VNA03-J. Do not assume that a group of calls to independently atomic methods is atomic

A consistent locking policy guarantees that multiple threads cannot simultaneously access or modify shared data. If two or more operations need to 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 individually atomic operations require no additional locking. Similarly, programmers may incorrectly assume that using a thread-safe Collection does not require explicit synchronization to preserve an invariant that involves the collection's elements. A thread-safe class can only guarantee atomicity of its individual methods. A grouping of calls to such methods requires additional synchronization.

Consider, for example, a scenario where the standard thread-safe API does not provide a single method to both find a particular person's record in a Hashtable and update the corresponding payroll information. In such cases, the two method invocations must be performed atomically.

Enumerations and iterators also require explicit synchronization on the collection object (client-side locking) or a private final lock object.

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

CON04-J. Ensure that calls to chained methods are atomic describes a specialized case of this guideline.

Noncompliant Code Example (AtomicReference)

This noncompliant code example wraps BigInteger objects 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());
  }
}

An AtomicReference is an object reference that can be updated atomically. However, operations that combine more than one atomic reference are not atomic. In this noncompliant code example, one thread may call update() while a second thread may call add(). This might cause the add() method to add the new value of first to the old value of second, yielding an erroneous result.

Compliant Solution (Method Synchronization)

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

final class Adder {
  // ...

  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 Collections.synchronizedList is used as a synchronization wrapper for ArrayList. An array, rather than an iterator, is used to iterate over 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 they are called in succession (for example in the addAndPrintIPAddresses() method), there are no guarantees that the combined operation is atomic. A race condition exists in the addAndPrintIPAddresses() method 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 then expected.

Compliant Solution (Synchronized Block)

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.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 ...
  }
}

This technique is also called client-side locking [[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 CON34-J. Avoid client-side locking when using classes that do not commit to their locking strategy for more information.

The addressCopy array holds a copy of the IP addresses and can be safely operated upon outside the synchronized block. This code does not violate CON11-J. Do not synchronize on a collection view if the backing collection is accessible, because while it does synchronize on a collection view (the synchronizedList), the backing collection is inaccessible, and therefore cannot be modified by any code.

Noncompliant Code Example (synchronizedMap)

This noncompliant code example defines a class KeyedCounter that is not thread-safe. Although the HashMap is wrapped in a synchronizedMap, the overall increment operation is not atomic [[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);
  }
}

Compliant Solution (synchronization)

To ensure atomicity, this compliant solution uses 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 does not use Collections.synchronizedMap() because locking on the unsynchronized map provides sufficient thread-safety for this application. CON11-J. Do not synchronize on a collection view if the backing collection is accessible provides more information about synchronizing on synchronizedMap objects.

To prevent overflow, the caller must ensure that the increment() method is called no more than Integer.MAX_VALUE times for any key. See INT00-J. Perform explicit range checking to ensure integer operations do not overflow for more information.

Compliant Solution (ConcurrentHashMap)

The previous compliant solution is safe for multithreaded use, however, it does not scale well because of excessive synchronization, which can lead to contention and deadlock.

The 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 09]].

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) {
      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 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 size() and isEmpty() are allowed to return an approximate result for performance reasons. Code should not rely on these return values for deriving exact results.

Risk Assessment

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

Automated Detection

TODO

Related Vulnerabilities

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

References

[[API 06]]
[[JavaThreads 04]] Section 8.2, "Synchronization and Collection Classes"
[[Goetz 06]] Section 4.4.1, "Client-side Locking," Section 5.2.1, "ConcurrentHashMap"
[[Lee 09]] "Map & Compound Operation"

      12. Locking (LCK)