2. RegularExpressionsandNonregularlanguages DanielLupp€¦ · Regular Expressions...

INF20802. Regular Expressions and Nonregular languages

Daniel Lupp

Universitetet i Oslo

25th January 2018

Department ofInformatics

University ofOslo

INF2080 Lecture :: 25th January 1 / 39

Last week

Deterministic finite automata (DFA)

Regular languages are those languages accepted by DFA’sNondeterministic automata (NFA)

1start

DFA ↔ NFA

Last week

Regular languages are those languages accepted by DFA’s

Nondeterministic automata (NFA)

1start

DFA ↔ NFA

Last week

1start

DFA ↔ NFA

Last week

1start

DFA ↔ NFAINF2080 Lecture :: 25th January 2 / 39

Regular Expressions

Definition (Regular Expression)

Given an alphabet Σ, a regular expression isa for some a ∈ Σ,

ε,∅,(R1 ∪ R2) for regular expressions R1,R2,(R1R2) for regular expressions R1,R2,R∗1 for a regular expression R1.

→ Regular expressions represent languages!

Regular Expressions

Given an alphabet Σ, a regular expression isa for some a ∈ Σ,ε,

∅,(R1 ∪ R2) for regular expressions R1,R2,(R1R2) for regular expressions R1,R2,R∗1 for a regular expression R1.

Regular Expressions

Given an alphabet Σ, a regular expression isa for some a ∈ Σ,ε,∅,

(R1 ∪ R2) for regular expressions R1,R2,(R1R2) for regular expressions R1,R2,R∗1 for a regular expression R1.

Regular Expressions

Given an alphabet Σ, a regular expression isa for some a ∈ Σ,ε,∅,(R1 ∪ R2) for regular expressions R1,R2,

(R1R2) for regular expressions R1,R2,R∗1 for a regular expression R1.

Regular Expressions

Given an alphabet Σ, a regular expression isa for some a ∈ Σ,ε,∅,(R1 ∪ R2) for regular expressions R1,R2,(R1R2) for regular expressions R1,R2,

R∗1 for a regular expression R1.

Regular Expressions

Given an alphabet Σ, a regular expression isa for some a ∈ Σ,ε,∅,(R1 ∪ R2) for regular expressions R1,R2,(R1R2) for regular expressions R1,R2,R∗1 for a regular expression R1.

Regular Expressions

Given an alphabet Σ, a regular expression isa for some a ∈ Σ,ε,∅,(R1 ∪ R2) for regular expressions R1,R2,(R1R2) for regular expressions R1,R2,R∗1 for a regular expression R1.

Regular Expressions - Examples

What languages do the following regular expressions (RE) represent?0∗

10∗1(1(0 ∪ 1)∗1) ∪ (0(0 ∪ 1)∗0) ∪ 0 ∪ 1

10∗1

(1(0 ∪ 1)∗1) ∪ (0(0 ∪ 1)∗0) ∪ 0 ∪ 1

10∗1(1(0 ∪ 1)∗1) ∪ (0(0 ∪ 1)∗0) ∪ 0 ∪ 1

Regular Expressions - Automata

What is the connection between RE and DFA/NFA?

Language 0(0 ∪ 1)∗0:2

1start 3

Language 0(0 ∪ 1)∗0:

1start 3

Language 0(0 ∪ 1)∗0:2

1start 3

Regular Expressions and Automata

Can all RE be represented using DFA/NFA?Can all DFA/NFA be described by RE?

PropositionEvery language described by an RE is regular.

Proof based on inductive definition of RE!

Given an alphabet Σ, a regular expressionis

a for some a ∈ Σ,ε,∅,(R1 ∪ R2) for regular expressionsR1,R2,(R1R2) for regular expressions R1,R2,R∗1 for a regular expression R1.

if R = a for a ∈ Σ, then L(R) = {a} is ac-cepted by

starta

If R = ε, then L(R) = {ε} is accepted by

If R = ∅, then L(R) = ∅ is accepted by

starta

The rest is union, concatanation and Kleenestar of regular languages, as discussed lastweek!

(recall: the union/concatanation/Kleene star ofregular languages is itself regular)

The rest is union, concatanation and Kleenestar of regular languages, as discussed lastweek!(recall: the union/concatanation/Kleene star ofregular languages is itself regular)

So we’ve just proven

PropositionEvery language described by a RE is regular.

