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Code generation (compiler) In computing, code generation is part of the process chain of a compiler and converts intermediate representation of source code into a form (e.g., machine code) that can be readily executed by the target system. Sophisticated compilers typically perform multiple passes over various intermediate forms.
Convolutional code with any code rate can be designed based on polynomial selection; 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.
The binary Golay code, G 23 is a perfect code. That is, the spheres of radius three around code words form a partition of the vector space. G 23 is a 12-dimensional subspace of the space F 23 2. The automorphism group of the perfect binary Golay code G 23 (meaning the subgroup of the group S 23 of permutations of the coordinates of F 23
Zurich-based DeepCode claims that their system — essentially a tool for analyzing and improving code — is like Grammarly for programmers. The system, which uses a corpus of 250,000 rules ...
full semantic analysis of source code, including parameter types, conditional compilation directives, macro expansions Javadoc: JSDoc: Yes JsDoc Toolkit: Yes mkd: Customisable for all type of comments 'as-is' in comments all general documentation; references, manual, organigrams, ... Including the binary codes included in the comments. all ...
It has learned to code (and blog and argue). Cade Metz, The New York Times OpenAI’s GPT-3 natural language system was trained on digital books, Wikipedia, blog posts, social media entries and more.
Thanks to Vancouver-based developer Jack Qiao, though, there's now a slightly easier way. He came up with Colormind, an AI algorithm that uses films, video games, fashion and art to "generate ...
Generators in the study must generate 250-words-or-fewer summaries provided a topic and a set of documents, while discriminators must detect whether a given summary is potentially AI-written.