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Double-precision floating-point format (sometimes called FP64 or float64) is a floating-point number format, usually occupying 64 bits in computer memory; it represents a wide range of numeric values by using a floating radix point. Double precision may be chosen when the range or precision of single precision would be insufficient.
The Java virtual machine's set of primitive data types consists of: [12] byte, short, int, long, char (integer types with a variety of ranges) 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 ...
Another meaning of range in computer science is an alternative to iterator. When used in this sense, range is defined as "a pair of begin/end iterators packed together". [1] It is argued [1] that "Ranges are a superior abstraction" (compared to iterators) for several reasons, including better safety.
In single precision, the bias is 127, so in this example the biased exponent is 124; in double precision, the bias is 1023, so the biased exponent in this example is 1020. fraction = .01000… 2 . IEEE 754 adds a bias to the exponent so that numbers can in many cases be compared conveniently by the same hardware that compares signed 2's ...
Because M falls in the range 1 ≤ M < 2, the value of log 2 M will fall in the range 0 ≤ log 2 M < 1 so at least 52 bits are needed to the right of the radix point to represent the fractional part of the logarithm. Combining 10 bits to the left of the radix point with 52 bits to the right of the radix point means that the significand part of ...
negate a double drem 73 0111 0011 value1, value2 → result get the remainder from a division between two doubles dreturn af 1010 1111 value → [empty] return a double from a method dstore 39 0011 1001 1: index value → store a double value into a local variable #index: dstore_0 47 0100 0111 value → store a double into local variable 0 dstore_1
Double-ended queues can also be implemented as a purely functional data structure. [3]: 115 Two versions of the implementation exist. The first one, called 'real-time deque, is presented below. It allows the queue to be persistent with operations in O(1) worst-case time, but requires lazy lists with memoization. The second one, with no lazy ...
In software engineering, double-checked locking (also known as "double-checked locking optimization" [1]) is a software design pattern used to reduce the overhead of acquiring a lock by testing the locking criterion (the "lock hint") before acquiring the lock. Locking occurs only if the locking criterion check indicates that locking is required.