Search results
Results From The WOW.Com Content Network
The register width of a processor determines the range of values that can be represented in its registers. Though the vast majority of computers can perform multiple-precision arithmetic on operands in memory, allowing numbers to be arbitrarily long and overflow to be avoided, the register width limits the sizes of numbers that can be operated on (e.g., added or subtracted) using a single ...
The correct number of sections for a fence is n − 1 if the fence is a free-standing line segment bounded by a post at each of its ends (e.g., a fence between two passageway gaps), n if the fence forms one complete, free-standing loop (e.g., enclosure accessible by surmounting, such as a boxing ring), or n + 1 if posts do not occur at the ends ...
1 Debugging logic errors. 2 Examples. ... it is the easiest way to find the problem if the program uses the incorrect results of a bad mathematical calculation. ...
Visualization of a software buffer overflow. Data is written into A, but is too large to fit within A, so it overflows into B.. In programming and information security, a buffer overflow or buffer overrun is an anomaly whereby a program writes data to a buffer beyond the buffer's allocated memory, overwriting adjacent memory locations.
Arithmetic underflow can occur when the true result of a floating-point operation is smaller in magnitude (that is, closer to zero) than the smallest value representable as a normal floating-point number in the target datatype. [1] Underflow can in part be regarded as negative overflow of the exponent of the floating-point value. For example ...
In an interactive log-file browser, the right thing to do might be to return the entry unparsed, so the user can see it—but in an automated log-summarizing program, the right thing to do might be to supply null values for the unreadable fields, but abort with an error, if too many entries have been malformed.
An operation can be legal in principle, but the result can be impossible to represent in the specified format, because the exponent is too large or too small to encode in the exponent field. Such an event is called an overflow (exponent too large), underflow (exponent too small) or denormalization (precision loss).
In computing, a roundoff error, [1] also called rounding error, [2] is the difference between the result produced by a given algorithm using exact arithmetic and the result produced by the same algorithm using finite-precision, rounded arithmetic. [3]