
            public void onClick(DialogInterface dialog, int which) {
 
            }
        }).show();
    else // 如果wifi直连功能支持并已开启
        WifiDirectUtil.discoverPeers(DeviceListActivity.this, manager, channel);
    }
}

2.广播接收者里收到的 WIFI_P2P_THIS_DEVICE_CHANGED_ACTION 这个广播是更新自己的状态

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if (WifiP2pManager.WIFI_P2P_THIS_DEVICE_CHANGED_ACTION.equals(action)) {
    // 更新自己的设备状态
    activity.updateThisDevice((WifiP2pDevice) intent
            .getParcelableExtra(WifiP2pManager.EXTRA_WIFI_P2P_DEVICE));
}
        收到广播的意图intent中保存了自己这个设备的信息,所以通过(WifiP2pDevice) intent.getParcelableExtra(WifiP2pManager.EXTRA_WIFI_P2P_DEVICE 来得到自己这台设备 WifiP2pDevice 对象。
        更新自己的设备状态
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public void updateThisDevice(WifiP2pDevice device) {
    TextView myName = (TextView) findViewById(R.id.my_name);
    TextView myStatus  = (TextView) findViewById(R.id.my_status);
    myName.setText(device.deviceName);
    myStatus.setText(Util.getDeviceStatus(device.status));
}

其中 device.status 是int型值,所以要转变为对应文字,这样看着有意义

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public static String getDeviceStatus(int deviceStatus) {
    switch (deviceStatus) {
    case WifiP2pDevice.AVAILABLE:
        return "Available";
    case WifiP2pDevice.INVITED:
        return "Invited";
    case WifiP2pDevice.CONNECTED:
        return "Connected";
    case WifiP2pDevice.FAILED:
        return "Failed";
    case WifiP2pDevice.UNAVAILABLE:
        return "Unavailable";
    default:
        return "Unknown";
    }
}

3.原来 discoverPeers,requestPeers 之类的方法都是放在Activity里,但如果作为一个库供其它程序调用的话要把这些方法提取出来放到一个工具类里。比如

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/**
   * 去发现设备
   * @param context
   * @param manager
   * @param channel
   */
public static void discoverPeers(final Context context, WifiP2pManager manager, Channel channel) {
    Log.i(TAG, "discoverPeers");
    manager.discoverPeers(channel, new ActionListener() {
 
        @Override
        public void onSuccess() {
            // 成功后,会收到对应广播
        }
 
        @Override
        public void onFailure(int reason) {
            Toast.makeText(context, "搜索设备失败,错误代码:" + reason,
                    Toast.LENGTH_SHORT).show();
        }
    });
}
 
/**
   * 更新自己这台设备的状态
   * @param activity
   * @param device
   */
public static void updateThisDevice(Activity activity, WifiP2pDevice device) {
    Log.i(TAG, "updateThisDevice");
    TextView myName = (TextView) activity.findViewById(R.id.my_name);
    TextView myStatus  = (TextView) activity.findViewById(R.id.my_status);
    myName.setText(device.deviceName);
    myStatus.setText(getDeviceStatus(device.status));
}
        这样在 Activity 和 BroadcastReceiver 中只要调用这些方法,并传入对应参数即可。
        在广播接收者里收到 WIFI_P2P_PEERS_CHANGED_ACTION 这个广播时,要调用 WifiP2pManager 的requestPeers 方法,第二个参数是 PeerListListener 对象,会自动回调里面的 onPeersAvailable 方法。原来是让设备列表的适配器直接实现 PeerListListener,但这样就写死了,所以考虑将这个 requestPeers 方法也提取到工具类里。
        在 onPeersAvailable 方法里得到更新的设备列表,应该去更新适配器的数据并刷新。原来是这样的
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@Override
public void onPeersAvailable(WifiP2pDeviceList peerList) {
    // peers 就是适配器中用到的那个设备列表集合    
    peers.clear();
    peers.addAll(peerList.getDeviceList());
 
    notifyDataSetChanged(); // 刷新适配器
    if (peers.size() == 0) {
        return;
    }
}

