Alphabeta Math
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.

✓ 12 results · all verified · 8 also independently AI-judged
Every result on this page is machine-checked by a proof checker and read in full and owner-audited; the judge is an additional, independent cross-model AI review of the proofs. The 4 not AI-judged were verified by owner audit (typically over a confirmed judge false positive), not failures.

Myhill--Nerode Theory and DFA Minimization

1 · Prerequisites

2 · Summary

This page develops the Myhill--Nerode point of view in two parallel forms. First it studies equivalent states inside one DFA and the quotient obtained by merging them. It then passes to Nerode equivalence on words, proves the Myhill--Nerode characterization of regular languages, and reads minimal DFA structure off the resulting equivalence classes.

The closing items package two standard applications. One is algorithmic: the table-filling procedure detects exactly the distinguishable state pairs and therefore computes DFA minimization. The other is structural: the pumping lemma is a necessary consequence of finite-state behavior, but it is weaker than the full Myhill--Nerode criterion and can be misused when its quantifiers are read in the wrong order.

3 · Logical flowchart

4 · Definitions, theorems and proofs

DefinitionDefinition: Literature-sourcedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-09-12Open item page →

The right language of a DFA state and state equivalence

Definition

Let D=(Q,Σ,δ,q0,F) be a DFA with extended transition function δ∗.

For a state q∈Q, the right language of q is RD(q):={w∈Σ∗:δ∗(q,w)∈F}.

Two states p,q∈Q are state-equivalent when they have the same right language: p≡Dq⟺RD(p)=RD(q). Equivalently, p≡Dq⟺∀w∈Σ∗, δ∗(p,w)∈F  ⟺  δ∗(q,w)∈F.

Remarks

  • State-equivalent states have the same future accepting behavior under every continuation.

  • Distinct states may still be equivalent; minimization identifies exactly such redundancies.

LemmaStatement: Literature-sourcedProof: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-09-12Open item page →

State-equivalent DFA states stay equivalent after every input word

Statement

For every DFA D, the state-equivalence relation ≡D of The right language of a DFA state and state equivalence is an equivalence relation on the state set, and for every word u∈Σ∗, p≡Dq  ⟹  δ∗(p,u)≡Dδ∗(q,u).

Facts & Assumptions

Given: A DFA D=(Q,Σ,δ,q0,F) with extended transition function δ∗.

[L1]

By The right language of a DFA state and state equivalence, p≡Dq means that for every continuation w∈Σ∗ one has δ∗(p,w)∈F if and only if δ∗(q,w)∈F.

[L2]

By Equivalence relation, equivalence class, and the quotient set A/∼, a relation is an equivalence relation exactly when it is reflexive, symmetric, and transitive.

[L3]

By The extended transition function of a DFA, δ∗(s,ε)=s and δ∗(s,va)=δ(δ∗(s,v),a) for every state s, word v, and letter a.

Proof

technique · direct
1.1L1L2given

Equality of right languages is reflexive, symmetric, and transitive, so [L1] and [L2] show that ≡D is an equivalence relation on Q.

1.2L1L3construct

Fix a letter a∈Σ. If p≡Dq, then induction on v using [L3] gives δ∗(δ(p,a),v)=δ∗(p,av) and δ∗(δ(q,a),v)=δ∗(q,av) for every word v; applying [L1] to the continuation av therefore yields δ(p,a)≡Dδ(q,a).

2.1L3step 1.2induction

We now induct on the word u. The case u=ε is immediate from [L3]. If the claim holds for u and a∈Σ, then step 1.2 applied to the equivalent states δ∗(p,u) and δ∗(q,u) gives δ∗(p,ua)≡Dδ∗(q,ua).

3.1step 1.1step 2.1∎

Steps 1.1 and 2.1 prove both claims.

DefinitionDefinition: Literature-sourcedProof: Not applicableaudited 2026-09-12Open item page →

The quotient DFA by state equivalence

Definition

Let D=(Q,Σ,δ,q0,F) be a DFA, and let ≡D be the state-equivalence relation of The right language of a DFA state and state equivalence. Its quotient set Q/≡D is available by State-equivalent DFA states stay equivalent after every input word together with Equivalence relation, equivalence class, and the quotient set A/∼.

