The Java language allows platforms to make use of available floating-point hardware that may can provide extended floating-point support with mantissas and/or exponents that contain more bits than the standard Java primitive type double
, thus enabling those platforms to (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 may 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 JLSSection 15, §15.4, "FP-Strict strict Expressions": "the net effect [JLS 2005]:
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 "When it is important to obtain 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
, thus guaranteeing that the result of the computations will match exactly across all JVMs and platforms.
Use of the strict_fp
modifier lacks impact 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 the strict_fp
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 may 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:
UsageStrictness | BehaviorApplies to |
---|---|
Class | All code in the class including (instance, variable, static initializers), and code in nested classes |
Method | All code within the method is subject to strictness constraints |
Interface | All code in the any class that implements the interface is also strict |
An expression is FP-strict when any of the containing classes, methods, or interfaces is declared to be a strictfp
. Constant expressions containing floating-point operations are also evaluated strictly. All compile-time constant expressions are by default , strictfp
FP-strict.
The strict behavior cannot be Strict behavior is not inherited by a subclass that extends a strictfp
FP-strict superclass. An overriding method may 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 being multiplied by 1.1 and reduced back by dividing by 1.1, according to the evaluation order. JVM implementations are not required to report an overflow resulting from the initial multiplication, although they 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
.
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.
Code Block | ||
---|---|---|
| ||
class StrictfpExample { 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
To be compliantFor 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 design. This code snippet behavior. The calculation in this compliant solution is guaranteed to return positive INFINITY
produce infinity
because of the intermediate overflow condition, regardless of what floating-point support is provided by the platform.
Code Block | ||
---|---|---|
| ||
strictfp class StrictfpExample { 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
Native floating-point hardware provides greater 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.
Code Block | ||
---|---|---|
| ||
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();
}
}
|
Magnitude loss would also 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
is identical to the value stored in this.d
, even on platforms that support extended range exponents.
Code Block | ||
---|---|---|
| ||
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
NUM06-J-EX0: This rule applies only to calculations that require consistent floating-point results on all platforms. Applications that lack this requirement need not comply.
Risk Assessment
Failure to use the strictfp
modifier can result in platform nonportable, implementation-defined behavior with respect to the accuracy behavior of floating-point operations.
Guideline Rule | Severity | Likelihood | Remediation Cost | Priority | Level |
---|---|---|---|---|---|
FLP04NUM06-J | low | unlikely | high | P1 | L3 |
Automated Detection
TODO
Related Vulnerabilities
Search for vulnerabilities resulting from the violation of this guideline on the CERT website.
Bibliography
Wiki Markup |
---|
\[[Darwin 2004|AA. Bibliography#Darwin 04]\] Ensuring the Accuracy of Floating-Point Numbers
\[[JLS 2005|AA. Bibliography#JLS 05]\] 15.4 FP-strict Expressions
\[[JPL 2005|AA. Bibliography#JPL 05]\] 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 |
Related Guidelines
FLP00-C. Understand the limitations of floating-point numbers | |
VOID FLP00-CPP. Understand the limitations of floating-point numbers |
Bibliography
Ensuring the Accuracy of Floating-Point Numbers | |
[JLS 2005] | |
[JPL 2006] | 9.1.3, Strict and Non-Strict Floating-Point Arithmetic |
Making Deep Copies of Objects, Using strictfp, and Optimizing String Performance |
...
FLP03-J. Range check before casting floating point numbers to narrower types 07. Floating Point (FLP) FLP05-J. Do not attempt comparisons with NaN