但现在将 PeerListListener 和适配器分离,所以考虑得到最新的列表后去通过方法调用去更改适配器中内容,然后再刷新,所以要在适配器类中添加一个方法,去设置它自己的那个 List 集合,但用户开始不知道一定要有这方法,所以写一个接口

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public interface BaseDeviceAdapter {
    /**
       * 更新适配器中的设备列表那个List集合。并刷新适配器内容
       * @param peers
       */
    public void updateDeviceList(List<WifiP2pDevice> peers);
}

这样自己写的 DeviceAdapter 实现接口,重写这个方法

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// 更新peers并刷新适配器
@Override
public void updateDeviceList(List<WifiP2pDevice> peers) {
    this.peers = peers;
    notifyDataSetChanged();
}

在工具类里

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/**
   * 查找设备
   * @param manager
   * @param channel
   * @param adapter 要更新内容的适配器,类型是自己定义的那个接口
   */
public static void requestPeers(WifiP2pManager manager,  Channel channel, final BaseDeviceAdapter adapter) {
    Log.i(TAG, "requestPeers");
    manager.requestPeers(channel, new PeerListListener() {
 
        @Override
        public void onPeersAvailable(WifiP2pDeviceList peerList) {
            List<WifiP2pDevice> peers = new ArrayList<WifiP2pDevice>();
            peers.clear();
            peers.addAll(peerList.getDeviceList());
 
            // 更新适配器中内容。利用参数传递的那个接口调用
            adapter.updateDeviceList(peers);
            if (peers.size() == 0) {
                return;
            }
        }
    });
}

4.连接一台设备,知道的是WifiP2pDevice,WifiP2pManager 真正去 connect 需要的 WifiP2pConfig 信息通过 WifiP2pDevice 来设置

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public static void connect(final Context context, WifiP2pManager manager,
    Channel channel, WifiP2pDevice device) {
    WifiP2pConfig config = new WifiP2pConfig();
    config.deviceAddress = device.deviceAddress;
    config.wps.setup = WpsInfo.PBC;
 
    manager.connect(channel, config, new ActionListener() {
        @Override
        public void onSuccess() {
            // WiFiDirectBroadcastReceiver will notify us. Ignore for now.
        }
 
        @Override
        public void onFailure(int reason) {
            Toast.makeText(context, "连接失败,请重试", Toast.LENGTH_SHORT).show();
        }
    });
}

5.广播接收者收到这个广播 WIFI_P2P_CONNECTION_CHANGED_ACTION 表示连接状态改变了

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if (manager == null) {
    return;
}
 
NetworkInfo networkInfo = (NetworkInfo) intent
                    .getParcelableExtra(WifiP2pManager.EXTRA_NETWORK_INFO);
 
if (networkInfo.isConnected()) { // 成功连接上
    Log.i(TAG, "收到广播:连接成功");
    WifiDirectUtil.requestConnectionInfo(manager, channel);
else {
    // 不管哪一方主动断开连接,这里都会收到广播,在这里去重置数据
    // 比如清空一些数据,或者重新 discoverPeers 显示到界面上
    activity.resetData();
}
        
// 在Activity中,如果直连断了,重新查找设备
public void resetData() {
    WifiDirectUtil.discoverPeers(DeviceListActivity.this, manager, channel);
}
        而在 Activity 中的 onCreate 方法中每次进入都调用 adapter.clearPeers() 先清空适配器中数据,不然上一次的数据不清空会影响下一次的界面显示内容。
        在适配器中
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public void clearPeers() {
    peers.clear();
    notifyDataSetChanged();
}

在 onDestory 中断开连接,如果原来是连接的,断开成功,如果原来就是断开的,断开失败,反正没影响。