1. Topic #3: Lexical Analysis EE 456 – Compiling Techniques Prof. Carl Sable Fall 2003

2. Lexical Analyzer and Parser

3. Why Separate? Reasons to separate lexical analysis from parsing: –Simpler design –Improved efficiency –Portability Tools exist to help implement lexical analyzers and parsers independently

4. Tokens, Lexemes, and Patterns Tokens include keywords, operators, identifiers, constants, literal strings, punctuation symbols A lexeme is a sequence of characters in the source program representing a token A pattern is a rule describing a set of lexemes that can represent a particular token

5. Attributes Attributes provide additional information about tokens Technically speaking, lexical analyzers usually provide a single attribute per token (might be pointer into symbol table)

6. Buffer Most lexical analyzers use a buffer Often buffers are divided into two N character halves Two pointers used to indicate start and end of lexeme If pointer walks past end of either half of buffer, other half of buffer is reloaded A sentinel character can be used to decrease number of checks necessary

7. Strings and Languages Alphabet – any finite set of symbols (e.g. ASCII, binary alphabet, or a set of tokens) String – A finite sequence of symbols drawn from an alphabet Language – A set of strings over a fixed alphabet Other terms relating to strings: prefix; suffix; substring; proper prefix, suffix, or substring (non- empty, not entire string); subsequence

8. Operations on Languages Union: Concatenation: Kleene closure: – –Zero or more concatenations Positive closure: – –One or more concatenations

9. Regular Expressions Defined over an alphabet Σ ε represents { ε }, the set containing the empty string If a is a symbol in Σ, then a is a regular expression denoting { a }, the set containing the string a If r and s are regular expressions denoting the languages L(r) and L(s), then: –(r)|(s) is a regular expression denoting L(r) U L(s) –(r)(s) is a regular expression denoting L(r)L(s) –(r) * is a regular expression denoting (L(r)) * –(r) is a regular expression denoting L(r) Precedence: * (left associative), then concatenation (left associative), then | (left associative)

10. Regular Definitions Can give “names” to regular expressions Convention: names in boldface (to distinguish them from symbols) letter  A|B|…|Z|a|b|…|z digit  0|1|…|9 id  letter (letter | digit)*

11. Notational Shorthands One or more instances: r + denotes rr * Zero or one Instance: r? denotes r|ε Character classes: [a-z] denotes [a|b|…|z] digit  [0-9] digits  digit + optional_fraction  (. digits )? optional_exponent  (E(+|-)? digits )? num  digits optional_fraction optional_exponent

12. Limitations Can not describe balanced or nested constructs –Example, all valid strings of balanced parentheses –This can be done with CFG Can not describe repeated strings –Example: { wcw|w is a string of a ’s and b ’s} –Can not denote with CFG either!

13. Grammar Fragment (Pascal) stmt  if expr then stmt | if expr then stmt else stmt | ε expr  term relop term | term term  id | num

14. Related Regular Definitions if  if then  then else  else relop  | > | >= id  letter ( letter | digit ) * num  digit + (. digit + )? (E(+|-)? digit + )? delim  blank | tab | newline ws  delim +

15. Tokens and Attributes Regular ExpressionTokenAttribute Value ws-- if - then - else - id pointer to entry num pointer to entry <relopLT <=relopLE =relopEQ <>relopNE >relopGT =>relopGE

16. Transition Diagrams A stylized flowchart Transition diagrams consist of states connected by edges Edges leaving a state s are labeled with input characters that may occur after reaching state s Assumed to be deterministic There is one start state and at least one accepting (final) state Some states may have associated actions At some final states, need to retract a character

17. Transition Diagram for “relop”

18. Identifiers and Keywords Share a transition diagram –After reaching accepting state, code determines if lexeme is keyword or identifier –Easier than encoding exceptions in diagram Simple technique is to appropriately initialize symbol table with keywords

19. Numbers

20. Order of Transition Diagrams Transition diagrams tested in order Diagrams with low numbered start states tried before diagrams with high numbered start states Order influences efficiency of lexical analyzer