The quotient DFA by state equivalence is the automaton D/≡D:=(Q/≡D,Σ,δ‾,[q0],F‾), where δ‾([q],a):=[δ(q,a)] and F‾:={[q]∈Q/≡D:q∈F}.

The next item proves that these definitions do not depend on the chosen representatives and that the quotient recognizes the same language as D.

LemmaStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-09-12Open item page →

The quotient by state equivalence is a well-defined equivalent DFA

Statement

Let D be a DFA. The quotient automaton D/≡D of The quotient DFA by state equivalence is well defined and recognizes the same language as D.

Facts & Assumptions

Given: A DFA D=(Q,Σ,δ,q0,F) with extended transition function δ∗.

[L1]

By The quotient DFA by state equivalence, the quotient automaton uses states [q], transition rule δ‾([q],a)=[δ(q,a)], start state [q0], and accepting classes F‾={[q]:q∈F}.

[L2]

By State-equivalent DFA states stay equivalent after every input word, if q≡Dq′ then δ∗(q,u)≡Dδ∗(q′,u) for every word u, hence in particular δ(q,a)≡Dδ(q′,a) for every letter a.

[L3]

By Acceptance of a word by a DFA and the recognized language, a DFA accepts a word exactly when the state reached by its extended transition function is accepting.

[L4]

By The extended transition function of a DFA, the extended transition satisfies δ∗(q,ε)=q and δ∗(q,ua)=δ(δ∗(q,u),a).

[L5]

By The right language of a DFA state and state equivalence, q≡Dq′ means that for every continuation u∈Σ∗ one has δ∗(q,u)∈F if and only if δ∗(q′,u)∈F.

Proof

technique · direct
1.1L1L2given

Step [L2] shows that if q≡Dq′ then [δ(q,a)]=[δ(q′,a)] for every letter a, so δ‾([q],a) is independent of the chosen representative.

1.2L4L5

If q≡Dq′ and q∈F, then [L4] gives δ∗(q,ε)=q and δ∗(q′,ε)=q′. Applying [L5] to the continuation ε therefore shows q′∈F as well. Thus F‾ is representative-independent.

1.3L1L4induction

Let δ‾∗ be the extended transition of the quotient DFA. Induction on u using [L1] and [L4] gives δ‾∗([q],u)=[δ∗(q,u)] for every state class [q] and every word u.

2.1L3step 1.2step 1.3

For every word u, step 1.3 and [L3] give u∈L(D/≡D)  ⟺  δ‾∗([q0],u)∈F‾  ⟺  [δ∗(q0,u)]∈F‾  ⟺  δ∗(q0,u)∈F  ⟺  u∈L(D).

3.1step 1.1step 1.2step 2.1∎

Therefore the quotient DFA is well defined and equivalent to D.

DefinitionDefinition: Literature-sourcedProof: Not applicablejudge pass (gpt-5.6-terra)audited 2026-09-12Open item page →

Nerode equivalence of words

Definition

Let L⊆Σ∗ be a language over an alphabet Σ.

Two words u,v∈Σ∗ are Nerode-equivalent for L when every right continuation tests membership in the same way: u≡Lv⟺∀x∈Σ∗, ux∈L  ⟺  vx∈L.

The equivalence classes of ≡L are the Nerode classes of L. Their number, finite or infinite, is the index of ≡L.

LemmaStatement: Literature-sourcedProof: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-09-12Open item page →

Nerode-equivalent words stay equivalent after right concatenation

Statement

For every language L⊆Σ∗, the Nerode relation ≡L of Nerode equivalence of words is an equivalence relation on Σ∗, and for every words u,v,x∈Σ∗, u≡Lv  ⟹  ux≡Lvx.

Facts & Assumptions

Given: A language L⊆Σ∗.

[L1]

By Nerode equivalence of words, u≡Lv means that for every continuation y∈Σ∗ one has uy∈L if and only if vy∈L.

[L2]

By Equivalence relation, equivalence class, and the quotient set A/∼, it is enough to check reflexivity, symmetry, and transitivity.

Proof

technique · direct
1.1L1L2given

Reflexivity, symmetry, and transitivity follow immediately from the biconditional in [L1], so [L2] shows that ≡L is an equivalence relation.