PropositionEvery regular language can be described using a RE.

So we’ve just proven

PropositionEvery language described by a RE is regular.

Generalized Nondeterministic Finite Automaton(GNFA):

NFA where the transitions are RE, notonly symbols from Σ.

some other assumptions for convenience:start state goes to every other state, buthas no incoming statesevery state goes to the unique acceptingstate, which is different from the startingstate. The accepting state does not haveany outgoing arrows.all other states have one transition to allother states, including themselves.

start1

(0 ∪ 1)∗

start((ab∗) ∪ (ba∗))∗

NFA where the transitions are RE, notonly symbols from Σ.

some other assumptions for convenience:start state goes to every other state, buthas no incoming statesevery state goes to the unique acceptingstate, which is different from the startingstate. The accepting state does not haveany outgoing arrows.all other states have one transition to allother states, including themselves.

(0 ∪ 1)∗

NFA where the transitions are RE, notonly symbols from Σ.some other assumptions for convenience:

start state goes to every other state, buthas no incoming statesevery state goes to the unique acceptingstate, which is different from the startingstate. The accepting state does not haveany outgoing arrows.all other states have one transition to allother states, including themselves.

(0 ∪ 1)∗

NFA where the transitions are RE, notonly symbols from Σ.some other assumptions for convenience:start state goes to every other state, buthas no incoming states

every state goes to the unique acceptingstate, which is different from the startingstate. The accepting state does not haveany outgoing arrows.all other states have one transition to allother states, including themselves.

(0 ∪ 1)∗

NFA where the transitions are RE, notonly symbols from Σ.some other assumptions for convenience:start state goes to every other state, buthas no incoming statesevery state goes to the unique acceptingstate, which is different from the startingstate. The accepting state does not haveany outgoing arrows.

all other states have one transition to allother states, including themselves.

(0 ∪ 1)∗

NFA where the transitions are RE, notonly symbols from Σ.some other assumptions for convenience:start state goes to every other state, buthas no incoming statesevery state goes to the unique acceptingstate, which is different from the startingstate. The accepting state does not haveany outgoing arrows.all other states have one transition to allother states, including themselves.

(0 ∪ 1)∗

GNFA: Convenient assumptions

NFA where the transitions are RE, notonly symbols from Σ.some other assumptions for convenience:start state goes to every other state, buthas no incoming statesevery state goes to the unique acceptingstate, which is different from the startingstate. The accepting state does not haveany outgoing arrows.all other states have one transition to allother states, including themselves.

Astart

(0 ∪ 1)∗

NFA where the transitions are RE, notonly symbols from Σ.some other assumptions for convenience:start state goes to every other state, buthas no incoming states Xevery state goes to the unique acceptingstate, which is different from the startingstate. The accepting state does not haveany outgoing arrows.all other states have one transition to allother states, including themselves.

start A

(0 ∪ 1)∗

∅∅

NFA where the transitions are RE, notonly symbols from Σ.some other assumptions for convenience:start state goes to every other state, buthas no incoming states Xevery state goes to the unique acceptingstate, which is different from the startingstate. The accepting state does not haveany outgoing arrows. Xall other states have one transition to allother states, including themselves. (X)

start A

(0 ∪ 1)∗

∅∅

for thelast point, add ∅ transitions between any twonon-accepting/starting states that were notpreviously connected (e.g., (B,D))

NFA where the transitions are RE, notonly symbols from Σ.some other assumptions for convenience:start state goes to every other state, buthas no incoming states Xevery state goes to the unique acceptingstate, which is different from the startingstate. The accepting state does not haveany outgoing arrows. Xall other states have one transition to allother states, including themselves. (X)

start A

(0 ∪ 1)∗

∅∅

for thelast point, add ∅ transitions between any twonon-accepting/starting states that were notpreviously connected (e.g., (B,D))

Generalized Nondeterministic Finite Automata

DefinitionA generalized nondeterministic finite automaton (GNFA) is a 5-tuple (Q,Σ, δ, qstart , qaccept)where

1 Q is a finite set of states2 Σ is the input alphabet3 δ : (Q \ {qaccept})× (Q \ {qstart})→ R is the transition function, where R is the set of

all RE’s over Σ,4 qstart is the start state, and5 qaccept is the accept state.

