2. Lexical Analysis. Oscar Nierstrasz

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1 2. Lexicl Anlysis Oscr Nierstrsz Thnks to Jens Plserg nd Tony Hosking for their kind permission to reuse nd dpt the CS132 nd CS502 lecture notes.

2 Rodmp > Introduction > Regulr lnguges > Finite utomt recognizers > From RE to DFAs nd ck gin > Limits of regulr lnguges See, Modern compiler implementtion in Jv (Second edition), chpter 2. 2

3 Rodmp > Introduction > Regulr lnguges > Finite utomt recognizers > From RE to DFAs nd ck gin > Limits of regulr lnguges 3

4 Lexicl Anlysis Source Code Scnner Tokens Prser IR errors 1. Mps sequences of chrcters to tokens 2. Elimintes white spce (ts, lnks, comments etc.) x = x + y <ID,x> <EQ> <ID,x> <PLUS> <ID,y> The string vlue of token is lexeme. 4

5 How to specify rules for token clssifiction? A scnner must recognize vrious prts of the lnguge s syntx Some prts re esy: White spce <ws> ::= <ws> <ws> \t \t Keywords nd opertors specified s literl ptterns: do, end Comments opening nd closing delimiters: /* */ 5

6 Specifying ptterns Other prts re hrder: Identifiers lphetic followed y k lphnumerics (_, $, &, )) Numers integers: 0 or digit from 1-9 followed y digits from 0-9 decimls: integer. digits from 0-9 rels: (integer or deciml) E (+ or ) digits from 0-9 complex: ( rel, rel ) We need n expressive nottion to specify these ptterns! A key issue is... 6

7 Rodmp > Introduction > Regulr lnguges > Finite utomt recognizers > From RE to DFAs nd ck gin > Limits of regulr lnguges 7

8 Lnguges nd Opertions A lnguge is set of strings Opertion Definition Union L M = { s s L or s M } Conctention LM = { st s L nd t M } Kleene closure Positive closure L* = I=0, L i L + = I=1, L i 8

9 Production Grmmrs > Powerful formlism for lnguge description Non-terminls (A, B) Terminls (,) Production rules (A->A) Strt symol (S0) > Rewriting Recursively enumerle Context sensitive Context free Regulr 9

10 Detil: The Chomsky Hierrchy > Type 0: α β Unrestricted grmmrs generte recursively enumerle lnguges. Miniml requirement for recognizer: Turing mchine. > Type 1: αaβ αγβ Context-sensitive grmmrs generte context-sensitive lnguges, recognizle y liner ounded utomt > Type 2: A γ Context-free grmmrs generte context-free lnguges, recognizle y non-deterministic push-down utomt > Type 3: A nd A B Regulr grmmrs generte regulr lnguges, recognizle y finite stte utomt NB: A is non-terminl; α, β, γ re strings of terminls nd non-terminls 10

11 Grmmrs for regulr lnguges Regulr grmmrs generte regulr lnguges Definition: In regulr grmmr, ll productions hve one of two forms: 1. A A 2. A where A is ny non-terminl nd is ny terminl symol These re lso clled type 3 grmmrs (Chomsky) 11

12 Regulr lnguges cn e descried y Regulr Expressions Regulr expressions (RE) over n lphet Σ: 1. ε is RE denoting the set {ε} 2. If Σ, then is RE denoting {} 3. If r nd s re REs denoting L(r) nd L(s), then: > (r) (s) is RE denoting L(r) L(s) > (r)(s) is RE denoting L(r)L(s) > (r)* is RE denoting L(r)* We dopt precedence for opertors: Kleene closure, then conctention, then lterntion s the order of precedence. For ny RE r, there exists grmmr g such tht L(r) = L(g) 12

13 Exmples Let Σ = {,} > denotes {,} > ( ) ( ) denotes {,,,} > * denotes {ε,,,, } > ( )* denotes the set of ll strings of s nd s (including ε) > Universit(ä e)t Bern(e )... 13

14 Algeric properties of REs r s = s r r (s t) = (r s) t r (st) = (rs)t r(s t) = rs rt (s t)r = sr tr εr = r rε = r is commuttive is ssocitive conctention is ssocitive conctention distriutes over ε is the identity for conctention r * = (r ε)* ε is contined in * r ** = r* * is idempotent 14

15 Exmples of using REs to specify lexicl ptterns identifiers letter ( c z A B C Z ) digit ( ) id letter ( letter digit )* numers integer (+ ε) (0 ( ) digit * ) deciml integer. ( digit )* rel ( integer deciml ) E (+ ) digit * complex ( rel, rel ) 15

