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Comment: REM Cost Reform

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 and |= [JLS 2005]. Compound operations on shared variables must be performed atomically to prevent data races andrace 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 booleanshared _Bool flag variable and provides a toggle_flag() method that negates the current value of flag.:
Code Block
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langc
#include <stdbool.h>
 
static bool flag = false;
 
void toggle_flag(void) {
  flag = !flag;
}
 
bool get_flag(void) {
  return 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 because the value of of flag is is read, negated, and written back.

Consider, for example, two threads that call toggle_flag(). 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:

Time

flag=

Thread

Action

1

true

t 1

reads

Reads the current value of flag, true, into a

temporary variable

cache

2

true

t 2

reads

Reads the current value of flag, (still) true, into a

temporary variable

different cache

3

true

t 1

toggles

Toggles the temporary variable in the cache to false

4

true

t 2

toggles

Toggles the temporary variable in the different cache to false

5

false

t 1

writes

Writes the

temporary

cache variable's value to flag

6

false

t 2

writes

Writes the

temporary

different cache variable's value to flag

As a result, the effect of the call by t 2 is not reflected in flag; the program behaves as if toggle_flag() was called only once, not twice.

Noncompliant Code Example (Bitwise Negation)

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 data race exists because ^= is a nonatomic compound operation.

Noncompliant Code Example (Volatile)

Declaring flag volatile also fails to solve the problem:

 

final class Flag {
  private volatile boolean flag = true;
 
  public void toggle() {  // Unsafe
    flag ^= true;
  }
 
  public boolean getFlag() { // Safe
    return flag;
  }
}

 

This code remains unsuitable for multithreaded use because declaring a variable volatile fails to guarantee the atomicity of compound operations on the variable.

Compliant Solution (Synchronization)

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;
  }
}

Compliant Solution (Mutex)

This compliant solution restricts access to flag under a mutex lock:

Code Block
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langc
#include <threads.h>
#include <stdbool.h>
 
static bool flag = false;
mtx_t flag_mutex;

/* Initialize flag_mutex */
bool init_mutex(int type) {
  /* Check mutex type */
  if (thrd_success != mtx_init(&flag_mutex, type)) {
    return false;  /* Report error */
  }
  return true;
}
 
void toggle_flag(void) {
  if (thrd_success != mtx_lock(&flag_mutex)) {
    /* Handle error */
  }
  flag = !flag;
  if (thrd_success != mtx_unlock(&flag_mutex)) {
    /* Handle error */
  }
}
 
bool get_flag(void) {
  bool temp_flag;
  if (thrd_success != mtx_lock(&flag_mutex)) {
    /* Handle error */
  }
  temp_flag = flag;
  if (thrd_success != mtx_unlock(&flag_mutex)) {
    /* Handle error */
  }
  return temp_flag;
}
 

This solution guards reads and writes to the the flag field field with a lock on the instance, that is, this. Furthermore, synchronization flag_mutex. This lock ensures that changes to flag are visible to all threads. Now, only two execution orders are possible, one of which is shown in the following scenario. In one execution order, t1 obtains the mutex and completes the operation before t 2 can acquire the mutex, as shown here:

Time

flag=

Thread

Action

1

true

t 1

reads

Reads the current value of flag, true, into a

temporary

cache variable

2

true

t 1

toggles

Toggles the

temporary

cache variable to false

3

false

t 1

writes

Writes the

temporary

cache variable's value to flag

4

false

t 2

reads

Reads the current value of flag, false, into a

temporary

different cache variable

5

false

t 2

toggles

Toggles the

temporary

different cache variable to true

6

true

t 2

writes

Writes the

temporary

different cache variable's value to flag

The second other execution order involves the same operations, but is similar, except that t 2 starts and finishes before t 1
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. 

Compliant Solution (

Volatile-Read, Synchronized-Write)

atomic_compare_exchange_weak() )

This compliant solution uses atomic variables and a compare-and-exchange operation to guarantee that the correct value is stored in flag. All updates are visible to other threads.

Code Block
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langc
#include <stdatomic.h>
#include <stdbool.h>
 
static atomic_bool flag;

void init_flag(void) {
  atomic_init(&flag, false);
}
void toggle_flag(void) {
  bool old_flag = atomic_load(&flag);
  bool new_flag;
  do {
    new_flag = !old_flag;
  } while (!atomic_compare_exchange_weak(&flag, &old_flag, new_flag));
}
  
bool get_flag(void) {
  return atomic_load(&flag);
}

An alternative solution is to use the atomic_flag data type for managing Boolean values atomically

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 thegetFlag() method is an atomic operation and the volatile qualification assures visibility. The toggle() method still requires synchronization because it performs a nonatomic 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.

Profiling the application can determine the suitability of read-write locks.

Compliant Solution (AtomicBoolean)

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;
  }
}

 

The flag variable is updated using the compareAndSet() method of the AtomicBoolean class. All updates are visible to other threads.

Noncompliant Code Example (Addition of Primitives)

In this noncompliant code example, multiple threads can invoke the setValuesset_values() method to set the a and b fields. Because this class code fails to test for integer overflow, users of the Adder class must this code must also ensure that the arguments to the setValuesset_values() method can be added without overflow . (See rule NUM00-J. Detect or prevent integer see INT32-C. Ensure that operations on signed integers do not result in 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;
  }
}

 

).

