How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Finite tuples admit effective prefix-free binary encodings
Statement
For every fixed , the set of binary -tuples has an effective prefix-free binary encoding.
Facts & Assumptions
Given: A fixed integer .
An effective binary encoding is an injective map into equipped with a total decoder having a fixed malformed-code output, and prefix-free means that no codeword is a proper prefix of another, by Effective binary encodings and total decoders.
Proof
First encode a single binary word by From the initial block of 's and the following , one reads off and then reads exactly that many remaining bits, so is injective and has a total decoder that either returns the uniquely parsed word or the malformed token of [L1].
For the fixed tuple length , define The initial block tells the decoder that exactly self-delimiting blocks must follow. Parsing those blocks recovers a unique tuple when the input has the required form, and otherwise the decoder returns the malformed token. Hence is an effective encoding in the sense of [L1].
The encoding is prefix-free. Indeed, once the parser has read the initial block , it knows that the codeword ends exactly after the th self-delimiting block. So a valid codeword cannot be a proper prefix of a different valid codeword with extra unread bits at the end.
Therefore admits an effective prefix-free binary encoding.
Depends on
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
4 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- Michael Sipser, MIT 18.404J Theory of Computation, Lecture 7 (standard reference, not scraped)