Proof idea: take DFA and transform into a GNFA that accepts the same language. Iterativelyremove (non-starting and non-accepting) states so that the same language is accepted, untilonly the starting and accepting state remain. Then the RE along the transition between thetwo states describes the regular language.

Proof:Given a DFA M, we construct an equivalent GNFA G by adding a new start state qstartwith an ε transition to the old start state q0, as well as a new accepting state qacept , withε transitions from all old accept states.add ∅ transitions for all state pairs that do not have a transition in M.

Recall the “convenient” properties ofGNFA:start state goes to every other state, buthas no incoming statesevery state goes to the unique acceptingstate, which is different from the startingstate. The accepting state does not haveany outgoing arrows.all other states have one transition to allother states, including themselves.

⇒ When removing X, we only need to considersituations like this:

⇓R1 ∪ (R2R

∗3R4)

⇓R1 ∪ (R2R

∗3R4)

⇓R1 ∪ (R2R

∗3R4)

Let’s formalize this! Let us define a procedure CONVERT(G ):1 If k = 2 then G only has one start and one accept state, so return the regular expression

R of the transition connecting them.

2 if k > 2 select a state q′ 6∈ {qaccept , qstart}. Define G ′ = {Q ′,Σ, δ′, qstart , qaccept} withQ ′ = Q \ {q′} and

δ′(qi , qj) = R1 ∪ R2R∗3R4

where R1 = δ(qi , qj), R2 = δ(qi , q′), R3 = δ(q′, q′), R4 = δ(q′, qj), and .

3 Return the result of CONVERT(G ′).4 correctness still remains to be shown! See book for details! (Claim 1.65)

R of the transition connecting them.2 if k > 2 select a state q′ 6∈ {qaccept , qstart}. Define G ′ = {Q ′,Σ, δ′, qstart , qaccept} with

Q ′ = Q \ {q′} andδ′(qi , qj) = R1 ∪ R2R

∗3R4

Q ′ = Q \ {q′} andδ′(qi , qj) = R1 ∪ R2R

∗3R4

3 Return the result of CONVERT(G ′).

4 correctness still remains to be shown! See book for details! (Claim 1.65)

Q ′ = Q \ {q′} andδ′(qi , qj) = R1 ∪ R2R

∗3R4

Example:DFA:

∅ ∅

Example:DFA:

∅ ∅

Example:Remove state X:

∅ ∅

∅ ∪ (10∗1)

Example:Remove state X:

∅ ∅

∅start

∅ ∪ (10∗1)

Example:Remove state Y:

(10∗1)

(10∗1) ∪ (01∗0)

Example:Remove state Y:

(10∗1)

(10∗1) ∪ (01∗0)

Summary

So RE = GNFA = DFA = NFA = Regular languages...

But when is a language nonregular? How can we check?⇒ Pumping Lemma!

Summary

So RE = GNFA = DFA = NFA = Regular languages...But when is a language nonregular? How can we check?

⇒ Pumping Lemma!

Summary

So RE = GNFA = DFA = NFA = Regular languages...But when is a language nonregular? How can we check?⇒ Pumping Lemma!

Pumping Lemma

DFAs only have finite memory, aka states.

Pumping lemma gives a pumping length: if a string is longer than the pumping length, itcan be pumped, i.e., there is a substring that can be repeated arbitrarily often such thatthe string remains in the languageIf a DFA has p states, and a string has length ≥ p, then the accepting path in the DFAmust visit at least p + 1 states. In other words, at least one state appears twice. ⇒ loop!This loop can be repeated while staying in the language.

Pumping Lemma

DFAs only have finite memory, aka states.Pumping lemma gives a pumping length: if a string is longer than the pumping length, itcan be pumped, i.e., there is a substring that can be repeated arbitrarily often such thatthe string remains in the language

If a DFA has p states, and a string has length ≥ p, then the accepting path in the DFAmust visit at least p + 1 states. In other words, at least one state appears twice. ⇒ loop!This loop can be repeated while staying in the language.

