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If the function is not inlined, then the additional overhead of the function calls will probably take longer to run (on the order of 10 processor instructions for most high-performance languages). Theoretically, this additional time to run could matter. Example of duplicate code fix via code replaced by the method
Cycle detection is the problem of finding i and j, given f and x 0. Several algorithms are known for finding cycles quickly and with little memory. Robert W. Floyd 's tortoise and hare algorithm moves two pointers at different speeds through the sequence of values until they both point to equal values.
A checksum of a message is a modular arithmetic sum of message code words of a fixed word length (e.g., byte values). The sum may be negated by means of a ones'-complement operation prior to transmission to detect unintentional all-zero messages.
Any non-linear differentiable function, (,), of two variables, and , can be expanded as + +. If we take the variance on both sides and use the formula [11] for the variance of a linear combination of variables (+) = + + (,), then we obtain | | + | | +, where is the standard deviation of the function , is the standard deviation of , is the standard deviation of and = is the ...
Off-by-one errors are common in using the C library because it is not consistent with respect to whether one needs to subtract 1 byte – functions like fgets() and strncpy will never write past the length given them (fgets() subtracts 1 itself, and only retrieves (length − 1) bytes), whereas others, like strncat will write past the length given them.
In the case of a binary repetition code, there exist two code words - all ones and all zeros - which have a length of . Therefore, the minimum Hamming distance of the code equals its length n {\displaystyle n} .
In computer programming, bounds checking is any method of detecting whether a variable is within some bounds before it is used. It is usually used to ensure that a number fits into a given type (range checking), or that a variable being used as an array index is within the bounds of the array (index checking).
Empirical risk minimization for a classification problem with a 0-1 loss function is known to be an NP-hard problem even for a relatively simple class of functions such as linear classifiers. [5] Nevertheless, it can be solved efficiently when the minimal empirical risk is zero, i.e., data is linearly separable .