1 Regular Languages, Regular Operations September 11, 2001

2 Agenda Today Regular languages  Finite languages are regular Regular operations on languages  Union (  )  Concatenation (  )  Kleene star (*) For next time: Read 1.3 and handout on minimization Thursday, 9/20 (revised ): HW1 collected

3 Definition of Regular Language Recall the definition of a regular language: DEF: The language accepted by an FA M is the set of all strings which are accepted by M and is denoted by L (M). Would like to understand what types of languages are regular. Languages of this type are amenable to super-fast recognition of their elements Would be nice to know for example, which of the following are regular:

4 Language Examples Unary prime numbers: { 11, 111, 11111, , , … } = {1 2, 1 3, 1 5, 1 7, 1 11, 1 13, … } = { 1 p | p is a prime number } Unary squares: { , 1, 1 4, 1 9, 1 16, 1 25, 1 36, … } = { 1 n | n is a perfect square } Palindromic bit strings: { , 0, 1, 00, 11, 000, 010, 101, 111, …} = {x  {0,1}* | x = x R } o Will explore whether or not these are regular in future.

5 Finite Languages All the previous examples had the following property in common: infinite cardinality NOTE: The strings which made up the language were finite (as they always will be in this course); however, the collection of such strings was infinite. Before looking at infinite languages, should definitely look at finite languages.

6 Languages of Cardinality 1 Q: Is the singleton language containing one string regular? For example, is { banana } regular?

7 Languages of Cardinality 1 A: Yes. Q: What’s, wrong with this example?

8 Languages of Cardinality 1 A: Nothing, really. This an example of a nondeterministic FA. This turns out to be the most concise way to encapsulate the language { banana } But we will deal with nondeterminism in coming lectures. So: Q: Is there a way of fixing this and making it deterministic?

9 Languages of Cardinality 1 A: Yes, just add a fail state q7; I.e., put a state that sucks in all strings different from “banana” for all eternity –unless they happen to be the “banana” prefixes { , b, ba, ban, bana, banan}.

10 ABCEZ Goes Bananas Show how ABCEZ works on this example.

11 Two Strings Q: How about two strings? For example { banana, nab } ?

12 Two Strings A: Just add another route:

13 Arbitrary Finite Number of Strings Q1: How about more? For example { banana, nab, ban, babba } ? Q2: Or less (the empty set): Ø = {} ?

14 Arbitrary Finite Number of Strings A1:

15 Arbitrary Finite Number of Strings: Empty Language A2: Build a 1-state automaton whose accept states set F is empty!

16 Arbitrary Finite Number of Strings THM: All finite languages are regular. Proof : Can always construct a tree whose leaves are word-ending. In our example the tree is: Now make word endings into accept states, add a fail sink-state and add links to the fail state to finish the construction. b a a b a n b a n b a n

17 Infinite Cardinality Q: Are all regular languages finite?

18 Infinite Cardinality A: No! Many infinite languages are regular. Common Mistake 1: The strings of regular languages are finite, therefore the regular languages must be finite. Common Mistake 2: Regular languages are –by definition– accepted by finite automata, therefore regular languages are finite. Q: Give an example of a infinite but regular language.

19 Infinite Cardinality bit strings with an even number of b’s Simplest example is    many, many more Home exercise: think of a criterion for non- finiteness

20 Regular Operations You may have come across the regular operations when doing advanced searches utilizing programs such as emacs, egrep, perl, python, etc. There are three basic operations we will work with: 1. Union 2. Concatenation 3. Kleene-star And a fourth definable in terms of the previous: 4. Kleene-plus

21 Regular Operations – Summarizing Table OperationSymbolUNIX versionMeaning Union  | match one of the patterns Concatenation  implicit in UNIX match patterns in sequence Kleene- star ** Match pattern 0 or more times Kleene- plus ++ Match pattern 1 or more times

22 Regular operations - Union UNIX: to search for all lines containing vowels in a text one could use the command egrep -i `a|e|i|o|u’ Here the pattern “vowel ” is matched by any line containing one of a, e, i, o or u. Q: What is a string pattern?