Pumping Lemma

DFAs only have finite memory, aka states.Pumping lemma gives a pumping length: if a string is longer than the pumping length, itcan be pumped, i.e., there is a substring that can be repeated arbitrarily often such thatthe string remains in the languageIf a DFA has p states, and a string has length ≥ p, then the accepting path in the DFAmust visit at least p + 1 states. In other words, at least one state appears twice. ⇒ loop!This loop can be repeated while staying in the language.

Pumping Lemma - Example

astart

Language (10∗1) ∪ (01∗0)

DFA has 4 statesconsider string 10001, length 5⇒ path must contain a loop (in this case,at node b)

astart

Language (10∗1) ∪ (01∗0)

astart

Language (10∗1) ∪ (01∗0)

DFA has 4 states

consider string 10001, length 5⇒ path must contain a loop (in this case,at node b)

astart

Language (10∗1) ∪ (01∗0)

DFA has 4 statesconsider string 10001, length 5

⇒ path must contain a loop (in this case,at node b)

astart

Language (10∗1) ∪ (01∗0)

astart

Language 1(010)∗1DFA has 5 statesconsider string 10101, length 5⇒ path must contain a loop (in this case,at nodes b,d,e)⇒ 10100101 is also a word!

astart

Language 1(010)∗1

DFA has 5 statesconsider string 10101, length 5⇒ path must contain a loop (in this case,at nodes b,d,e)⇒ 10100101 is also a word!

astart

Language 1(010)∗1DFA has 5 states

consider string 10101, length 5⇒ path must contain a loop (in this case,at nodes b,d,e)⇒ 10100101 is also a word!

astart

Language 1(010)∗1DFA has 5 statesconsider string 10101, length 5

⇒ path must contain a loop (in this case,at nodes b,d,e)⇒ 10100101 is also a word!

astart

Language 1(010)∗1DFA has 5 statesconsider string 10101, length 5⇒ path must contain a loop (in this case,at nodes b,d,e)

⇒ 10100101 is also a word!

astart

Language 1(010)∗1DFA has 5 statesconsider string 10101, length 5⇒ path must contain a loop (in this case,at nodes b,d,e)⇒ 10100101 is also a word!

Pumping Lemma

Lemma (Pumping Lemma)

If A is a regular language, then there is a number p, called the pumping length, where if w is aword in A of length ≥ p then w can be divided into three parts, w = xyz , such that

1 xy iz ∈ A for every i ≥ 0,2 |y | > 0,3 |xy | ≤ p.

Pumping Lemma

Proof: We formalize our intuition.Let M = (Q.Σ, δ, q0,F ) be a DFA, A = L(M) the language accepted by M, and p be thenumber of states in M.

Let w = w1 · · ·wn be a word in A of length n ≥ p. Since w ∈ A, it is accepted by M, i.e.,there exists a sequence of states s1, s2, . . . sn+1 of length n + 1, where sn+1 is an acceptstate and δ(si ,wi+1) = si+1.

Pumping Lemma

Proof: We formalize our intuition.Let M = (Q.Σ, δ, q0,F ) be a DFA, A = L(M) the language accepted by M, and p be thenumber of states in M.Let w = w1 · · ·wn be a word in A of length n ≥ p. Since w ∈ A, it is accepted by M, i.e.,there exists a sequence of states s1, s2, . . . sn+1 of length n + 1, where sn+1 is an acceptstate and δ(si ,wi+1) = si+1.

Pumping Lemma

Let w = w1 · · ·wn be a word in A of length n ≥ p. Since w ∈ A, it is accepted by M, i.e.,there exists a sequence of states s1, s2, . . . sn+1 of length n + 1.

Since n + 1 ≥ p + 1, one state must occur twice within the first p + 1 elements of thesequence (pigeonhole pricniple).Let these occurences be sj and sl . Since these occur in the first p + 1 elements of thesequence, we have l ≤ p + 1.

Pumping Lemma

Let w = w1 · · ·wn be a word in A of length n ≥ p. Since w ∈ A, it is accepted by M, i.e.,there exists a sequence of states s1, s2, . . . sn+1 of length n + 1.Since n + 1 ≥ p + 1, one state must occur twice within the first p + 1 elements of thesequence (pigeonhole pricniple).