1.2L1given

Assume u≡Lv and fix x∈Σ∗. For every continuation y, [L1] applied to the continuation xy gives uxy∈L  ⟺  vxy∈L, which is exactly the condition (ux)≡L(vx).

2.1step 1.1step 1.2∎

Therefore ≡L is an equivalence relation preserved by right concatenation.

LemmaStatement: Literature-sourcedProof: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-09-12Open item page →

A DFA can realize at most one Nerode class per reachable state

Statement

Let D be a DFA recognizing a language L. If two words u,v∈Σ∗ drive D from its start state to the same state, then u≡Lv. Consequently, distinct Nerode classes of L must reach distinct reachable states of D.

Facts & Assumptions

Given: A DFA D=(Q,Σ,δ,q0,F) recognizing L, with extended transition function δ∗.

[L1]

By Nerode equivalence of words, to prove u≡Lv it is enough to show that uz∈L if and only if vz∈L for every continuation z∈Σ∗.

[L2]

By Acceptance of a word by a DFA and the recognized language, a word w belongs to L exactly when δ∗(q0,w)∈F.

[L3]

By The extended transition function of a DFA, δ∗(s,ε)=s and δ∗(s,xa)=δ(δ∗(s,x),a).

Proof

technique · direct
1.1L3construct

For every state s and words x,z, repeated use of [L3] gives δ∗(s,xz)=δ∗(δ∗(s,x),z); in particular, δ∗(q0,uz)=δ∗(δ∗(q0,u),z) and δ∗(q0,vz)=δ∗(δ∗(q0,v),z).

2.1L1L2step 1.1given

If δ∗(q0,u)=δ∗(q0,v), then step 1.1 implies δ∗(q0,uz)=δ∗(q0,vz) for every z∈Σ∗. By [L2], this gives uz∈L if and only if vz∈L for every z, so [L1] yields u≡Lv.

3.1step 2.1∎

Therefore every reachable state of D contains words from at most one Nerode class, and distinct Nerode classes must land in distinct reachable states.

TheoremStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-09-12Open item page →

A language is regular if and only if its Nerode equivalence has finite index

Statement

Let L⊆Σ∗ be a language. Then L is regular if and only if its Nerode equivalence relation ≡L has finite index.

Facts & Assumptions

Given: A language L⊆Σ∗ over an alphabet Σ.

[L1]

By Regular languages, a language is regular exactly when some DFA recognizes it; acceptance and the recognized language are those of Acceptance of a word by a DFA and the recognized language.

[L2]

By A DFA can realize at most one Nerode class per reachable state, if a DFA recognizes L then distinct Nerode classes of L must reach distinct reachable states of that DFA.

[L3]

By Nerode-equivalent words stay equivalent after right concatenation, u≡Lv implies ua≡Lva for every letter a∈Σ, so the transition rule [u]↦[ua] on Nerode classes is well defined.

[L4]

By Deterministic finite automata, a DFA is determined by a finite state set, a start state, a total transition rule on letters, and a chosen accepting subset.

Proof

technique · direct
1.1L1L2given

Assume L is regular. By [L1], choose a DFA D recognizing L. Step [L2] gives an injection from the set of Nerode classes of L into the reachable state set of D, so the index of ≡L is finite because a DFA has only finitely many states.

1.2L3L4construct

Assume conversely that ≡L has finite index. Let Q be its finite set of equivalence classes, let the start state be [ε], define δ([u],a):=[ua], and let F:={[u]∈Q:u∈L}. By [L3], the transition rule is well defined, so [L4] gives a DFA DL=(Q,Σ,δ,[ε],F).

2.1L1step 1.2induction

For every word u∈Σ∗, induction on u shows that the state reached by DL from [ε] is exactly [u]. Hence u∈L(DL)  ⟺  [u]∈F  ⟺  u∈L, so DL recognizes L and [L1] implies that L is regular.

3.1step 1.1step 2.1∎

Steps 1.1 and 2.1 prove both implications.

CorollaryStatement: Literature-sourcedProof: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-09-12Open item page →

Nerode classes form the canonical minimal DFA

Statement

If L is regular, then the DFA whose states are the Nerode classes of L is a minimal DFA for L. Its state set and transition structure depend only on L, so it is canonical.

Facts & Assumptions

Given: A regular language L⊆Σ∗.

