This document provides an introduction to regular expressions and regular languages. It defines the key operations used in regular expressions: union, concatenation, and Kleene star. It explains how regular expressions can be converted into finite state automata and vice versa. Examples of regular expressions are provided. The document also defines regular languages as those languages that can be accepted by a deterministic finite automaton. It introduces the pumping lemma as a way to determine if a language is not regular. Finally, it includes some practical activities for readers to practice converting regular expressions to automata and writing regular expressions.

1. Regular Expressions
& Regular Languages
slideshare: http://www.slideshare.net/marinasantini1/regular-expressions-and-regular-languages
Mathematics for Language Technology
http://stp.lingfil.uu.se/~matsd/uv/uv15/mfst/
Last Updated 6 March 2015
Marina Santini
santinim@stp.lingfil.uu.se
Department of Linguistics and Philology
Uppsala University, Uppsala, Sweden
Spring 2015
1

2. Acknowledgements
 Several
slides
borrowed
from
Jurafsky
and
Mar6n
(2009).
 Prac6cal
ac6vi6es
by
Mats
Dahllöf
and
Jurafsky
and
Mar6n
(2009).
2

3. Reading
 Required Reading:
 E&G (2013): Ch. 9 (pp. 252-256)
 Compendium (3): 7.2, 7.3, 8.2.3
 Mats Dahllöf: Reguljära uttryck
• http://stp.lingfil.uu.se/~matsd/uv/uv14/mfst/dok/oh6.pdf
 Further Reading:
 Chapters
2
in
Jurafsky
D.
&
Mar6n
J.
(2009)
Speech
and
Language
Processing:
An
introduc5on
to
natural
language
processing,
computa5onal
linguis5cs,
and
speech
recogni5on.
Online
draG
version:
hIp://stp.lingfil.uu.se/~san6nim/ml/2014/
JurafskyMar6nSpeechAndLanguageProcessing2ed_draG%202007.pdf
3

4. Outline
 Regular Expressions
 Regular Languages
 Practical Activities
 (Pumping Lemma)
4

5. 5
Regular Expressions
Definitions
Equivalence to Finite Automata

6. 6
Regular Expressions and Text Searching
 Everybody does it
 Emacs, vi, perl, grep, etc..
 Regular expressions are a compact
textual representation of a set of strings
representing a language.

7. 7
Example
 Find all the instances of the word “the”
in a text.
 /the/
 /[tT]he/
 /b[tT]heb/

8. 8
Errors
 The process we just went through was
based on two fixing kinds of errors
 Matching strings that we should not have
matched (there, then, other)
• False positives (Type I)
 Not matching things that we should have
matched (The)
• False negatives (Type II)

9. 9
Errors
 Reducing the error rate for an application
often involves two antagonistic efforts:
 Increasing accuracy, or precision, (minimizing
false positives)
 Increasing coverage, or recall, (minimizing
false negatives).

10. 10
REs: What are they?
 Regular expressions describe
languages by an algebra.

11. Link: https://www.youtube.com/watch?v=eOfMcdeyrMU
11

12. DFA
12

13. Converting the regular expression
(a|b)* to a DFA
13

14. Converting the regular expression
(a*|b*)* to a DFA
14

15. Converting the regular expression
ab(a|b)* to a DFA
15

16. Remember Jeff Ullman video?
16

17. 17
Operations on Languages
 REs use three operations:
 union
 concatenation
 Kleene star (*) [cleany star]

18. Union ∪ (aka: disjunction, OR, |, +)
 The union of languages is the usual
thing, since languages are sets.
 Example: {01,111,10}∪{00, 01} =
{01,111,10,00}.
18
01 happens to be in both
sets, so it will be once in the
union

19. 19
Concatenation: represented by juxtaposition (no punctuation)
or middle dot ( · )
 The concatenation of languages
L and M is denoted LM.
 It contains every string wx such
that w is in L and x is in M.
 Example: {01,111,10}{00, 01}
= {0100, 0101, 11100, 11101,
1000, 1001}. In the example, we take 01 from the first language,
and we concatenate it with 00 in the second language.
That gives us 0100.
We then take 01 from the first language again, and we
concatenate it with 01 in the second language, and that
gives us 0101.
Then we take 111 from the first language and we
concatenated it with 00 in the second language and
this gives us 11100
…. and so on.

20. 20
Kleene Star: represented by an asterisk
aka star (*)
 If L is a language, then L*, the Kleene
star or just “star,” is the set of strings
formed by concatenating zero or more
strings from L, in any order.
 L* = {ε} ∪ L ∪ LL ∪ LLL ∪ …
 Example: {0,10}* = {ε, 0, 10, 00, 010,
100, 1010,…}
If you take no strings from L, that would give you the empty string.

