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A consistent locking policy guarantees that multiple threads cannot simultaneously access or modify shared data. When two or more operations must be performed as a single atomic operation, a consistent locking policy must be implemented using either intrinsic synchronization or java.util.concurrent utilities. In the absence of such a policy, the code is susceptible to race conditions.

Given an invariant involving multiple objects, a programmer may incorrectly assume that a group When presented with a set of operations, where each is guaranteed to be atomic, it is tempting to assume that a single operation consisting of individually atomic operations is guaranteed to be collectively atomic without additional locking. Similarly, programmers may might incorrectly assume that use of a thread-safe Collection is sufficient to preserve an invariant that involves the collection's elements without additional synchronization. A thread-safe class can only guarantee atomicity of its individual methods. A grouping of calls to such methods requires additional synchronization for the group.

Consider, for example, a scenario where in which the standard thread-safe API lacks a single method both to both find a particular person's record in a Hashtable and also update the corresponding to update that person's payroll information. In such cases, the two method invocations must be performed atomically.

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Compound operations on shared variables are also non-atomic . For more information, see rule (see VNA02-J. Ensure that compound operations on shared variables are atomic for more information).

Rule VNA04-J. Ensure that calls to chained methods are atomic describes a specialized case of this rule.

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This noncompliant code example wraps references to BigInteger objects within within thread-safe AtomicReference objects.:

final class Adder {
  private final AtomicReference<BigInteger> first;
  private final AtomicReference<BigInteger> second;

  public Adder(BigInteger f, BigInteger s) {
    first  = new AtomicReference<BigInteger>(f);
    second = new AtomicReference<BigInteger>(s);
  }

  public void update(BigInteger f, BigInteger s) { // Unsafe
    first.set(f);
    second.set(s);
  }

  public BigInteger add() { // Unsafe
    return first.get().add(second.get());
  }
}

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This compliant solution declares the update() and add() methods synchronized to guarantee atomicity.:

final class Adder {
  // ...
  private final AtomicReference<BigInteger> first;
  private final AtomicReference<BigInteger> second;

  public Adder(BigInteger f, BigInteger s) {
    first  = new AtomicReference<BigInteger>(f);
    second = new AtomicReference<BigInteger>(s);
  }



  public synchronized void update(BigInteger f, BigInteger s){
    first.set(f);
    second.set(s);
  }

  public synchronized BigInteger add() {
    return first.get().add(second.get());
  }
}

Noncompliant Code Example (synchronizedList())

This noncompliant code example uses a java.util.ArrayList<E> collection, which is not thread-safe. However, the example uses Collections.synchronizedList as a synchronization wrapper for the ArrayList. It subsequently uses an array, rather than an iterator, to iterate over the ArrayList to avoid a ConcurrentModificationException.

final class IPHolder {
  private final List<InetAddress> ips = 
      Collections.synchronizedList(new ArrayList<InetAddress>());

  public void addAndPrintIPAddresses(InetAddress address) {
    ips.add(address);
    InetAddress[] addressCopy = 
        (InetAddress[]) ips.toArray(new InetAddress[0]);
    // Iterate through array addressCopy ...
  }
}

Individually, the add() and toArray() collection methods are atomic. However, when called in succession (for example as shown in the addAndPrintIPAddresses() method), they lack any there is no guarantee that the combined operation is atomic. The addAndPrintIPAddresses() method contains a a race condition that allows one thread to add to the list and a second thread to race in and modify the list before the first thread completes. Consequently, the addressCopy array may contain more IP addresses than expected.

Compliant Solution (Synchronized Block)

The The race condition can be eliminated by synchronizing on the underlying list's lock. This compliant solution encapsulates all references to the array list within synchronized blocks.:

final class IPHolder {
  private final List<InetAddress> ips = Collections
      Collections.synchronizedList(new ArrayList<InetAddress>());

  public void addAndPrintIPAddresses(InetAddress address) {
    synchronized (ips) {
      ips.add(address);
      InetAddress[] addressCopy = 
          (InetAddress[]) ips.toArray(new InetAddress[0]);
      // Iterate through array addressCopy ...
    }
  }
}

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This technique is also called client-side locking \ [[Goetz 2006|AA. Bibliography#Goetz 06]\] because the class holds a lock on an object that might be accessible to other classes. Client-side locking is not always an appropriate strategy ; see rule [(see LCK11-J. Avoid client-side locking when using classes that do not commit to their locking strategy] for more information).

This code does not violate rule LCK04-J. Do not synchronize on a collection view if the backing collection is accessible because, while although it does synchronize synchronizes on a collection view (the synchronizedList result), the backing collection is inaccessible and therefore consequently cannot be modified by any code.

Noncompliant Code Example (synchronizedMap)

Note that this compliant solution does not actually use the synchronization offered by Collections.synchronizedList(). If no other code in this solution used it, it could be eliminated.