21. Trying Transition Diagrams int next_td(void) { switch (start) { case 0: start = 9; break; case 9: start = 12; break; case 12: start = 20; break; case 20: start = 25; break; case 25: recover(); break; default: error("invalid start state"); } /* Possibly additional actions here */ return start; }

22. Finding the Next Token token nexttoken(void) { while (1) { switch (state) { case 0: c = nextchar(); if (c == ' ' || c=='\t' || c == '\n') { state = 0; lexeme_beginning++; } else if (c == '<') state = 1; else if (c == '=') state = 5 else if (c == '>') state = 6 else state = next_td(); break; … /* 27 other cases here */

23. The End of a Token token nexttoken(void) { while (1) { switch (state) { … /* First 19 cases */ case 19: retract(); install_num(); return(NUM); break; … /* Final 8 cases */

24. Finite Automata Generalized transition diagrams that act as “recognizer” for a language Can be nondeterministic (NFA) or deterministic (DFA) –NFAs can have ε-transitions, DFAs can not –NFAs can have multiple edges with same symbol leaving a state, DFAs can not –Both can recognize exactly what regular expressions can denote

25. NFAs A set of states S A set of input symbols Σ (input alphabet) A transition function move that maps state, symbol pairs to a set of states A single start state s 0 A set of accepting (or final) states F An NFA accepts a string s if and only if there exists a path from the start state to an accepting state such that the edge labels spell out s

26. Transition Tables State Input Symbol ab 0{0,1}{0} 1---{2} 2---{3}

27. DFAs No state has an ε-transition For each state s and input symbol a, there as at most one edge labeled a leaving s

28. Thompson’s Construction Method of converting a regular expression into an NFA Start with two simple rules –For ε, construct NFA: –For each a in Σ, construct NFA: Next will inductively apply a more complex rule until entire we obtain NFA for entire expression

29. Complex Rule, Part 1 For the regular expression s|t, such that N(s) and N(t) are NFAs for s and t, construct the following NFA N(s|t) :

30. Complex Rule, Part 2 For the regular expression st, construct the composite NFA N(st) : N(S)N(T)

31. Complex Rule, Part 3 For the regular expression s *, construct the composite NFA N(s * ) : 

32. Complex Rule, Part 4 For the parenthesized regular expression (s), use N(s) itself as the NFA

33. Example: r = (a|b) * abb

34. Functions ε-closure and move ε-closure(s) is the set of NFA states reachable from NFA state s on ε- transitions alone ε-closure(T) is the set of NFA states reachable from any NFA state s in T on ε- transitions alone move(T,a) is the set of NFA states to which there is a transition on input a from any NFA state s in T

35. Computing ε-closure push all states in T onto stack initialize ε-closure(T) to T while stack is not empty pop t from top of stack for each state u with an ε-transition from t if u is not in ε-closure(T) then add u to ε-closure(T) push u onto stack

36. Subset Construction (NFA to DFA) initialize Dstates to unmarked ε-closure(s 0 ) while there is an unmarked state T in Dstates mark T for each input symbol a U := ε-closure(move(T,a)) if U is not in Dstates add U as unmarked state to Dstates Dtran[T,a] := U

37. Constructed DFA

38. Simulating a DFA s := s 0 c := nextchar while c != eof do s := move(s, c) c := nextchar end if s is in F then return “yes” else return “no”

39. Simulating an NFA S := ε-closure({s 0 }) a := nextchar while a != eof do S := ε-closure(move(S,a)) a := nextchar if S ∩ F != Ø return “yes” else return “no”

40. Space/Time Tradeoff (Worst Case) SpaceTime NFAO(|r|)O(|r|*|x|) DFAO(2 |r| )O(|x|)

41. First use Thompson’s Construction to convert RE to NFA Then there are two choices: –Use subset construction to convert NFA to DFA, then simulate the DFA –Simulate the NFA directly You won’t have to worry about any of this while programming, Lex will take care of it! Simulating a Regular Expression