16 Rodmp > Introduction > Regulr lnguges > Finite utomt recognizers > From RE to DFAs nd ck gin > Limits of regulr lnguges 16

17 Recognizers letter ( c z A B C Z ) digit ( ) id letter ( letter digit )* From regulr expression we cn construct deterministic finite utomton (DFA) 17

18 Code for the recognizer 18

19 Tles for the recognizer Two tles control the recognizer chr_clss chr -z A-Z 0-9 other vlue letter letter digit other next_stte letter 1 1 digit 3 1 other 3 2 To chnge lnguges, we cn just chnge tles 19

20 Automtic construction > Scnner genertors utomticlly construct code from regulr expression-like descriptions construct DFA use stte minimiztion techniques emit code for the scnner (tle driven or direct code ) > A key issue in utomtion is n interfce to the prser > lex is scnner genertor supplied with UNIX emits C code for scnner provides mcro definitions for ech token (used in the prser) nowdys JvCC is more populr 20

21 NFA exmple Wht out the RE ( )*? Stte s 0 hs multiple trnsitions on! This is non-deterministic finite utomton 21

22 Review: Finite Automt A non-deterministic finite utomton (NFA) consists of: 1. set of sttes S = { s 0,, s n } 2. set of input symols Σ (the lphet) 3. trnsition function move (δ) mpping stte-symol pirs to sets of sttes 4. distinguished strt stte s 0 5. set of distinguished ccepting (finl) sttes F A Deterministic Finite Automton (DFA) is specil cse of n NFA: 1. no stte hs ε-trnsition, nd 2. for ech stte s nd input symol, there is t most one edge leled leving s. A DFA ccepts x iff there exists unique pth through the trnsition grph from the s 0 to n ccepting stte such tht the lels long the edges spell x. 22

23 DFA exmple Exmple: the set of strings contining n even numer of zeros nd n even numer of ones The RE is (00 11)*((01 10)(00 11)*(01 10)(00 11)*)* Note how the RE wlks through the DFA. 23

24 DFAs nd NFAs re equivlent 1. DFAs re suset of NFAs 2. Any NFA cn e converted into DFA, y simulting sets of simultneous sttes: ech DFA stte corresponds to set of NFA sttes NB: possile exponentil lowup 24

25 NFA to DFA using the suset construction 25

26 Rodmp > Introduction > Regulr lnguges > Finite utomt recognizers > From RE to DFAs nd ck gin > Limits of regulr lnguges 26

27 Constructing DFA from RE > RE NFA Build NFA for ech term; connect with ε moves > NFA DFA Simulte the NFA using the suset construction > DFA minimized DFA Merge equivlent sttes > DFA RE Construct R k ij = R k-1 ik (R k-1 kk)* R k-1 kj R k-1 ij Or convert vi Generlized NFA (GNFA) 27

28 RE to NFA Strt Stte 28

29 RE to NFA exmple: ( )* ( ) ( )* ( )* 29

30 NFA to DFA: the suset construction Input: NFA N Output: DFA D with sttes S D nd trnsitions T D such tht L(D) = L(N) Method: Let s e stte in N nd P e set of sttes. Use the following opertions: > ε-closure(s) set of sttes of N rechle from s y ε trnsitions lone > ε-closure(p) set of sttes of N rechle from some s in P y ε trnsitions lone > move(t,) set of sttes of N to which there is trnsition on input from some s in P dd stte P = ε-closure(s 0 ) unmrked to S D while unmrked stte P in S D mrk P for ech input symol U = ε-closure(move(p,)) if U S D then dd U unmrked to S D T D [P,] = U end for end while ε-closure(s 0 ) is the strt stte of D A stte of D is ccepting if it contins n ccepting stte of N 30

31 NFA to DFA using suset construction: exmple A = {0,1,2,4,7} B = {1,2,3,4,6,7,8} C = {1,2,4,5,6,7} D = {1,2,4,5,6,7,9} E = {1,2,4,5,6,7,10} A C B D E 31

32 DFA Minimiztion Theorem: For ech regulr lnguge tht cn e ccepted y DFA, there exists DFA with minimum numer of sttes. A B D Minimiztion pproch: merge equivlent sttes. C E Sttes A nd C re indistinguishle, so they cn e merged! 32

