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The exception to this result is a bit pattern the same as that of the generator polynomial. All uneven bit errors are detected by generator polynomials with even number of terms. 2-bit errors in a (multiple) distance of the longest bitfilter of even parity to a generator polynomial are not detected; all others are detected.
After a verification condition generator has created the verification conditions they are passed to an automated theorem prover, which can then formally prove the correctness of the code. Methods have been proposed to use the operational semantics of machine languages to automatically generate verification condition generators. [1]
The check digit is calculated by (()), where s is the sum from step 3. This is the smallest number (possibly zero) that must be added to s {\displaystyle s} to make a multiple of 10. Other valid formulas giving the same value are 9 − ( ( s + 9 ) mod 1 0 ) {\displaystyle 9-((s+9){\bmod {1}}0)} , ( 10 − s ) mod 1 0 {\displaystyle (10-s){\bmod ...
Formally, a message authentication code (MAC) system is a triple of efficient [4] algorithms (G, S, V) satisfying: G (key-generator) gives the key k on input 1 n, where n is the security parameter. S (signing) outputs a tag t on the key k and the input string x. V (verifying) outputs accepted or rejected on inputs: the key k, the string x and ...
In the context of hardware and software systems, formal verification is the act of proving or disproving the correctness of a system with respect to a certain formal specification or property, using formal methods of mathematics. [1] Formal verification is a key incentive for formal specification of systems, and is at the core of formal methods.
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Convolutional code with any code rate can be designed based on polynomial selection; [15] however, in practice, a puncturing procedure is often used to achieve the required code rate. Puncturing is a technique used to make a m/n rate code from a "basic" low-rate (e.g., 1/n) code. It is achieved by deleting of some bits in the encoder output.
A longest common subsequence (LCS) is the longest subsequence common to all sequences in a set of sequences (often just two sequences). It differs from the longest common substring : unlike substrings, subsequences are not required to occupy consecutive positions within the original sequences.