The following 19 specific conversions on primitive types are called the widening primitive conversions:
byte
toshort
,int
,long
,float
, ordouble
short
toint
,long
,float
, ordouble
char
toint
,long
,float
, ordouble
int
tolong
,float
, ordouble
long
tofloat
ordouble
float
todouble
Conversion from int
or long
to float
, or from long
to double
may can lead to loss of precision (loss of least significant bits). In this casethese cases, the resulting floating-point value is a rounded version of the integer value, using IEEE 754 round-to-nearest mode. Despite this loss of precision, the The Java Language Specification (JLS) requires that the conversion and rounding occur silently; , that is, without any runtime exception . See (see the JLS, Section 5 §5.1.2, "Widening Primitive Conversion" [JLS 2015], for more information. ). Conversions from integral types smaller than int
to a floating-point type and conversions from int
to double
can never result in a loss of precision. Consequently, programs must ensure that conversions from an int
or long
to a floating-point type or from long
to double
do not result in a loss of required precision.
Note that conversions from float
to double
can also lose information about the overall magnitude of the converted value (see NUM53Note that conversions from float
to double
can also lose information about the overall magnitude of the converted value. Specifically, on platforms whose native floating point hardware provides greater precision than double
, the JIT is permitted to use floating point registers to hold values of type float
(or type double
), even though the registers support values with greater mantissa and/or exponent range. Consequently, conversion from float
to double
can cause an effective loss of precision, of magnitude, or of both. However, the lost precision or magnitude would also have been lost if the value were stored to memory, for example to a field of type float
. See guideline FLP04-J. Use the strictfp modifier for floating-point calculation consistency across platforms for additional information).
Noncompliant Code Example
In this noncompliant code example, two identical large integer literals are passed as arguments to the subFloatFromInt()
method. The second argument is coerced to float
, cast back to int
, and subtracted from a value of type int
. The result is returned as a value of type int
.
This method may could have unexpected results because of the loss of precision. Values In FP-strict mode, values of type float
have 23 mantissa bits, a sign bit, and an 8-bit exponent (see NUM53-J. Use the strictfp modifier for floating-point calculation consistency across platforms for more information about FP-strict mode). The exponent allows type float
to represent a larger range than that of type int
. However, the 23-bit mantissa means that float
supports exact representation only of integers whose representation fits within 23 bits; float
supports only approximate representation of integers outside that range.
Code Block | ||
---|---|---|
| ||
strictfp class WideSample { public static int subFloatFromInt(int op1, float op2) { return op1 - (int)op2; } public static void main(String[] args) { int result = subFloatFromInt(1234567890, 1234567890); // This prints -46, and not 0, as may be expected System.out.println(result); } } |
Note that conversions from long
to either float
or double
can lead to similar loss of precision.
Compliant Solution (ArithmeticException
)
This compliant solution range checks the argument of the integer argument (op1
) to ensure it can be represented as a value of type float
without a loss of precision.:
Code Block | ||
---|---|---|
| ||
strictfp class WideSample { public static int subFloatFromInt(int op1, float op2) throws ArithmeticException { // The significand can store at most 23 bits if ((op1op2 > 0x007fffff) || (op1op2 < -0x800000)) { throw new ArithmeticException("Insufficient precision"); } return op1 - (int)op2; } public static void main(String[] args) { int result = subFloatFromInt(1234567890, 1234567890); System.out.println(result); } } |
In this example, the subFloatFromInt()
method throws java.lang.ArithmeticException
. This approach should general approach, with appropriate range checks, can be used for conversions from long
to either float
or double
.
Compliant Solution (
...
Wider Type)
This compliant solution accepts an argument of type double
instead of an argument of type float
. Values In FP-strict mode, values of type double
have 52 mantissa bits, a sign bit, and an 11-bit exponent. Consequently, integer Integer values of type int
and narrower can be converted to double
without a loss of precision.
Code Block | ||
---|---|---|
| ||
strictfp class WideSample { public static int subDoubleFromInt(int op1, double op2) { return op1 - (int)op2; } public static void main(String[] args) { int result = subDoubleFromInt(1234567890, 1234567890); // Works as expected System.out.println(result); } } |
Note that this compliant solution is insufficient cannot be used when the primitive integers are of type long
, because Java lacks a primitive floating-point type whose mantissa can represent the full range of a long
.
Exceptions
NUM13-J-EX0: Conversion from integral types to floating-point types without a range check is permitted when suitable numerical analysis demonstrates that the loss of the least significant bits of precision is acceptable.
Risk Assessment
Converting integer values to floating-point types whose mantissa has fewer bits than the original integer value will lose precisioncan result in a rounding error.
Rule | Severity | Likelihood | Remediation Cost | Priority | Level |
---|
NUM13-J |
Low |
Unlikely |
Medium | P2 | L3 |
Automated Detection
Automatic detection of casts that can lose precision is straightforward. Sound determination of whether those casts correctly reflect the intent of the programmer is infeasible in the general case. Heuristic warnings could be useful.
Related Vulnerabilities
Search for vulnerabilities resulting from the violation of this guideline on the CERT website.
Related Guidelines
C Secure Coding Standard: FLP36-C. Beware of precision loss when converting integral types to floating point
C++ Secure Coding Standard: FLP36-CPP. Beware of precision loss when converting integral types to floating point
Bibliography
Wiki Markup |
---|
\[[JLS 2005|AA. Bibliography#JLS 05]\] [Section 5.1.2|http://java.sun.com/docs/books/jls/third_edition/html/conversions.html#5.1.2], "Widening Primitive Conversion" |
Tool | Version | Checker | Description | ||||||
---|---|---|---|---|---|---|---|---|---|
CodeSonar |
| JAVA.CAST.FTRUNC | Cast: Integer to Floating Point (Java) | ||||||
Parasoft Jtest |
| CERT.NUM13.AIC | Avoid implicit casts from integer data types to floating point data types | ||||||
PVS-Studio |
| V6011 |
Related Guidelines
Bibliography
...
INT02-J. Do not assume that the remainder operator always returns a non-negative result 03. Integers (INT) INT04-J. Avoid using the char integral type to hold signed values