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.
Formal Languages, Encodings, and Decision Problems: Examples and Counterexamples
1 · Prerequisites
2 · Summary
These examples make the page's vocabulary concrete: one worked language concatenation, one paired-encoding calculation, and two local counterexamples to common misstatements about languages and encodings.
3 · Logical flowchart
4 · Definitions, theorems and proofs
None yet.
5 · Examples, counterexamples and false statements
A concrete calculation of
Example
Let , , and over the alphabet . Then
Facts & Assumptions
Given: , , and .
Language concatenation is by Language concatenation, powers, and Kleene star.
Language concatenation is associative by Language concatenation is associative.
Verification
Using [L1], we have . Therefore
Again by [L1], . Therefore
The two explicit calculations in steps 1.1 and 1.2 agree, so this example realizes the identity of [L2] as the four-word set .
The language is not a set of alphabet symbols
Statement refuted
The statement "every language over an alphabet is a subset of " is false.
Facts & Assumptions
Given: The binary alphabet and the set .
The statement refuted is: every language over an alphabet is a subset of .
A language over is a subset of by Languages over an alphabet.
Counterexample
The set is a language over : the unique element is a binary word, so .
But , because contains only the two one-letter symbols and . Therefore .
So is a counterexample to [A1].
The encoding is effective but not prefix-free
Statement refuted
The statement "every effective binary encoding is prefix-free" is false.
Facts & Assumptions
Given: The encoding on binary words.
The statement refuted is: every effective binary encoding is prefix-free.
An effective binary encoding is an injective map into with a total decoder, and prefix-free means that no codeword is a proper prefix of another, by Effective binary encodings and total decoders.
Counterexample
The map is effective: define a total decoder by removing the first bit from any binary word beginning with , and sending every binary word not beginning with (including the empty word) to the fixed malformed token. Then the decoder recovers from .
The codeword is a proper prefix of , so is not prefix-free.
Therefore is a counterexample to [A1].