33 DFA Minimiztion lgorithm > Crete lower-tringulr tle DISTINCT, initilly lnk > For every pir of sttes (p,q): If p is finl nd q is not, or vice vers DISTINCT(p,q) = ε > Loop until no chnge for n itertion: For every pir of sttes (p,q) nd ech symol α If DISTINCT(p,q) is lnk nd DISTINCT( δ(p,α), δ(q,α) ) is not lnk DISTINCT(p,q) = α > Comine ll sttes tht re not distinct 33

34 Minimiztion in ction A C B D E C nd A re indistinguishle so cn e merged A A A A A B B B B B C C C C C D D D D D E E ε ε ε ε E ε ε ε ε E ε ε ε ε E ε ε ε ε A B C D E A B C D E A B C D E A B C D E A B C D E 34

35 DFA Minimiztion exmple A C B D E It is esy to see tht this is in fct the miniml DFA for ( )*

36 DFA to RE vi GNFA > A Generlized NFA is n NFA where trnsitions my hve ny RE s lels > Conversion lgorithm: 1. Add new strt stte nd ccept stte with ε-trnsitions to/from the old strt/end sttes 2. Merge multiple trnsitions etween two sttes to single RE choice trnsition 3. Add empty trnsitions etween sttes where missing 4. Itertively rip out old sttes nd replce dngling trnsitions with ppropritely leled trnsitions etween remining sttes 5. STOP when ll old sttes re gone nd only the new strt nd ccept sttes remin 36

37 GNFA conversion lgorithm 1. Let k e the numer of sttes of G, k 2 2. If k=2, then RE is the lel found etween q s nd q (strt nd ccept sttes of G) 3. While k>2, select q rip q s or q Q = Q {q rip } For ny q i Q {q } let δ (q i,q j ) = R 1 R 2 * R 3 R 4 where: R 1 = δ (q i,q rip ), R 2 = δ (q rip,q rip ), R 2 = δ (q rip,q j ), R 4 = δ (q i,q j ) Replce G y G 37

38 The initil DFA

39 ε ε s Add new strt nd ccept sttes

40 ε ε s Add missing empty trnsitions (we ll just pretend they re there)

41 1 2 3 ε ε s Delete n ritrry stte

42 1 2 3 * * ε s Fix dngling trnsitions s 1 nd 3 1 Don t forget to merge the existing trnsitions!

43 Simplify the RE Delete nother stte 2 3 * * ε s NB: * = (* ε) = *

44 * 2 3 ** ** ε s

45 * 2 ** ** ε s

46 * ** 2 ** s NB: * ** = (ε *)* = **

47 ** 2 ** s

48 ** ** s

49 Hm not wht we expected s ** (**)*

50 ** (**)* = ( )*? > We cn rewrite: ** (**)* ** (**)* (**)* ** > But does this hold? (**)* ** = ( )* We cn show tht the miniml DFAs for these REs re isomorphic

51 Rodmp > Introduction > Regulr lnguges > Finite utomt recognizers > From RE to DFAs nd ck gin > Limits of regulr lnguges 51

52 Limits of regulr lnguges Not ll lnguges re regulr! One cnnot construct DFAs to recognize these lnguges: L = { p k q k } L = { wcw r w Σ*, w r is w reversed } In generl, DFAs cnnot count! However, one cn construct DFAs for: Alternting 0 s nd 1 s: (ε 1)(01)*(ε 0) Sets of pirs of 0 s nd 1 s (01 10) + 52

53 So, wht is hrd? Certin lnguge fetures cn cuse prolems: > Reserved words PL/I hd no reserved words if then then then = else; else else = then > Significnt lnks FORTRAN nd Algol68 ignore lnks do 10 i = 1,25 do 10 i = 1.25 > String constnts Specil chrcters in strings Newline, t, quote, comment delimiter > Finite limits Some lnguges limit identifier lengths Add stte to count length FORTRAN 66 6 chrcters(!) 53

54 How d cn it get? Compiler needs context to distinguish vriles from control constructs! 54

55 Wht you should know! Wht re the key responsiilities of scnner? Wht is forml lnguge? Wht re opertors over lnguges? Wht is regulr lnguge? Why re regulr lnguges interesting for defining scnners? Wht is the difference etween deterministic nd non-deterministic finite utomton? How cn you generte DFA recognizer from regulr expression? Why ren t regulr lnguges expressive enough for prsing? 55

56 Cn you nswer these questions? Why do compilers seprte scnning from prsing? Why doesn t NFA DFA trnsltion normlly result in n exponentil increse in the numer of sttes? Why is it necessry to minimize sttes fter trnsltion NFA to DFA? How would you progrm scnner for lnguge like FORTRAN? 56

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