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Compound operations are operations that consist of more than one discrete operation. Expressions that include postfix or prefix increment (++), postfix or prefix decrement (--), or compound assignment operators always result in compound operations. Compound assignment expressions use operators such as *=, /=, %=, +=, -=, <<=, >>=, >>>=, ^= and |= [JLS 20052015]. Compound operations on shared variables must be performed atomically to prevent data races and race conditions.

For information about the atomicity of a grouping of calls to independently atomic methods that belong to thread-safe classes, see rule VNA03-J. Do not assume that a group of calls to independently atomic methods is atomic.

The Java Language Specification also permits reads and writes of 64-bit values to be non-atomic . For more information, (see rule VNA05-J. Ensure atomicity when reading and writing 64-bit values).

Noncompliant Code Example (Logical Negation)

This noncompliant code example declares a shared boolean flag variable and provides a toggle() method that negates the current value of flag.:

final class Flag {
  private boolean flag = true;

  public void toggle() {  // Unsafe
    flag = !flag;
  }

  public boolean getFlag() { // Unsafe
    return flag;
  }
}

Execution of this code may result in a data race because the value of flag is read, negated, and written back.

Consider, for example, two threads that call toggle(). The expected effect of toggling flag twice is that it is restored to its original value. However, the following scenario leaves flag in the incorrect state:

As a result, the effect of the call by t₂ is not reflected in flag; the program behaves as if toggle() was called only once, not twice.

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The toggle() method may also use the compound assignment operator ^= to negate the current value of flag.:

final class Flag {
  private boolean flag = true;

  public void toggle() {  // Unsafe
    flag ^= true;  // Same as flag = !flag;
  }

  public boolean getFlag() { // Unsafe
    return flag;
  }
}

This code is also not thread-safe. A A data race exists because ^= is a nonatomic non-atomic compound operation.

Noncompliant Code Example (Volatile)

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This compliant solution declares both the toggle() and getFlag() methods as synchronized.:

final class Flag {
  private boolean flag = true;

  public synchronized void toggle() {
    flag ^= true; // Same as flag = !flag;
  }

  public synchronized boolean getFlag() {
    return flag;
  }
}

This solution guards reads and writes to the flag field with a lock on the instance, that is, this. Furthermore, synchronization ensures that changes are visible to all threads. Now, only two execution orders are possible, one of which is shown in the following scenario:

The second execution order involves the same operations, but t₂ starts and finishes before t₁.
Compliance with rule LCK00-J. Use private final lock objects to synchronize classes that may interact with untrusted code can reduce the likelihood of misuse by ensuring that untrusted callers cannot access the lock object.

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In this compliant solution, the getFlag() method is not synchronized, and flag is declared as volatile. This solution is compliant because the read of flag in the getFlag() method is an atomic operation and the volatile qualification assures visibility. The toggle() method still requires synchronization because it performs a nonatomic non-atomic operation.

final class Flag {
  private volatile boolean flag = true;

  public synchronized void toggle() {
    flag ^= true; // Same as flag = !flag;
  }

  public boolean getFlag() {
    return flag;
  }
}

This approach must not be used for getter methods that perform any additional operations other than returning the value of a volatile field without use of synchronization. Unless read performance is critical, this technique may lack significant advantages over synchronization [Goetz 2006].

Compliant Solution (Read-Write Lock)

This compliant solution uses a read-write lock to ensure atomicity and visibility.:

final class Flag {
  private boolean flag = true;
  private final ReadWriteLock lock = new ReentrantReadWriteLock();
  private final Lock readLock = lock.readLock();
  private final Lock writeLock = lock.writeLock();

  public void toggle() {
    writeLock.lock();
    try {
      flag ^= true; // Same as flag = !flag;
    } finally {
      writeLock.unlock();
    }
  }

  public boolean getFlag() {
    readLock.lock();
    try {
      return flag;
    } finally {
      readLock.unlock();
    }
  }
}

Read-write locks allow shared state to be accessed by multiple readers or a single writer but never both. According to Goetz [Goetz 2006]:

In practice, read-write locks can improve performance for frequently accessed read-mostly data structures on multiprocessor systems; under other conditions they perform slightly worse than exclusive locks due to their greater complexity.

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This compliant solution declares flag to be of type AtomicBoolean.:

import java.util.concurrent.atomic.AtomicBoolean;

final class Flag {
  private AtomicBoolean flag = new AtomicBoolean(true);

  public void toggle() {
    boolean temp;
    do {
      temp = flag.get();
    } while (!flag.compareAndSet(temp, !temp));
  }

  public AtomicBoolean getFlag() {
    return flag;
  }
}

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In this noncompliant code example, multiple threads can invoke the setValues() method to set the a and b fields. Because this class fails to test for integer overflow, users of the Adder class must ensure that the arguments to the setValues() method can be added without overflow . (See rule see NUM00-J. Detect or prevent integer overflow for more information).)

final class Adder {
  private int a;
  private int b;

  public int getSum() {
    return a + b;
  }

  public void setValues(int a, int b) {
    this.a = a;
    this.b = b;
  }
}

The getSum() method contains a race condition. For example, when a and b currently have the values 0 and Integer.MAX_VALUE, respectively, and one thread calls getSum() while another calls setValues(Integer.MAX_VALUE, 0), the getSum() method might return either 0 or Integer.MAX_VALUE, or it might overflow. Overflow will occur when the first thread reads a and b after the second thread has set the value of a to Integer.MAX_VALUE, but before it has set the value of b to 0.

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In this noncompliant code example, a and b are replaced with atomic integers.:

final class Adder {
  private final AtomicInteger a = new AtomicInteger();
  private final AtomicInteger b = new AtomicInteger();

  public int getSum() {
    return a.get() + b.get();
  }

  public void setValues(int a, int b) {
    this.a.set(a);
    this.b.set(b);
  }
}

The simple replacement of the two int fields with atomic integers fails to eliminate the the race condition because the compound operation a.get() + b.get() is still non-atomic.

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This compliant solution synchronizes the setValues() and getSum() methods to ensure atomicity.:

final class Adder {
  private int a;
  private int b;

  public synchronized int getSum() {
    // Check for overflow 
    return a + b;
  }

  public synchronized void setValues(int a, int b) {
    this.a = a;
    this.b = b;
  }
}

The operations within the synchronized methods are now atomic with respect to other synchronized methods that lock on that object's monitor (that is, it's its intrinsic lock). It is now possible, for example, to add overflow checking to the synchronized getSum() method without introducing the possibility of a race condition.

Risk Assessment

When operations on shared variables are not atomic, unexpected results can be produced. For example, information can be disclosed inadvertently because one user can receive information about other users.

Automated Detection

Some available static analysis tools can detect the instances of nonatomic non-atomic update of a concurrently shared value. The result of the update is determined by the interleaving of thread execution. These tools can detect the instances where thread-shared data is accessed without holding an appropriate lock, possibly causing a race condition.

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Related Guidelines

Bibliography

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