Let these occurences be sj and sl . Since these occur in the first p + 1 elements of thesequence, we have l ≤ p + 1.

Pumping Lemma

Let w = w1 · · ·wn be a word in A of length n ≥ p. Since w ∈ A, it is accepted by M, i.e.,there exists a sequence of states s1, s2, . . . sn+1 of length n + 1.Since n + 1 ≥ p + 1, one state must occur twice within the first p + 1 elements of thesequence (pigeonhole pricniple).Let these occurences be sj and sl . Since these occur in the first p + 1 elements of thesequence, we have l ≤ p + 1.

Pumping Lemma

Let these occurences be sj and sl . Since these occur in the first p + 1 elements of thesequence, we have l ≤ p + 1.

define x = w1 · · ·wj−1, y = wj · · ·wl−1, z = wl · · ·wn.Then |y | > 0 and |xy | ≤ p.

Pumping Lemma

Let these occurences be sj and sl . Since these occur in the first p + 1 elements of thesequence, we have l ≤ p + 1.define x = w1 · · ·wj−1, y = wj · · ·wl−1, z = wl · · ·wn.

Then |y | > 0 and |xy | ≤ p.

Pumping Lemma

Let these occurences be sj and sl . Since these occur in the first p + 1 elements of thesequence, we have l ≤ p + 1.define x = w1 · · ·wj−1, y = wj · · ·wl−1, z = wl · · ·wn.Then |y | > 0 and |xy | ≤ p.

Pumping Lemma

define x = w1 · · ·wj−1, y = wj · · ·wl−1, z = wl · · ·wn.x takes M from s1 to sj , y takes M from sj to sl , z takes M from sl to sn+1.

Thus the word xy iz takes M from the start state s1 to sj , follows the path from sj to sl itimes (recall that sj = sl), then takes M from sl to sn+1.Thus M accepts any word xy iz for i ≥ 0.

Pumping Lemma

define x = w1 · · ·wj−1, y = wj · · ·wl−1, z = wl · · ·wn.x takes M from s1 to sj , y takes M from sj to sl , z takes M from sl to sn+1.Thus the word xy iz takes M from the start state s1 to sj , follows the path from sj to sl itimes (recall that sj = sl), then takes M from sl to sn+1.

Thus M accepts any word xy iz for i ≥ 0.

Pumping Lemma

define x = w1 · · ·wj−1, y = wj · · ·wl−1, z = wl · · ·wn.x takes M from s1 to sj , y takes M from sj to sl , z takes M from sl to sn+1.Thus the word xy iz takes M from the start state s1 to sj , follows the path from sj to sl itimes (recall that sj = sl), then takes M from sl to sn+1.Thus M accepts any word xy iz for i ≥ 0.

Pumping Lemma

define x = w1 · · ·wj−1, y = wj · · ·wl−1, z = wl · · ·wn.x takes M from s1 to sj , y takes M from sj to sl , z takes M from sl to sn+1.Thus the word xy iz takes M from the start state s1 to sj , follows the path from sj to sl itimes (recall that sj = sl), then takes M from sl to sn+1.Thus M accepts any word xy iz for i ≥ 0.

Pumping Lemma

very useful for determining if a language is nonregular

→ find a string with length ≥ p such that the pumping lemma does not holdnot very useful for proving a language is regular→ not an if and only if statement!

Pumping Lemma

very useful for determining if a language is nonregular→ find a string with length ≥ p such that the pumping lemma does not hold

not very useful for proving a language is regular→ not an if and only if statement!

Pumping Lemma

very useful for determining if a language is nonregular→ find a string with length ≥ p such that the pumping lemma does not holdnot very useful for proving a language is regular

→ not an if and only if statement!

Pumping Lemma

very useful for determining if a language is nonregular→ find a string with length ≥ p such that the pumping lemma does not holdnot very useful for proving a language is regular→ not an if and only if statement!

Pumping Lemma - Applied

Let A = {0n1n | n ≥ 0}.

Is A regular?If it is, then the pumping lemma gives us a pumping length p.Let s = 0p1p.

Let A = {0n1n | n ≥ 0}.Is A regular?

If it is, then the pumping lemma gives us a pumping length p.Let s = 0p1p.