[L1]

By A language is regular if and only if its Nerode equivalence has finite index, finite-index Nerode classes build a DFA recognizing L.

[L2]

By A DFA can realize at most one Nerode class per reachable state, every DFA recognizing L has distinct reachable states for distinct Nerode classes.

Proof

technique · direct
1.1L1given

Because L is regular, [L1] provides a DFA DL whose states are exactly the Nerode classes of L and which recognizes L.

1.2L2given

Let D be any DFA recognizing L. Every Nerode class contains some word u, and the state reached by D on u is reachable. By [L2], two distinct Nerode classes cannot reach the same state of D, so D has at least as many reachable states as DL has states.

2.1step 1.1step 1.2∎

Step 1.2 shows that no DFA for L can use fewer reachable states than DL, so DL is minimal. It is canonical because its states are defined directly from the language L rather than from an auxiliary machine.

TheoremStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-09-12Open item page →

Minimal DFAs are unique up to start-state-preserving isomorphism

Statement

If two DFAs are minimal among the DFAs recognizing the same regular language L, then there is an isomorphism between them that sends the start state of one to the start state of the other.

Facts & Assumptions

Given: Minimal DFAs D1 and D2 recognizing the same regular language L.

[L1]

By Nerode classes form the canonical minimal DFA, the Nerode-class DFA DL is a minimal DFA for L.

[L2]

By Reachable states of a DFA, a state is reachable exactly when some input word leads to it from the start state.

[L3]

By Removing unreachable states preserves the recognized language, deleting unreachable states preserves the recognized language.

Proof

technique · direct
1.1L3given

A minimal DFA has no unreachable states. Indeed, if Di had an unreachable state, then [L3] would remove it without changing the language, contradicting minimality.

2.1L1L2step 1.1construct

Let DL be the canonical Nerode-class DFA from [L1]. Because step 1.1 shows that every state of Di is reachable, for each state q of Di we may choose a word u with δi∗(q0,i,u)=q, which is possible by [L2], and send q to the Nerode class [u]. If two words u,v reach the same state q, then every continuation is accepted or rejected identically from that state, so u and v determine the same Nerode class. Thus the map is well defined. For any Nerode class [u], the state reached by Di on u maps to [u], so the map is surjective onto the state set of DL.

3.1L1step 2.1given

Both Di and DL are minimal DFAs for L: Di by hypothesis and DL by [L1]. Therefore their finite state sets have the same cardinality. The surjection from step 2.1 between finite sets of equal size is therefore a bijection.

4.1step 2.1step 3.1∎

The bijection of steps 2.1 and 3.1 sends the start state to [ε], and its definition via reaching words shows that it preserves letter transitions and accepting states. Hence each Di is pointed-isomorphic to DL, so D1 and D2 are pointed-isomorphic to one another.

DefinitionDefinition: AI-adaptedProof: Not applicableaudited 2026-09-12Open item page →

Distinguishing words for states and for prefixes

Definition

Let D=(Q,Σ,δ,q0,F) be a DFA with extended transition function δ∗.

  • A word x∈Σ∗ distinguishes states p,q∈Q when exactly one of the states δ∗(p,x) and δ∗(q,x) is accepting. Equivalently, x witnesses that p and q are not state-equivalent.

  • For a language L⊆Σ∗, a word x∈Σ∗ distinguishes words u,v∈Σ∗ when exactly one of ux and vx lies in L. Equivalently, x witnesses that u̸≡Lv.

Remarks

  • Distinguishing words are the concrete witnesses behind both minimization and Myhill--Nerode lower bounds.

  • The empty word ε is allowed; it distinguishes two states exactly when one is accepting and the other is not.

TheoremStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-09-12Open item page →

The table-filling algorithm computes state equivalence and DFA minimization

Statement

Fix a DFA D. Delete its unreachable states, mark every accepting/nonaccepting pair, and then repeatedly mark any unmarked pair {p,q} for which some letter a has already-marked successor pair {δ(p,a),δ(q,a)}. When the process stabilizes, the unmarked pairs are exactly the state-equivalent pairs of D, and merging each equivalence class yields a minimal DFA for the same language.

Facts & Assumptions

Given: A DFA D.

[L1]

By Removing unreachable states preserves the recognized language, we may delete unreachable states first without changing the recognized language.

