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  2. Source lines of code - Wikipedia

    en.wikipedia.org/wiki/Source_lines_of_code

    Source lines of code (SLOC), also known as lines of code (LOC), is a software metric used to measure the size of a computer program by counting the number of lines in the text of the program's source code.

  3. Engset formula - Wikipedia

    en.wikipedia.org/wiki/Engset_formula

    In queueing theory, the Engset formula is used to determine the blocking probability of an M/M/c/c/N queue (in Kendall's notation). The formula is named after its developer, T. O. Engset . Example application

  4. Noisy-channel coding theorem - Wikipedia

    en.wikipedia.org/wiki/Noisy-channel_coding_theorem

    In information theory, the noisy-channel coding theorem (sometimes Shannon's theorem or Shannon's limit), establishes that for any given degree of noise contamination of a communication channel, it is possible (in theory) to communicate discrete data (digital information) nearly error-free up to a computable maximum rate through the channel.

  5. Little's law - Wikipedia

    en.wikipedia.org/wiki/Little's_law

    In mathematical queueing theory, Little's law (also result, theorem, lemma, or formula [1] [2]) is a theorem by John Little which states that the long-term average number L of customers in a stationary system is equal to the long-term average effective arrival rate λ multiplied by the average time W that a customer spends in the system.

  6. Shannon–Hartley theorem - Wikipedia

    en.wikipedia.org/wiki/Shannon–Hartley_theorem

    This formula's way of introducing frequency-dependent noise cannot describe all continuous-time noise processes. For example, consider a noise process consisting of adding a random wave whose amplitude is 1 or −1 at any point in time, and a channel that adds such a wave to the source signal. Such a wave's frequency components are highly ...

  7. Shannon's source coding theorem - Wikipedia

    en.wikipedia.org/wiki/Shannon's_source_coding...

    In information theory, the source coding theorem (Shannon 1948) [2] informally states that (MacKay 2003, pg. 81, [3] Cover 2006, Chapter 5 [4]): N i.i.d. random variables each with entropy H(X) can be compressed into more than N H(X) bits with negligible risk of information loss, as N → ∞; but conversely, if they are compressed into fewer than N H(X) bits it is virtually certain that ...

  8. Amdahl's law - Wikipedia

    en.wikipedia.org/wiki/Amdahl's_law

    Scalability Issues: While it highlights the limits of parallel speedup, it doesn't address practical scalability issues, such as the cost and complexity of adding more processors. Non-Parallelizable Work : Amdahl's Law emphasizes the non-parallelizable portion of the task as a bottleneck but doesn’t provide solutions for reducing or ...

  9. M/M/c queue - Wikipedia

    en.wikipedia.org/wiki/M/M/c_queue

    In queueing theory, a discipline within the mathematical theory of probability, the M/M/c queue (or Erlang–C model [1]: 495 ) is a multi-server queueing model. [2] In Kendall's notation it describes a system where arrivals form a single queue and are governed by a Poisson process, there are c servers, and job service times are exponentially distributed. [3]

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