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, §15.4, "FP-strict Expressions" [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 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 that can be represented by a standard Java float
or double
, guaranteeing that the result of the computations will match exactly across all JVMs and platforms.
Using the strictfp
modifier leaves execution unchanged on platforms that lack platform-specific, extended floating-point support. It can have substantial impact, however, on both the efficiency and the resulting values of floating-point computations when executing on platforms that provide extended floating-point support. On these platforms, using the strictfp
modifier increases the likelihood that intermediate operations will overflow or underflow because it restricts the range 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:
Usage |
Applies to |
---|---|
Class |
All code in the class (instance, variable, static initializers), and code in nested classes |
Method |
All code within the method |
Interface |
All code in any class that implements the 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 FP-strict.
Strict behavior is not inherited by a subclass that extends a FP-strict superclass. An overriding method can independently choose to be FP-strict when the overridden method is not, or vice versa.
Noncompliant Code Example
This noncompliant code example does not mandate 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
.
The JVM may choose to treat this case as FP-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 behavior. 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
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.
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.
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-EX0: This rule applies only to calculations that require consistent floating-point results on all platforms. Applications that lack this requirement need not comply.
NUM06-EX1: The strictfp
modifier may be omitted when suitable numerical analysis demonstrates that the computed values meet all accuracy and behavioral requirements appropriate to the application.
Risk Assessment
Failure to use the strictfp
modifier can result in nonportable, implementation-defined behavior with respect to the behavior of floating-point operations.
Rule |
Severity |
Likelihood |
Remediation Cost |
Priority |
Level |
---|---|---|---|---|---|
NUM06-J |
low |
unlikely |
high |
P1 |
L3 |
Automated Detection
Sound automated detection of violations of this rule is not feasible in the general case.
Related Guidelines
FLP00-C. Understand the limitations of floating point numbers |
|
FLP00-CPP. Understand the limitations of floating point numbers |
Bibliography
<ac:structured-macro ac:name="unmigrated-wiki-markup" ac:schema-version="1" ac:macro-id="01a9b9cc-361d-4e59-aba2-e6d53c84c078"><ac:plain-text-body><![CDATA[ |
[[Darwin 2004 |
AA. Bibliography#Darwin 04]] |
Ensuring the Accuracy of Floating-Point Numbers |
]]></ac:plain-text-body></ac:structured-macro> |
|
<ac:structured-macro ac:name="unmigrated-wiki-markup" ac:schema-version="1" ac:macro-id="a8ef73d1-7979-4fc7-8312-1b1859db7626"><ac:plain-text-body><![CDATA[ |
[[JLS 2005 |
AA. Bibliography#JLS 05]] |
[§15.4, FP-strict Expressions |
http://java.sun.com/docs/books/jls/third_edition/html/expressions.html#15.4] |
]]></ac:plain-text-body></ac:structured-macro> |
<ac:structured-macro ac:name="unmigrated-wiki-markup" ac:schema-version="1" ac:macro-id="41b14d0e-940f-49fe-9d97-417a26067507"><ac:plain-text-body><![CDATA[ |
[[JPL 2006 |
AA. Bibliography#JPL 06]] |
9.1.3, Strict and Non-Strict Floating-Point Arithmetic |
]]></ac:plain-text-body></ac:structured-macro> |
|
<ac:structured-macro ac:name="unmigrated-wiki-markup" ac:schema-version="1" ac:macro-id="0affc721-ae0f-43d9-bb12-dca90c14d9b9"><ac:plain-text-body><![CDATA[ |
[[McCluskey 2001 |
AA. Bibliography#McCluskey 01]] |
Making Deep Copies of Objects, Using strictfp, and Optimizing String Performance |
]]></ac:plain-text-body></ac:structured-macro> |
NUM05-J. Do not use denormalized numbers 03. Numeric Types and Operations (NUM)