Let A = {0n1n | n ≥ 0}.Is A regular?If it is, then the pumping lemma gives us a pumping length p.Let s = 0p1p.

Let A = {0n1n | n ≥ 0}.Let s = 0p1p.

Condition 3 tells us that y consists of only 0s.⇒ then xy iz for i ≥ 2 has more 0s than 1s. Contradiction! ⇒ A is nonregular.

Let A = {0n1n | n ≥ 0}.Let s = 0p1p.Condition 3 tells us that y consists of only 0s.

⇒ then xy iz for i ≥ 2 has more 0s than 1s. Contradiction! ⇒ A is nonregular.

Let A = {0n1n | n ≥ 0}.Let s = 0p1p.Condition 3 tells us that y consists of only 0s.⇒ then xy iz for i ≥ 2 has more 0s than 1s. Contradiction! ⇒ A is nonregular.

Even if a language is nonregular, it might contain strings for which the pumping lemma istrue!

We have to be careful!

Even if a language is nonregular, it might contain strings for which the pumping lemma istrue!We have to be careful!

|w | ≥ p,w = xyz , s.t.1 xy iz ∈ A for every i ≥ 0,2 |y | > 0,3 |xy | ≤ p.

Let B = {ω |ω contains an equal number of 0s and 1s}.Let w = (01)p.

x = ε, y = 01, z = (01)p−1

all conditions are met!

Let B = {ω |ω contains an equal number of 0s and 1s}.Let w = (01)p.x = ε, y = 01, z = (01)p−1

Let B = {ω |ω contains an equal number of 0s and 1s}.Let s = 0p1p.

x = ε, y = 0p1p, z = ε

looks like it can be pumped, but are all conditions met?condition 3 ⇒ y must contain only 0s, so it cannot be pumped⇒ B nonregular!

Let B = {ω |ω contains an equal number of 0s and 1s}.Let s = 0p1p.x = ε, y = 0p1p, z = ε

looks like it can be pumped

, but are all conditions met?condition 3 ⇒ y must contain only 0s, so it cannot be pumped⇒ B nonregular!

looks like it can be pumped, but are all conditions met?

condition 3 ⇒ y must contain only 0s, so it cannot be pumped⇒ B nonregular!

looks like it can be pumped, but are all conditions met?condition 3 ⇒ y must contain only 0s, so it cannot be pumped

⇒ B nonregular!

A = {0n1n | n ≥ 0}.B = {ω |ω contains an equal number of 0s and 1s}Another way of showing B is nonregular is to reduce it to the nonregularity of A:

regular languages are closed under intersectionand A = B ∩ 0∗1∗

if B is regular and since 0∗1∗ is regular, then A must be as well, contradiction!

A = {0n1n | n ≥ 0}.B = {ω |ω contains an equal number of 0s and 1s}Another way of showing B is nonregular is to reduce it to the nonregularity of A:regular languages are closed under intersection

and A = B ∩ 0∗1∗

A = {0n1n | n ≥ 0}.B = {ω |ω contains an equal number of 0s and 1s}Another way of showing B is nonregular is to reduce it to the nonregularity of A:regular languages are closed under intersectionand A = B ∩ 0∗1∗

if B is regular and since 0∗1∗ is regular, then A must be as well

, contradiction!

Summary

regular expressions are shorthand notations for languages

RE = GNFA = DFA = NFA, i.e., regular expressions are shorthand for regular languagesproof involved transforming a DFA to a GNFA then reducing the number of states to 2while accepting the same language→ the regular expressions describe the paths in the DFAevery regular language has a pumping lengthuseful for determining if a language is nonregular

Summary

regular expressions are shorthand notations for languagesRE = GNFA = DFA = NFA, i.e., regular expressions are shorthand for regular languages

proof involved transforming a DFA to a GNFA then reducing the number of states to 2while accepting the same language→ the regular expressions describe the paths in the DFAevery regular language has a pumping lengthuseful for determining if a language is nonregular

Summary

regular expressions are shorthand notations for languagesRE = GNFA = DFA = NFA, i.e., regular expressions are shorthand for regular languagesproof involved transforming a DFA to a GNFA then reducing the number of states to 2while accepting the same language

→ the regular expressions describe the paths in the DFAevery regular language has a pumping lengthuseful for determining if a language is nonregular