Code Block
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langc
static int a;
static int b;
 
int get_sum(void) {
  return a + b;
}
 
void set_values(int new_a, int new_b) {
  a = new_a;
  b = new_b;
}

The  get_sumThe getSum() method contains a race condition. For example, when a and b currently have the values 0 and Integer.MAX_VALUE and INT_MAX, respectively, and one thread calls getSumget_sum() while another calls setValues(Integer.MAX_VALUEset_values(INT_MAX, 0), the getSumget_sum() method might return either 0 or Integer.INT_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, INT_MAX but before it has set the value of b to 0.

Note that declaring the variables as volatile fails to resolve the issue because these compound operations involve reads and writes of multiple variables.


Noncompliant Code Example (Addition of Atomic Integers)

In this noncompliant code example,  a and  and b are 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);
  }
}


Code Block
bgColor#FFCCCC
langc
#include <stdatomic.h>

static atomic_int a;
static atomic_int b;

void init_ab(void) {
  atomic_init(&a, 0);
  atomic_init(&b, 0);
}

int get_sum(void) {
  return atomic_load(&a) + atomic_load(&b);
}
 
void set_values(int new_a, int new_b) {
  atomic_store(&a, new_a);
  atomic_store(&b, new_b);
}
 


The simple replacement of the two int fields with atomic integers fails to eliminate the race condition in the sum because the compound operation a.get() + b.get() is still non-atomic. While a sum of some value of a and some value of b will be returned, there is no guarantee that this value represents the sum of the values of a and b at any particular moment.

Compliant Solution (_Atomic struct)

This compliant solution uses an atomic struct, which guarantees that both numbers are read and written together.

Code Block
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langc
#include <stdatomic.h>
  
static _Atomic struct ab_s {
  int a, b;
} ab;
 
void init_ab(void) {
  struct ab_s new_ab = {0, 0};
  atomic_init(&ab, new_ab);
}
 
int get_sum(void) {
  struct ab_s new_ab = atomic_load(&ab);
  return new_ab.a + new_ab.b;
}
 
void set_values(int new_a, int new_b) {
  struct ab_s new_ab = {new_a, new_b};
  atomic_store(&ab, new_ab);
}

On most modern platforms, this will compile to be lock-free.

Compliant Solution (

Addition

Mutex)

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;
  }
}

 

protects the set_values() and get_sum() methods with a mutex to ensure atomicity:

Code Block
bgColor#ccccff
langc
#include <threads.h>
#include <stdbool.h>

static int a;
static int b;
mtx_t flag_mutex;

/* Initialize everything */
bool init_all(int type) {
  /* Check mutex type */
  a = 0;
  b = 0;
  if (thrd_success != mtx_init(&flag_mutex, type)) {
    return false;  /* Report error */
  }
  return true;
}
 
int get_sum(void) {
  if (thrd_success != mtx_lock(&flag_mutex)) {
    /* Handle error */
  }
  int sum = a + b;
  if (thrd_success != mtx_unlock(&flag_mutex)) {
    /* Handle error */
  }
  return sum;
}
 
void set_values(int new_a, int new_b) {
  if (thrd_success != mtx_lock(&flag_mutex)) {
    /* Handle error */
  }
  a = new_a;
  b = new_b;
  if (thrd_success != mtx_unlock(&flag_mutex)) {
    /* Handle error */
  }
}

Thanks to the mutex, it is now possible to add overflow checking to the get_sum()  function 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 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.

Rule

Severity

Likelihood

Remediation Cost

Detectable

Repairable

Priority

Level

VNA02

CON07-

J

C

Medium

medium

Probable

probable

Yes

medium

No

P8

L2

Automated Detection

Some available static analysis tools can detect the instances of nonatomic 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.

Related Guidelines

Tool

Version

Checker

Description

CodeSonar
Include Page
CodeSonar_V
CodeSonar_V

CONCURRENCY.DATARACE

Data Race

Related Guidelines

CERT Oracle Secure Coding Standard for JavaVNA02-J. Ensure that compound operations on shared variables are atomic

MITRE CWE

CWE-366,

MITRE CWE

CWE-667. Improper locking

 

CWE-413. Improper resource locking

 

CWE-366.

Race condition within a thread

 

CWE-413, Improper resource locking
CWE-567

.

, Unsynchronized access to shared data in a multithreaded context
CWE-667, Improper locking

Bibliography

[

API 2006]

Class AtomicInteger

[Bloch 2008]

Item 66. Synchronize access to shared mutable data

[Goetz 2006]

2.3, Locking

[JLS 2005]

Chapter 17, Threads and Locks

 

§17.4.5, Happens-Before Order

 

§17.4.3, Programs and Program Order

 

§17.4.8, Executions and Causality Requirements

[Lea 2000]

Section 2.2.7, The Java Memory Model

 

Section 2.1.1.1, Objects and Locks

[Tutorials 2008]

Java Concurrency Tutorial

ISO/IEC 14882:2011]

Subclause 7.17, "Atomics"



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