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Profiling in general can not prove anything about the unreachability of a piece of code, but may be a good heuristic for finding potentially unreachable code. Once a suspect piece of code is found, other methods, such as a more powerful code analysis tool, or even analysis by hand, could be used to decide whether the code is truly unreachable.
Dead code is normally considered dead unconditionally. Therefore, it is reasonable attempting to remove dead code through dead-code elimination at compile time. However, in practice it is also common for code sections to represent dead or unreachable code only under certain conditions, which may not be known at the time of compilation or assembly.
The term dead code has multiple definitions. Some use the term to refer to code (i.e. instructions in memory) which can never be executed at run-time. [1] [2] [3] In some areas of computer programming, dead code is a section in the source code of a program which is executed but whose result is never used in any other computation.
Psyco is an unmaintained specializing just-in-time compiler for pre-2.7 Python originally developed by Armin Rigo and further maintained and developed by Christian Tismer. Development ceased in December, 2011. [1] Psyco ran on BSD-derived operating systems, Linux, Mac OS X and Microsoft Windows using 32-bit Intel-compatible processors.
The W hierarchy is a collection of computational complexity classes. A parameterized problem is in the class W[i], if every instance (,) can be transformed (in fpt-time) to a combinatorial circuit that has weft at most i, such that (,) if and only if there is a satisfying assignment to the inputs that assigns 1 to exactly k inputs.
Shed Skin combines Ole Agesen's Cartesian Product Algorithm (CPA) with the data-polymorphic part of John Plevyak's Iterative Flow Analysis (IFA). [11] Version 0.6 introduced scalability improvements which repeatedly analyze larger versions of a program (in addition to the mentioned techniques), until it is fully analyzed.
In an example using the DVB-S2 rate 2/3 code the encoded block size is 64800 symbols (N=64800) with 43200 data bits (K=43200) and 21600 parity bits (M=21600). Each constituent code (check node) encodes 16 data bits except for the first parity bit which encodes 8 data bits.
In machine learning, a hyperparameter is a parameter that can be set in order to define any configurable part of a model's learning process. Hyperparameters can be classified as either model hyperparameters (such as the topology and size of a neural network) or algorithm hyperparameters (such as the learning rate and the batch size of an optimizer).