[L2]

By Distinguishing words for states and for prefixes, a pair of states is distinguishable exactly when some continuation accepts from one state and rejects from the other.

[L3]

By State-equivalent DFA states stay equivalent after every input word, state equivalence is preserved by every input word.

[L4]

By The quotient by state equivalence is a well-defined equivalent DFA, quotienting by state equivalence gives an equivalent DFA.

Proof

technique · direct
1.1L1construct

Replace D by its reachable part using [L1]. Let M0 be the set of accepting/nonaccepting pairs, and for t≥0 let Mt+1 be obtained from Mt by also marking every pair {p,q} for which some letter a has {δ(p,a),δ(q,a)}∈Mt. Put M:=⋃tMt.

2.1L2step 1.1induction

We prove by induction on t that every pair in Mt has a distinguishing word of length at most t. For M0, the empty word distinguishes every accepting/nonaccepting pair by [L2]. For the induction step, if {p,q} is newly marked because {δ(p,a),δ(q,a)}∈Mt, prepend the letter a to a distinguishing word for the successor pair.

3.1L2step 2.1induction

Conversely, we induct on the length of a distinguishing word x. If x=ε, then the pair is in M0. If x=ay, then y distinguishes δ(p,a) and δ(q,a), so the induction hypothesis puts the successor pair in some Mt, and the algorithm then marks {p,q} at the next stage. Therefore a pair is marked exactly when it is distinguishable.

4.1L2L3L4step 3.1

Unmarked pairs are therefore precisely the indistinguishable pairs, hence precisely the state-equivalent pairs by [L2]. By [L3] this is an equivalence relation, and [L4] gives an equivalent quotient DFA Q.

4.2L2step 1.1step 3.1construct

Let E be any reachable DFA equivalent to D. Because step 1.1 replaced D by its reachable part, each state class C of Q has a representative state qC reached in D by some word uC. Send C to the state reached by E on uC. If C≠C′, then their representatives are distinguishable by step 3.1; choose a distinguishing word x. The words uCx and uC′x are then accepted differently by D, hence also by the equivalent DFA E, so the reached states of E are distinct. Thus this map from the states of Q into the states of E is injective.

5.1step 4.1step 4.2∎

Therefore every reachable DFA equivalent to D has at least as many states as Q. Since Q itself is equivalent to D by step 4.1, it is a minimal DFA for the same language.

TheoremStatement: Literature-sourcedProof: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-09-12Open item page →

The pumping lemma for regular languages

Statement

If L is regular, then there exists p≥1 such that every word w∈L with ∣w∣≥p can be written as w=xyz with ∣xy∣≤p,∣y∣>0,xyiz∈L for every i≥0.

Facts & Assumptions

Given: A regular language L.

[L0]

By Regular languages, some DFA recognizes L.

[L1]

By Deterministic finite automata, a DFA has only finitely many states.

[L2]

By Acceptance of a word by a DFA and the recognized language, a word is in L exactly when an accepting state is reached after reading it in some DFA for L.

[L3]

By The extended transition function of a DFA, reading a word letter by letter determines the successive run states.

[L4]

By The pigeonhole principle on N, among n+1 objects placed into only n positions, some two positions coincide.

Proof

technique · direct
1.1L0L1L3given

Choose the DFA D recognizing L supplied by [L0], and let p be its number of states, which is finite by [L1]. Fix a word w=a1⋯am∈L with m≥p. As D reads the prefixes ε,a1,a1a2,…,a1⋯ap, [L3] gives p+1 visited states.

2.1L4step 1.1choose

By [L4], two of those first p+1 visited states are equal; write them as the states after the prefixes of lengths i<j≤p, and set x:=a1⋯ai, y:=ai+1⋯aj, and z:=aj+1⋯am. Then w=xyz, ∣xy∣=j≤p, and ∣y∣=j−i>0.

3.1L2L3step 2.1∎

Because the run returns to the same state after reading y, repeating or deleting that loop does not change the state reached before the suffix z. Therefore [L2] implies xyiz∈L for every i≥0, so the factorization from step 2.1 satisfies all three required conditions.

CorollaryStatement: Literature-sourcedProof: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-09-12Open item page →

Infinitely many pairwise distinguishable prefixes force nonregularity

Statement

Let L⊆Σ∗. If there are infinitely many words in Σ∗ that are pairwise distinguished by suffixes, then L is not regular.

