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, it is necessary to implement a consistent locking policy by either using intrinsic synchronization or the 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; however, this is not the case. 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. See CON01-J. Ensure that compound operations on shared variables are atomic for more information.
CON30-J. Do not use method chaining implementations in a multithreaded environment 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 is used to iterate over Arraylist
instead of an iterator 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 collection methods add()
and toArray()
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 also 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 addIPAddress(InetAddress address) { synchronized (ips) { ips.add(address); } } public void addAndPrintIPAddresses(InetAddress address) { synchronized (ips) { addIPAddress(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 [CON31-J. Avoid client-side locking when using classes that do not commit to their locking strategy] for more information.
This code does not violate CON40-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
which 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, value + 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, value + 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. The guideline CON40-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. Refer to 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 Goetz et al. [[Goetz 06]] section 5.2.1. ConcurrentHashMap:
ConcurrentHashMap
, along with the other concurrent collections, further improve on the synchronized collection classes by providing iterators that do not throwConcurrentModificationException
, as a result eliminating the need to lock the collection during iteration. The iterators returned byConcurrentHashMap
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 that atomicity of two or more operations that need to be performed as a single atomic operation can result in race conditions in multithreaded applications.
Rule |
Severity |
Likelihood |
Remediation Cost |
Priority |
Level |
---|---|---|---|---|---|
CON07- J |
low |
probable |
medium |
P4 |
L3 |
Automated Detection
TODO
Related Vulnerabilities
Search for vulnerabilities resulting from the violation of this rule 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"
VOID CON06-J. Do not defer a thread that is holding a lock 11. Concurrency (CON)