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strictfp is an obsolete and redundant reserved word in the Java programming language. [1] [2] Previously, this keyword was used as a modifier that restricted floating-point calculations to IEEE 754 semantics to ensure portability.
float and double, floating-point numbers with single and double precisions; boolean, a Boolean type with logical values true and false; returnAddress, a value referring to an executable memory address. This is not accessible from the Java programming language and is usually left out. [13] [14]
Primitive data types, such as Booleans, fixed-size integers, floating-point values, and characters, are value types. Objects, in the sense of object-oriented programming , belong to reference types. Assigning to a variable of reference type simply copies the reference, whereas assigning to a variable of value type copies the value.
Conversely, precision can be lost when converting representations from integer to floating-point, since a floating-point type may be unable to exactly represent all possible values of some integer type. For example, float might be an IEEE 754 single precision type, which cannot represent the integer 16777217 exactly, while a 32-bit integer type ...
A floating-point variable can represent a wider range of numbers than a fixed-point variable of the same bit width at the cost of precision. A signed 32-bit integer variable has a maximum value of 2 31 − 1 = 2,147,483,647, whereas an IEEE 754 32-bit base-2 floating-point variable has a maximum value of (2 − 2 −23) × 2 127 ≈ 3.4028235 ...
In the floating-point case, a variable exponent would represent the power of ten to which the mantissa of the number is multiplied. Languages that support a rational data type usually allow the construction of such a value from two integers, instead of a base-2 floating-point number, due to the loss of exactness the latter would cause.
The value distribution is similar to floating point, but the value-to-representation curve (i.e., the graph of the logarithm function) is smooth (except at 0). Conversely to floating-point arithmetic, in a logarithmic number system multiplication, division and exponentiation are simple to implement, but addition and subtraction are complex.
prefix, and with the zero mantissa all bits after the decimal point are zero, meaning this value is interpreted as =. Floating point numbers use a signed zero, so is also available and is equal to positive . 0 0000 000 = 0 1 0000 000 = −0