Facts & Assumptions

Given: A language L⊆Σ∗ with infinitely many pairwise distinguishable words.

[L1]

By Distinguishing words for states and for prefixes, a suffix distinguishes two words exactly when those two words are not Nerode-equivalent.

[L2]

By A language is regular if and only if its Nerode equivalence has finite index, a regular language has only finitely many Nerode classes.

Proof

technique · direct
1.1L1given

If two words are pairwise distinguished by suffixes, then [L1] shows that they lie in distinct Nerode classes.

2.1L2step 1.1∎

Therefore the infinitely many given words occupy infinitely many Nerode classes. By [L2], L cannot be regular.

False statementConstruction: AI-adaptedVerification: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-09-12Open item page →

FALSE: the pumping lemma characterizes the regular languages

Statement

If a language satisfies the regular pumping property, then it is regular.

Facts & Assumptions

Given: The language G:={wwRv:w,v∈{0,1}+, w≠ε}.

[L2]

By Infinitely many pairwise distinguishable prefixes force nonregularity, a language with infinitely many pairwise distinguishable prefixes is not regular.

Refutation

technique · direct
1.1givenconstruct

The language G satisfies the pumping conclusion with pumping length 4. If s=wwRv∈G with ∣w∣≥2, write w=au with u≠ε and choose x=ε, y=a, z=uuRav; then xz=uuRav∈G, the original word is xyz∈G, and for every i≥2 the word xyiz=aiuuRav lies in G by using the one-letter witness word a and the nonempty suffix ai−2uuRav.

1.2L2given

For each n≥1, let pn:=(01)n and xn:=(10)n1. Then pnxn=(01)n(10)n1 lies in G by taking witness word (01)n and suffix 1. If m>n and pmxn were in G, write pmxn=rrRv with r≠ε and v∈{0,1}+. The word pmxn=(01)m(10)n1 has exactly one doubled adjacent pair, namely the middle 11 at the junction between (01)m and (10)n1. Any prefix of the form rrR has a doubled middle pair at the boundary between r and rR, so that boundary must be this unique 11. Hence ∣r∣=2m, which makes the palindromic prefix rrR have length 4m. But ∣pmxn∣=2m+2n+1<4m+1 because n<m, so no such factorization with nonempty v exists. Therefore pmxn∉G, and the prefixes pn are pairwise distinguishable.

2.1step 1.1given

If instead ∣w∣=1, then s=aav with ∣v∣≥2 because ∣s∣≥4; writing v=bt and choosing x=aa, y=b, z=t pumps entirely inside the nonempty suffix v, so every xyiz stays in G. Thus every sufficiently long word in G has a legal pumping decomposition.

3.1L2step 1.1step 2.1step 1.2∎

Step 1.2 and [L2] show that G is not regular, while steps 1.1 and 2.1 show that G still has the regular pumping property. Therefore the pumping property does not characterize regularity, and the statement is false.

False statementConstruction: AI-adaptedVerification: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-09-12Open item page →

FALSE: the pumping lemma still works if its quantifiers are reordered

Statement

In the pumping lemma, once a pumping length is fixed, every legal decomposition of every sufficiently long word pumps.

Facts & Assumptions

Given: The regular language O:={x∈{0,1}∗:∣x∣ is odd}.

[L1]

By The pumping lemma for regular languages, a regular language only guarantees the existence of a good decomposition for each sufficiently long word.

Refutation

technique · direct
1.1givenconstruct

The language O is regular: a two-state DFA that toggles parity after each input symbol accepts exactly the words of odd length.

1.2givenconstruct

Fix any pumping length p≥1 and take w:=02p+1∈O. The decomposition x:=ε, y:=0, z:=02p is legal because ∣xy∣=1≤p and ∣y∣>0, but pumping once gives xz=02p, whose length is even, so xz∉O. Thus this legal decomposition does not pump.

2.1L1step 1.1step 1.2∎

Step 1.2 shows that a regular language can have bad legal decompositions even though [L1] supplies some good one. Therefore the quantifiers cannot be reordered as stated, and the statement is false.

5 · Examples, counterexamples and false statements

None yet.

Sources