Regular Expression to Finite Automata
- 1. Myself Archana R Assistant Professor In Department Of Computer Science SACWC. I am here because I love to give presentations. COMPILER DESIGN
- 2. REGULAR EXPRESSION TO FINITE AUTOMATA
- 3. Regular Expressions: We use regular expressions to describe tokens of a programming language. • A regular expression is built up of simpler regular expressions (using defining rules). • Each regular expression denotes a language. • A language denoted by a regular expression is called as a regular set.
- 4. Regular expressions over alphabet Language it denotes: [r1) | (r2) (r1) (r2) (r)* (r) L(r1) L(r2) L(r1) L(r2) (L(r))* L(r) Regular Expressions (Rules) Reg. Expr
- 5. Regular Expressions • We may remove parentheses by using precedence rules. – * highest – concatenation next – | lowest • ab*|c means (a(b)*)|(c)
- 6. Example: – = {0,1} – 0|1 => {0,1} – (0|1)(0|1) => {00,01,10,11} – 0* => { ,0,00,000,0000,....} – (0|1)* => all strings with 0 and 1, including the empty string
- 7. • To write regular expression for some languages can be difficult, because their regular expressions can be quite complex. In those cases, we may use regular definitions. • We can give names to regular expressions, and we can use these names as symbols to define other regular expressions. • A regular definition is a sequence of the definitions of the form: d1 r1 (where di is a distinct name and) d2 r2 (ri is a regular expression over symbols in) . {d1,d2,...,di-1} dn r n basic symbols previously defined names REGULAR DEFINITION:
- 8. Ex: Identifiers in Pascal letter A | B | ... | Z | a | b | ... | z digit 0 | 1 | ... | 9 id letter (letter | digit ) * –If we try to write the regular expression representing identifiers without using regular definitions, that regular expression will be complex. (A|...|Z|a|...|z) ( (A|...|Z|a|...|z) | (0|...|9) ) * Ex: Unsigned numbers in Pascal digit 0 | 1 | ... | 9 digits digit + opt-fraction ( . digits ) ? opt-exponent ( E (+|-)? digits)? unsigned-num digits opt- fraction opt-exponent
- 9. FINITE AUTOMATA • Both deterministic and non-deterministic finite automaton recognize regular sets. • Which one? – deterministic – faster recognizer, but it may take more space – non-deterministic – slower, but it may take less space – Deterministic automatons are widely used lexical analyzers. • First, we define regular expressions for tokens; Then we convert them into a DFA to get a lexical analyzer for our tokens. – Algorithm1: Regular Expression NFA DFA (two steps: first to NFA, then to DFA) – Algorithm2: Regular Expression DFA (directly convert a regular expression into a DFA) •A recognizer for a language is a program that takes a string x, and answers “yes” if x is a sentence of that language, and “no” otherwise. • We call the recognizer of the tokens as a finite automaton. • A finite automaton can be: deterministic(DFA) or non-deterministic (NFA) • This means that we may use a deterministic or non-deterministic automaton as a lexical analyzer.
- 10. Non-Deterministic Finite Automaton (NFA) • A non-deterministic finite automaton (NFA) is a mathematical model that consists of: – S - a set of states – - a set of input symbols (alphabet) – move – a transition function move to map state- symbol pairs to sets of states. – s0 - a start (initial) state – F – a set of accepting states (final states)
- 11. • - transitions are allowed in NFAs. In other words, we can move from one state to another one without consuming any symbol. •A NFA accepts a string x, if and only if there is a path from the starting state to one of accepting states such that edge labels along this path spell out x.
- 12. Transition graph of the NFA The language recognized by this NFA is (a|b) * a b 0 is the start state s0 {2} is the set of final states F . = {a,b} S = {0,1,2} start a a 1 b b 0 2
- 13. ExecutingNFA •Problem:How to execute NFA efficiently? "strings accepted are those for which there is some corresponding path fromat art state to an accept state“ •Conclusion:Search all paths in graph consistent With the string. •Idea:searchpathsinparallel •Keep track of subset of NFA states that search could be in after seeing string prefix. •"Multiple fingers"pointing to graph.
- 14. • A Deterministic Finite Automaton (DFA) is a special form of a NFA. • no state has - transition • for each symbol a and state s, there is at most one labeled edge a leaving s. i.e. transition function is from pair of state-symbol to state (not set of states) DETERMINISTIC FINITE AUTOMATON(DFA): a b 0 2 b 1 a a b The language recognized by this DFA is also (a|b) * a b
- 15. Converting A Regular Expression into A NFA (Thomson’s Construction) • This is one way to convert a regular expression into a NFA. • There can be other ways (much efficient) for the conversion. • Thomson’s Construction is simple and systematic method. It guarantees that the resulting NFA will have exactly one final state, and one start state. • Construction starts from simplest parts (alphabet symbols). To create a NFA for a complex regular expression, NFAs of its sub-expressions are combined to create its NFA, • To recognize an empty string • To recognize a symbol a in the alphabet • If N(r1) and N(r2) are NFAs for regular expressions r1 and r2 • For regular expression r1 | r2 NFA for r1 | r2
- 16. Converting a NFA into a DFA: Step 1 Step 2 S0 is the start state of DFA since 0 is a member of S0={0,1,2,4,7} S1 is an accepting state of DFA since 8 is a member of S1 = {1,2,3,4,6,7,8} a b b S0 s1 S2 a b a
- 17. DFAvs.NFA •DFA: Action of automaton one achin put symbolically determined. •obvious table-driven implementation. •NFA: •Automaton may have choice one ach step •Automaton accepts a string if there is anyway to make choices to arrive at accepting state/every path from start state to an accept state is a string accepted by automaton. •Not obvious how to implement efficiently!
- 18. Convert A Regular Expressions Directly To DFA: • We may convert a regular expression into a DFA (without creating a NFA first). •First we augment the given regular expression by concatenating it with special symbol #. • Then, we create a syntax tree for this augmented regular expression. •In this syntax tree, all alphabet symbols (plus # and the empty string) in the augmented regular expression will be on the leaves, and all inner nodes will be the operators in that augmented regular expression. •Then each alphabet symbol (plus #) will be numbered (position numbers).
- 19. DFA Minimization: • DFA construction can produce large DFA with many states. • Lexer generators perform additional phase of DFA Minimization to reduce to minimum possible size . What does this DFA do? - Can it be simplified. 1
- 20. Automatic Scanner Construction: To convert a specification into code. •Write down the RE for the input language. •Build a big NFA. •Build the DFA that simulates the NFA. •Systematically shrink the DFA. •Turn it into code. Scanner generators: •Lex and flex work along these lines. •Algorithm sare well known and understood. •Key issue is interface to the parser.
- 21. Thank you!