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The Java language allows platforms to use available floating-point hardware that can provide extended floating-point support with exponents that contain more bits than the standard Java primitive type double (in the absence of the strictfp modifier). Consequently, these platforms can represent a superset of the values that can be represented by the standard floating-point types. Floating-point computations on such platforms can produce different results than would be obtained if the floating-point computations were restricted to the standard representations of float and double. According to the JLS, Section 15§15.4, "FP-Strict strict Expressions" [JLS 2005]:

the The net effect [of non-fp-strict evaluation], roughly speaking, is that a calculation might produce "the correct answer" in situations where exclusive use of the float value set or double value set might result in overflow or underflow.

Programs that require consistent results from floating-point operations across different JVMs and platforms must use the strictfp modifier. This modifier requires the JVM and the platform to behave as though all floating-point computations were performed using values limited to those representable that can be represented by a standard Java float or double, consequently guaranteeing that the result of the computations will match exactly across all JVMs and platforms.

Use of Using the strictfp modifier leaves execution unchanged on platforms that lack platform-specific, extended floating-point behaviorsupport. It can have substantial impact, however, on both the efficiency and the result resulting values of floating-point computations when executing on platforms that implement platform-specific floating point behaviorprovide extended floating-point support. On these platforms, use of using the strictfp modifier increases the likelihood that intermediate operations will overflow or underflow because it restricts the representable range and precision of intermediate values that can be represented; it can also reduce computational efficiency. These issues are unavoidable when portability is the main concern.

The strictfp modifier can be used with a class, method, or interface:

An expression is FP-strict when any of the containing classes, methods, or interfaces is declared to be strictfp. Constant expressions containing floating-point operations are also evaluated strictly. All compile-time constant expressions are by default , strictfpFP-strict.

Strict behavior cannot be is not inherited by a subclass that extends a strictfp FP-strict superclass. An overriding method can independently choose to be strictfp FP-strict when the overridden method is not, or vice versa.

Noncompliant Code Example

This noncompliant code example does not mandate strictfp FP-strict computation. Double.MAX_VALUE is multiplied by 1.1 and reduced back by dividing by 1.1, according to the evaluation order. If Double.MAX_VALUE is the maximum value permissible by the platform, the calculation will yield the result infinity.

However, if the platform provides extended floating-point support, this program might print a numeric result roughly equivalent to Double.MAX_VALUE.

JVM implementations are not required to report an overflow resulting from the initial multiplication, although they can The JVM may choose to treat this case as strictfp. The ability to use extended exponent ranges to represent intermediate values is implementation definedFP-strict; if it does so, overflow occurs. Because the expression is not FP-strict, an implementation may use an extended exponent range to represent intermediate results.

class Example {
  public static void main(String[] args) {
    double d = Double.MAX_VALUE;
    System.out.println("This value \"" + ((d * 1.1) / 1.1) + "\" cannot be represented as double.");
  }
}

Compliant Solution

For maximum portability, use the strictfp modifier within an expression (class, method, or interface) to guarantee that intermediate results do not vary because of implementation-defined compiler optimizations or by designbehavior. The calculation in this compliant solution is guaranteed to produce infinity because of the intermediate overflow condition, regardless of what floating-point support is provided by the platform.

strictfp class Example {
  public static void main(String[] args) {
    double d = Double.MAX_VALUE;
    System.out.println("This value \"" + ((d * 1.1) / 1.1) + "\" cannot be represented as double.");
  }
}

Noncompliant Code Example

On platforms whose native Native floating-point hardware provides greater precision range than double. On these platforms, the JIT is permitted to use floating-point registers to hold values of type float or type double (in the absence of the strictfp modifier), even though the registers support values with greater exponent range than that of the primitive types. Consequently, conversion from float to double can cause an effective loss of magnitude.

class Example {
  double d = 0.0;

  public void example() {
    float f = Float.MAX_VALUE;
    float g = Float.MAX_VALUE;
    this.d = f * g;
    System.out.println("d (" + this.d + ") might not be equal to " +
                       (f * g));
  }

  public static void main(String[] args) {
    Example ex = new Example();
    ex.example();
  }
}

The lost magnitude Magnitude loss would also have been lost occur if the value were stored to memory , – for example, to a field of type float.

Compliant Solution

This compliant solution uses the strictfp keyword to require exact conformance with standard Java floating-point. Consequently, the intermediate value of both computations of f * g will be is identical to the value stored in this.d, even on platforms that support extended range exponents.

strictfp class Example {
  double d = 0.0;

  public void example() {
    float f = Float.MAX_VALUE;
    float g = Float.MAX_VALUE;
    this.d = f * g;
    System.out.println("d (" + this.d + ") might not be equal to " +
                       (f * g));
  }

  public static void main(String[] args) {
    Example ex = new Example();
    ex.example();
  }
}

Exceptions

NUM09NUM06-J-EX1EX0: This guideline rule applies only to calculations that require consistent floating-point results on all platforms. Applications that lack this requirement need not comply.

NUM09-EX2: The strictfp modifier may be omitted when competent numerical analysis demonstrates that the computed values will meet all accuracy and behavioral requirements that are appropriate to the application. Note that "competent numerical analysis" generally requires a specialized professional numerical analyst; lesser levels of rigor fail to qualify for this exception.

Risk Assessment

Failure to use the strictfp modifier can result in nonportable, implementation-defined behavior with respect to the behavior of floating-point operations.

Automated Detection

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Related

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Guidelines

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

Related Guidelines

Bibliography

\[[Darwin 2004|AA. Bibliography#Darwin 04]\] Ensuring the Accuracy of Floating-Point Numbers
\[[JLS 2005|AA. Bibliography#JLS 05]\] [Section 15.4|http://java.sun.com/docs/books/jls/third_edition/html/expressions.html#15.4], "FP-strict Expressions"
\[[JPL 2006|AA. Bibliography#JPL 06]\] 9.1.3. Strict and Non-Strict Floating-Point Arithmetic
\[[McCluskey 2001|AA. Bibliography#McCluskey 01]\] Making Deep Copies of Objects, Using strictfp, and Optimizing String Performance

Bibliography

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Image Added      Image Added      Image AddedImage Removed      03. Floating Point (FLP)      NUM10-J. Do not attempt comparisons with NaN