Book Image

Mastering Concurrency Programming with Java 9 - Second Edition

By : Javier Fernández González
Book Image

Mastering Concurrency Programming with Java 9 - Second Edition

By: Javier Fernández González

Overview of this book

Concurrency programming allows several large tasks to be divided into smaller sub-tasks, which are further processed as individual tasks that run in parallel. Java 9 includes a comprehensive API with lots of ready-to-use components for easily implementing powerful concurrency applications, but with high flexibility so you can adapt these components to your needs. The book starts with a full description of the design principles of concurrent applications and explains how to parallelize a sequential algorithm. You will then be introduced to Threads and Runnables, which are an integral part of Java 9's concurrency API. You will see how to use all the components of the Java concurrency API, from the basics to the most advanced techniques, and will implement them in powerful real-world concurrency applications. The book ends with a detailed description of the tools and techniques you can use to test a concurrent Java application, along with a brief insight into other concurrency mechanisms in JVM.
Table of Contents (21 chapters)
Title Page
About the Author
About the Reviewer
Customer Feedback

Possible problems in concurrent applications

Programming a concurrent application is not an easy job. Incorrect use of the synchronization mechanisms can create different problems with the tasks in your application. In this section, we describe some of these problems.

Data race

You can have a data race (also named race condition) in your application when you have two or more tasks writing a shared variable outside a critical section, that's to say, without using any synchronization mechanisms.

Under these circumstances, the final result of your application may depend on the order or execution of the tasks. Look at the following example:

public class Account { 
  private float balance; 
  public void modify (float difference) { 
    float value=this.balance; 

Imagine that two different tasks execute the modify() method in the same Account object. Depending on the order of execution of the sentences in the tasks, the final result can vary. Suppose that the initial balance is 1000 and the two tasks call the modify() method with 1000 as a parameter. The final result should be 3000, but if both tasks execute the first sentence at the same time and then the second sentence at the same time, the final result will be 2000. As you can see, the modify() method is not atomic and the Account class is not thread-safe.


There is a deadlock in your concurrent application when there are two or more tasks waiting for a shared resource that must be free from another thread that is waiting for another shared resource that must be free by one of the first ones. It happens when four conditions happen simultaneously in the system. They are the Coffman conditions, which are as follows:

  • Mutual exclusion: The resources involved in the deadlock must be nonshareable. Only one task can use the resource at a time.
  • Hold and wait condition: A task has the mutual exclusion for a resource and it's requesting the mutual exclusion for another resource. While it's waiting, it doesn't release any resources.
  • No pre-emption: The resources can only be released by the tasks that hold them.
  • Circular wait: There is a circular waiting where Task 1 is waiting for a resource that is being held by Task 2, which is waiting for a resource being held by Task 3, and so on until we have Task n that is waiting for a resource being held by Task 1.

Some mechanisms exist that you can use to avoid deadlocks:

  • Ignore them: This is the most commonly used mechanism. You suppose that a deadlock will never occur on your system, and if it occurs, you can see the consequences of stopping your application and having to re-execute it.
  • Detection: The system has a special task that analyzes the state of the system to detect whether a deadlock has occurred. If it detects a deadlock, it can take action to remedy the problem. For example, finishing one task or forcing the liberation of a resource.
  • Prevention: If you want to prevent deadlocks in your system, you have to prevent one or more of the Coffman conditions.
  • Avoidance: Deadlocks can be avoided if you have information about the resources that are used by a task before it begins its execution. When a task wants to start its execution, you can analyze the resources that are free in the system and the resources that the task needs so it is able to decide whether it can start its execution or not.


A livelock occurs when you have two tasks in your system that are always changing their states due to the actions of the other. Consequently, they are in a loop of state changes and unable to continue.

For example, you have two tasks - Task 1 and Task 2, and both need two resources - Resource 1 and Resource 2. Suppose that Task 1 has a lock on Resource 1, and Task 2 has a lock on Resource 2. As they are unable to gain access to the resource they need, they free their resources and begin the cycle again. This situation can continue indefinitely, so the tasks will never end their execution.

Resource starvation

Resource starvation occurs when you have a task in your system that never gets a resource that it needs to continue with its execution. When there is more than one task waiting for a resource and the resource is released, the system has to choose the next task that can use it. If your system doesn't have a good algorithm, it can have threads that are waiting for a long time for the resource.

Fairness is the solution to this problem. All the tasks that are waiting for a resource must have the resource in a given period of time. An option is to implement an algorithm that takes into account the time that a task has been waiting for a resource when it chooses the next task that will hold a resource. However, fair implementation of locks requires additional overhead, which may lower your program throughput.

Priority inversion

Priority inversion occurs when a low priority task holds a resource that is needed by a high priority task, so the low priority task finishes its execution before the high priority task.