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Thread-safety A consistent locking policy guarantees that no two multiple threads can cannot simultaneously access or modify some shared data. However, if When two or more operations need to be performed safely, it becomes necessary to enforce atomicity. It is possible for two threads to read some shared value, independently perform operations on it and induce a race condition while storing the final result. Programmers usually assume that a thread-safe Collection does not require explicit synchronization which can be a misleading practice. It follows that a thread-safe Collection may not ensure program correctness.

Noncompliant code Example

This noncompliant example is comprised of an ArrayList collection which is non-thread-safe by default. There is however, a way around this drawback. Most thread-unsafe classes have a synchronized thread-safe version, synchronizedList being a good substitute for ArrayList. One pitfall described in the coming lines, remains to be addressed even when the particular Collection offers thread-safety benefits.

The operations within the {{run()}} method are non-atomic. That is, it is possible that the first thread will operate on data that it does not expect. The superfluous data may be fed in by other threads while the first thread has not finished processing. Conversely, since the {{toArray()}} method produces a copy of the parameter, it is possible that the first thread operates on stale data \[[JavaThreads 04|AA. Java References#JavaThreads 04]\]. The code's output with varying array lengths signifies a race condition. Such omissions can be pernicious in methods that use complex formulas.    

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.

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

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

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

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

Noncompliant Code Example (AtomicReference)

This noncompliant code example wraps references to 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());
  }
}

AtomicReference is an object reference that can be updated atomically. However, operations that combine more than one atomic reference are non-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 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 = 
     

class RaceCollection implements Runnable {
  private List<InetAddress> ips = Collections.synchronizedList(new ArrayList<InetAddress>());
  
  public void addIPAddressaddAndPrintIPAddresses(InetAddress iaaddress) {
    synchronizedips.add(ipsaddress) {;
    InetAddress[] addressCopy = 
        (InetAddress[]) ips.add(iatoArray(new InetAddress[0]);
    // Iterate through array addressCopy ...
  }
}

Individually, the add() and toArray() collection methods are atomic. However, when called in succession (as shown in the addAndPrintIPAddresses() method), there is no guarantee that the combined operation is atomic. The addAndPrintIPAddresses() method contains 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 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 removeIPAddressaddAndPrintIPAddresses(InetAddress iaaddress) {
    synchronized (ips) {
      ips.removeadd(iaaddress);
     }
  }

  public void nonAtomic() throws InterruptedException {
    InetAddress[] ia;   

    synchronized(ips InetAddress[] addressCopy = 
          (InetAddress[]) ips.toArray(new InetAddress[0]);
      // Iterate through array addressCopy ...
    }
  }
}

This technique is also called client-side locking [Goetz 2006] 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 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 LCK04-J. Do not synchronize on a collection view if the backing collection is accessible because, although it synchronizes on a collection view (the synchronizedList result), the backing collection is inaccessible and consequently cannot be modified by any code.

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].

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 iaoldValue = (InetAddress[]) ips.toArray(new InetAddress[0]);     old == null) ? 0 : old.intValue();
    if (oldValue == Integer.MAX_VALUE) {
    }
  throw new ArithmeticException("Out of range");
    }
    Systemmap.out.printlnput("Number of IPs: "key, oldValue + ia.length1); 
  }

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

Compliant Solution (Synchronization)

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 public void run() {
  private  try {final Map<String, Integer> map =
      addIPAddress(InetAddress.getLocalHostnew HashMap<String, Integer>());
  private final Object lock = new nonAtomicObject();

  public void increment(String key) {
   } catchsynchronized (UnknownHostException elock) { }
      Integer old = map.get(key);
      catchint oldValue = (InterruptedException eold == null) { }		
  }? 0 : old.intValue();
  
  public static voidif main(String[] args(oldValue == Integer.MAX_VALUE) {
    RaceCollection   rc1 =throw new RaceCollection();ArithmeticException("Out of range");
      }
    for(int i=0;i<2;i++)  map.put(key, oldValue + 1);
      new Thread(rc1).start();	  	  }
  }

  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. 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 does not scale because of excessive synchronization, which can lead to decreased performance.

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 2009].

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 solutionTo eliminate the race condition, ensure atomicity. This can be achieved by including all statements that use the array list within the synchronized block.

synchronized(ips)final class KeyedCounter {
  private final ConcurrentMap<String, AtomicInteger> iamap =
      (InetAddress[]) ips.toArray(new InetAddress[0]);   new ConcurrentHashMap<String, AtomicInteger>();
  private final Object lock = new Object();

  public void increment(String key) {
    AtomicInteger value = new AtomicInteger();
  System.out.println("Number of IPs:AtomicInteger "old += ia.lengthmap.putIfAbsent(key, value); 
}

Note that this advice applies to all {{Collection}} classes including the thread-safe hash tables. Enumerations of the objects of a {{Collection}} and iterators also require explicit synchronization on the {{Collection}} object or any single lock object. Although expensive, {{CopyOnWriteArrayList}} and {{CopyOnWriteArraySet}} classes may also be used to create copies of the core {{Collection}} so that iterators do not fail with a runtime exception when some data in the {{Collection}} is modified. \[[JavaThreads 04|AA. Java References#JavaThreads 04]\]    

Risk Assessment

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

    synchronized (lock) {
      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 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 applicationsNon-atomic code can induce race conditions and affect program correctness.

Automated Detection

TODO

Related Vulnerabilities

Search for vulnerabilities resulting from the violation of this rule on the CERT website.

References

\[[API 06|AA. Java References#API 06]\] Class Vector, Class WeakReference
\[[JavaThreads 04|AA. Java References#JavaThreads 04]\] 8.2 "Synchronization and Collection Classes"

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

Related Guidelines

Bibliography

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Image Added Image Added Image AddedMSC00-J. Eliminate class initialization cycles      49. Miscellaneous (MSC)      MSC02-J. Be aware of the JVM Tool Interface