Noncompliant Code Example (synchronizedMap())

This noncompliant code example defines the KeyedCounter class that is not thread-safe. Although the HashMap is wrapped in a synchronizedMap(), the overall increment operation is not atomic [Lee 2009 Wiki MarkupThis noncompliant code example defines the {{KeyedCounter}} class that is not thread-safe. Although the {{HashMap}} is wrapped in a {{synchronizedMap}}, the overall increment operation is fails to be atomic \[[Lee 2009|AA. Bibliography#Lee 09]\].

final class KeyedCounter {
  private final Map<String, Integer> map =
      Collections.synchronizedMap(new HashMap<String, Integer>());

  public void increment(String key) {
    Integer old = map.get(key);
    int oldValue = (old == null) ? 0 : old.intValue();
    if (oldValue == Integer.MAX_VALUE) {
      throw new ArithmeticException("Out of range");
    }
    map.put( key, oldValue + 1);
  }

  public Integer getCount(String key) {
    return map.get(key);
  }
}

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This compliant solution ensures atomicity by using an internal private lock object to synchronize the statements of the increment() and getCount() methods.:

final class KeyedCounter {
  private final Map<String, Integer> map =
      new HashMap<String, Integer>();
  private final Object lock = new Object();

  public void increment(String key) {
    synchronized (lock) {
      Integer old = map.get(key);
      int oldValue = (old == null) ? 0 : old.intValue();
      if (oldValue == Integer.MAX_VALUE) {
        throw new ArithmeticException("Out of range");
      }
      map.put(key, oldValue + 1);
    }
  }

  public Integer getCount(String key) {
    synchronized (lock) {
      return map.get(key);
    }
  }
}

This compliant solution avoids using Collections.synchronizedMap() because locking on the unsynchronized map provides sufficient thread-safety for this application. Rule LCK04-J. Do not synchronize on a collection view if the backing collection is accessible provides more information about synchronizing on synchronizedMap() objects.

Compliant Solution (ConcurrentHashMap)

The previous compliant solution is safe for multithreaded use , but fails to does not scale well because of excessive synchronization, which can lead to contention and deadlockdecreased performance.

Wiki MarkupThe {{ConcurrentHashMap}} class used in this compliant solution provides several utility methods for performing atomic operations and is often a good choice for algorithms that must scale \[ [Lee 2009|AA. Bibliography#Lee 09]\].].

Note that this compliant solution still requires synchronization, because without it, the test to prevent overflow and the increment will not happen atomically, so two threads calling increment() can still cause overflow. The synchronization block is smaller and does not include the lookup or addition of new values, so it has less impact on performance than the previous compliant solution.

final class KeyedCounter {
  private final ConcurrentMap<String, AtomicInteger> map =
      new ConcurrentHashMap<String, AtomicInteger>();
  private final Object lock = new Object();

  public void increment(String key

final class KeyedCounter {
  private final ConcurrentMap<String, AtomicInteger> map =
    new ConcurrentHashMap<String, AtomicInteger>();

  public void increment(String key) {
    AtomicInteger value = new AtomicInteger();
    AtomicInteger old = map.putIfAbsent(key, value);

    if (old != null) {
      value = old;
    }

    if (value.get() == Integer.MAX_VALUE) {
    AtomicInteger value throw= new ArithmeticException("Out of range"AtomicInteger();
    }

AtomicInteger old = map.putIfAbsent(key, value.incrementAndGet(); // Increment the value atomically

  }

  publicif Integer getCount(String key(old != null) {
     AtomicInteger value = map.get(key);old;
    }

    returnsynchronized (value == null) ? null : lock) {
      if (value.get();
  }

  // Other accessors ...
}

According to Section 5.2.1., "ConcurrentHashMap" of the work of Goetz and colleagues \[[Goetz 2006|AA. Bibliography#Goetz 06]\]:

ConcurrentHashMap, along with the other concurrent collections, further improve on the synchronized collection classes by providing iterators that do not throw ConcurrentModificationException, as a result eliminating the need to lock the collection during iteration. The iterators returned by ConcurrentHashMap are weakly consistent instead of fail-fast. A weakly consistent iterator can tolerate concurrent modification, traverses elements as they existed when the iterator was constructed, and may (but is not guaranteed to) reflect modifications to the collection after the construction of the iterator.

Note that methods such as ConcurrentHashMap.size() and ConcurrentHashMap.isEmpty() are allowed to return an approximate result for performance reasons. Code should avoid relying on these return values when exact results are required.

Risk Assessment

Failure to ensure the atomicity of two or more operations that must be performed as a single atomic operation can result in race conditions in multithreaded applications.

Related Vulnerabilities

Any vulnerabilities resulting from the violation of this rule are listed on the CERT website.

Related Guidelines

Bibliography

) == Integer.MAX_VALUE) {
        throw new ArithmeticException("Out of range");
      }
      value.incrementAndGet(); // Increment the value atomically
    }
  }

  public Integer getCount(String key) {
    AtomicInteger value = map.get(key);
    return (value == null) ? null : value.get();
  }

  // Other accessors ...
}

According to Section 5.2.1., "ConcurrentHashMap," of the work of Goetz and colleagues [Goetz 2006]:

ConcurrentHashMap, along with the other concurrent collections, further improve on the synchronized collection classes by providing iterators that do not throw ConcurrentModificationException, as a result eliminating the need to lock the collection during iteration. The iterators returned by ConcurrentHashMap are weakly consistent instead of fail-fast. A weakly consistent iterator can tolerate concurrent modification, traverses elements as they existed when the iterator was constructed, and may (but is not guaranteed to) reflect modifications to the collection after the construction of the iterator.

Note that methods such as ConcurrentHashMap.size() and ConcurrentHashMap.isEmpty() are allowed to return an approximate result for performance reasons. Code should avoid relying on these return values when exact results are required.

Risk Assessment

Failure to ensure the atomicity of two or more operations that must be performed as a single atomic operation can result in race conditions in multithreaded applications.

Automated Detection

Some static analysis tools are capable of detecting violations of this rule.

Related Guidelines

Bibliography

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