Summary

regular expressions are shorthand notations for languagesRE = GNFA = DFA = NFA, i.e., regular expressions are shorthand for regular languagesproof involved transforming a DFA to a GNFA then reducing the number of states to 2while accepting the same language→ the regular expressions describe the paths in the DFA

every regular language has a pumping lengthuseful for determining if a language is nonregular

Summary

regular expressions are shorthand notations for languagesRE = GNFA = DFA = NFA, i.e., regular expressions are shorthand for regular languagesproof involved transforming a DFA to a GNFA then reducing the number of states to 2while accepting the same language→ the regular expressions describe the paths in the DFAevery regular language has a pumping length

useful for determining if a language is nonregular

Summary

regular expressions are shorthand notations for languagesRE = GNFA = DFA = NFA, i.e., regular expressions are shorthand for regular languagesproof involved transforming a DFA to a GNFA then reducing the number of states to 2while accepting the same language→ the regular expressions describe the paths in the DFAevery regular language has a pumping lengthuseful for determining if a language is nonregular

2. RegularExpressionsandNonregularlanguages DanielLupp€¦ · Regular Expressions...

Documents

Transcript of 2. RegularExpressionsandNonregularlanguages DanielLupp€¦ · Regular Expressions...

Digital Signatures...Chameleon hash functions (Deﬁnition, recap) A chameleon hash function CH consists of two PPT algorithms (Gen CH,TrapColl):•Gen CH(1k) outputs ch: M×R→Nand

Regular expressions and Kleeneâ€™s theorem

Chapter Seven: Regular Expressions · 2015-08-11 · Regular Expressions • A regular expression is a string r that denotes a language L(r) over some alphabet Σ • Regular expressions

On Reporting Expressions of Jane Austen's Works C …harp.lib.hiroshima-u.ac.jp/it-hiroshima/file/4179/...On Reporting Expressions of Jane Austen's Works (I) Table 1. Distribution

Generalized Social Marginal Welfare Weights for Optimal Tax ......R i w iu ci dT(z i) = R i g idT(z i). ChangeintaxpaidperpersonisdT(z i)+T0(z i)dz i. Deﬁnition AreformdT(z) isbudgetneutralifandonlyif

Expressions régulières - Théorie des langages et de la compilation … · 2009-10-14 · Expressions r eguli eres Th eorie des langages et de la compilation Travaux pratiques Nicolas

1 Expressions régulières et hash tables Expressions rationnelles/régulières Hash Tables.

Regular expressions to fsms \hardware and software techniques Paul Cockshott.

Simplifying expressions, solving, domain and range

Regular Expressions - Cornell University€¦ · Regular Expressions CS 2800: Discrete Structures, Fall 2014 Sid Chaudhuri. Regular expressions (“regex”-es) are defned inductively

Languages and Regular expressionsalko5368/lecturesCSCI5444/lec03.pdf · Regular Expressions •In arithmetic, we can use operations ×,+to build up expressions such as (5+3)×4 •Similarly,

Multi-word expressions in Modern Greek: present and future · Multi-word expressions in Modern Greek Definitions A multi-word expression is a sequence of words which constitutes a

Lambda Calculus - York University · Lambda expressions are a direct analogue of λ-calculus expressions! » They are the basis of Lisp functions – a modiﬁed syntax to simplify

Regular expressions to fsms

Lambda Expressions in Java 8

Regular Languages and Expressions

πEQUALITY, EXPRESSIONS, EQUATIONS, AND INEQUALITIESalgebra.wceruw.org/documents/EEEI_Learning Goals.pdf · πEQUALITY, EXPRESSIONS, EQUATIONS, ... over the grades 3-8 progression.

12-Dec-15 Regular Expressions. About “Regular” Expressions In a theory course you should have learned about regular expressions Regular expressions describe.

x potential velocity potential - DAMTP · [As a consistency check, you can verify that these expressions for the spherical components of r˚ correspond to a linear combination of

Polynomial Time Hierarchy - University of Washingtoncourses.cs.washington.edu/courses/cse532/08sp/all.pdf1.1.1 Alternative deﬁnition in terms of oracle TMs Deﬁnition 1.3 An oracle