23 String Patterns A: A good way to define a pattern is as a set of strings, i.e. a language. The language for a given pattern is the set of all strings satisfying the predicate of the pattern. EG: vowel-pattern = { the set of strings which contain at least one of: a e i o u }

24 UNIX patterns vs. Computability patterns In UNIX, a pattern is implicitly assumed to occur as a substring of the matched strings. In our course, however, a pattern needs to specify the whole string, and not just a substring.

25 Regular operations - Union Computability: union is exactly what we expect. If you have patterns A = {aardvark}, B = {bobcat}, C = {chimpanzee} union the patterns together to get A  B  C = {aardvark, bobcat, chimpanzee}

26 Regular operations - Concatenation UNIX: to search for all consecutive double occurrences of vowels, use: egrep -i `(a|e|i|o|u)(a|e|i|o|u)’ Here the pattern “vowel ” has been repeated. Parentheses have been introduced to specify where exactly in the pattern the concatenation is occurring.

27 Regular operations - Concatenation Computability. Consider the previous result: L = {aardvark, bobcat, chimpanzee} Q: What language results when we concatenate L with itself obtaining L  L ?

28 Regular operations - Concatenation A: L  L = {aardvark, bobcat, chimpanzee}  {aardvark, bobcat, chimpanzee} = {aardvarkaardvark, aardvarkbobcat, aardvarkchimpanzee, bobcataardvark, bobcatbobcat, bobcatchimpanzee, chimpanzeeaardvark, chimpanzeebobcat, chimpanzeechimpanzee} Q1: What is L  ? Q2: What is L  Ø ?

29 Algebra of Languages A1: L  = L. In general,  is the identity in the “algebra” of languages. I.e., if we think of concatenation as being like multiplication,  acts like the number 1. A2: L  Ø = Ø. Opposite to , Ø acts like the number zero obliterating everything it is concatenated with. Note: We can carry on the analogy between numbers and languages. Addition becomes union, multiplication becomes concatenation. This forms a so-called “algebra”.

30 Regular operations – Kleene-* UNIX: search for lines consisting purely of vowels (including the empty line): egrep -i `^(a|e|i|o|u)*$’ NOTE: ^ and $ are special symbols in UNIX regular expressions which respectively anchor the pattern at the beginning and end of a line. The trick above can be used to convert any Computability regular expression into an equivalent UNIX form.

31 Regular operations – Kleene-* Computability: Suppose we have a language B = { ba, na } Q: What is the language B * ?

32 Regular operations – Kleene-* A: B * = { ba, na }*= { , ba, na,  baba, bana, naba, nana,  bababa, babana, banaba, banana,  nababa, nabana, nanaba, nanana,  babababa, bababana, … }

33 Regular operations – Kleene-+ Kleene-+ is just like Kleene-* except that the pattern is forced to occur at least once. UNIX: search for lines consisting purely of vowels (not including the empty line): egrep -i `^(a|e|i|o|u)+$’ Computability: B + = { ba, na } + = {ba, na,  baba, bana, naba, nana,  bababa, babana, banaba, banana,  nababa, nabana, nanaba, nanana,  babababa, bababana, … }

34 Generating the Regular Languages The real reason that regular languages are called regular is the following: THM: The regular languages are all those languages which can be generated starting from the finite languages by applying the regular operations. This will be proved in the coming lectures. Q: Can we start with even more basic languages than arbitrary finite languages?

35 Generating the Regular Languages A: Yes. We can start with languages consisting of single strings which are themselves just a single character. These are the “atomic” regular languages. EG: To generate the finite language L = { banana, nab } we can start with the atomic languages A = {a}, B = {b}, N = {n}. Then we can express L as: L = (B  A  N  A  N  A)  (N  A  B )

36 Blackboard Exercises Express the DFA patterns from the previous board-exercises using regular operations in both UNIX-style and Computability-style.