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In computing, in particular compiler construction, value range analysis is a type of data flow analysis that tracks the range (interval) of values that a numeric variable can take on at each point of a program's execution. [1]
In engineering, numerical ranges are used as a rough estimate of eigenvalues of A. Recently, generalizations of the numerical range are used to study quantum computing. A related concept is the numerical radius, which is the largest absolute value of the numbers in the numerical range, i.e.
In the case of an integer, the variable definition is restricted to whole numbers only, and the range will cover every number within its range (including the maximum and minimum). For example, the range of a signed 16-bit integer variable is all the integers from −32,768 to +32,767.
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 ...
As signed numbers can represent negative numbers, they lose a range of positive numbers that can only be represented with unsigned numbers of the same size (in bits) because roughly half the possible values are non-positive values, whereas the respective unsigned type can dedicate all the possible values to the positive number range.
At the conclusion of its seventh and penultimate rate-setting policy meeting of 2024 on November 7, 2024, the Federal Reserve announced it was lowering the federal funds target interest rate by 25 ...
[9] [10] A conforming program can assume that it can safely store values between −(2 15 −1) [11] and 2 15 −1, [12] but it may not assume that the range is not larger. In Java, a short is always a 16-bit integer. In the Windows API, the datatype SHORT is defined as a 16-bit signed integer on all machines.
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