21. IMPORTANT!
 FROM NOW ON, LET’S STICK TO THE
FOLLOWING CONVENTIONS (OTHERWISE WE
WILL BE CONFUSED):
 Union ∪ (aka: disjunction, OR) represented by: | or +
 Concatenation: represented by juxtaposition (= no
punctuation) or middle dot ( · )
 Kleene Star: represented by *
21

22. 22
Precedence of Operators
 Parentheses may be used wherever
needed to influence the grouping of
operators.
 Order of precedence is * (highest), then
concatenation, then + (lowest).
Remember: + = union/disjunction

23. 23
Examples: REs
1. L(01) = {01}.
2. L(01+0) = {01, 0}.
3. L(0(1+0)) = {01, 00}.
 Note order of precedence of
operators.
4. L(0*) = {ε, 0, 00, 000,… }.
5. L((0+10)*(ε+1)) = all strings
of 0s and 1s without two
consecutive 1s.
1) The regular expression 01 represents the
concatenation of the language consisting of one
string, 0 and the language consisting of one string, 1.
The result is the language containing the one string
01.
2) The language of 01+0 is the union of the language
containing only string 01 and the language containing
only string 0.
3) The language of 0 concatenated with 1+0 is the
two strings 01 and 00. Notice that we need
parentheses to force the + to group first. Without
them, since concatenation takes precedence over +,
we get the interpretation in the second example.
4) The language of 0* is the star of the language
containing only the string 0. This is all strings of 0’s,
including the empty string.
5) This example denotes the language with all strings
of 0s and 1s without two consecutive 0s. To see why
this works, in every such string, each 1 is either
followed immediately by a 0, or it comes at the end of
the string. (0+10)* denotes all strings in which every
1 is followed by a 0. These strings are surely in the
language we want. But we also want these strings
followed by a final 1. Thus, we concatenate the
language of (0+10)* with epsilon+1. This
concatenation gives us all the strings where 1s are
followed by 0s, plus all those strings with an
additional 1 at the end.

24. 24
Equivalence of REs and Finite
Automata
 For every RE, there is a finite automaton
that accepts the same language.
 And we need to show that for every finite
automaton, there is a RE defining its
language.

25. 25
Summary
Automata and regular expressions define
exactly the same set of languages: the
regular languages.

26. REGULAR LANGUAGES
26

27. 27
The Chomsky Hierachy
Regular
(DFA)
Context-
free
(PDA)
Context-
sensitive
(LBA)
Recursively-
enumerable
(TM)
• Hierarchy of classes of formal languages
One language is of greater generative power or complexity than another if
it can define a language that other cannot define. Context-free grammars
are more powerful that regular grammars

28. 28
Regular Languages
 A language L is regular if it is the
language accepted by some DFA.
 Note: the DFA must accept only the strings
in L, no others.
 Some languages are not regular.

29. Only languages that meet the following criteria
are regular languages:
29

30.  Regular language derive their name from the fact that the
strings they recognize are (in a formal computer science sense)
“regular.”
 This implies that there are certain kinds of strings that it will be
very hard, if not impossible, to recognize with regular
expressions, especially nested syntactic structures in natural
language.
30

31. Formal languages vs regular
languages
 A formal language is a set of strings,
each string composed of symbols from
a finite set called an alphabet.
 Ex: {a,b!}
 Formal languages are not the same as
regular languages….
31

32. 32
But Many Languages are Regular
 They appear in many contexts and have
many useful properties.

33. How to tell if a language is not regular
 The most common way to prove that a
language is regular is to build a regular
expression for the language.
33

34. Pumping Lemma
34

35. Prac6cal
Ac6vity
1
 The
language
L
contains
all
strings
over
the
alphabet
{a,b}
that
begin
with
a
and
end
with
b,
ie:
 Write a regular expression that defines
the language L.
35

36. Practical Activity 1:
Possible Solution
36

37. Your Solutions
37
In between the concatenation of a
and b there must be 0 or more
unions (disjuctions) of a and b.
Reference: slides 17-22

38. Practical Activity 2
 Draw a deterministic finite-state automaton
that accepts the following regular expression:
38
( (ab) | c)*
Alternative notation style:
ie: 0 or more occurences of
the disjunction ab | c
Test the
automaton with
these legal strings
in the language :
0
abc
a
ab
cccabc
cbacccabababccc
….

39. Practical Activity 2:
Possible Correct Solution
39
Having the initial state as a final state gives us the empty string as an element in the language.

40. Your solutions (1): when we interpret ”+” as
disjunction, these solutions are wrong because
”c” happens only after ”a” and ”b”…
40
Test
these
automata
with the
string on
slide 35

41. Your solutions (2): same as
previous slide. In addition, here no
final states are shown…
41
Test
these
automata
with the
string on
slide 35

42. Practical Activity 3
 Construct a grep regular expression that
matches patterns containing at least one
“ab” followed by any number of bs.
 Construct a grep regular expression that
matches any number between 1000 and
9999.
42

43. Practical Activity 3:
Possible Solutions
 grep ‘(ab)+b*’
 [1-9][0-9]{3}
43

44. Exercises: E&G (2013)
 Övning 9.40
 Optional: as many as you can
 AGer
having
completed
the
exercises,
check
out
the
solu6ons
at
the
end
of
the
book.
44

45. The End
45