Fall Compiler Principles Lecture 2: LL parsing. Roman Manevich Ben-Gurion University of the Negev

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1 Fall Compiler Principles Lecture 2: LL parsing Roman Manevich Ben-Gurion University of the Negev 1

2 Books Compilers Principles, Techniques, and Tools Alfred V. Aho, Ravi Sethi, Jeffrey D. Ullman Modern Compiler Implementation in Java Andrew W. Appel Modern Compiler Design D. Grune, H. Bal, C. Jacobs, K. Langendoen Advanced Compiler Design and Implementation Steven Muchnik 2

3 Tentative syllabus Front End Intermediate Representation Optimizations Code Generation Scanning Operational Semantics Dataflow Analysis Register Allocation Top-down Parsing (LL) Lowering Loop Optimizations Instruction Selection Bottom-up Parsing (LR) mid-term exam 3

4 Context-free grammars start nonterminal nonterminal S E $ E T E E + T T id T ( E ) terminal production / rule 4

5 Context-free languages Sentential forms Derivations (leftmost, rightmost) Language = all derivable words Derivation tree (also called parse tree) Language = all yields of derivation trees Ambiguous grammars 5

6 Agenda Understand role of syntax analysis Parsing strategies LL parsing Building a predictor table via FIRST/FOLLOW/NULLABLE sets Handling conflicts 6

7 Role of syntax analysis High-level Language Lexical Analysis Syntax Analysis Parsing AST Symbol Table etc. Inter. Rep. (IR) Code Generation Executable Code (scheme) Recover structure from stream of tokens Parse tree / abstract syntax tree Error reporting (recovery) Other possible tasks Syntax directed translation (one pass compilers) Create symbol table Create pretty-printed version of the program, e.g., Auto Formatting function in IDE 7

8 From tokens to abstract syntax trees program text 59 + (1257 * xposition) Lexical Analyzer Regular expressions Finite automata Lexical error valid token stream num + ( num * id ) Grammar: E id E num E E + E E E * E E ( E ) syntax error + Parser valid Context-free grammars Push-down automata Abstract Syntax Tree num * num x 8

9 Marking end-of-file Sometimes it will be useful to transform a grammar G with start non-terminal S into a grammar G with a new start non-terminal S and a new production rule S S $ $ is not part of the set of tokens It is a special End-Of-File (EOF) token To parse α with G we change it into α $ Simplifies parsing grammars with null productions Also simplifies parsing LR grammars Blank space character 9

10 Another convention We will assume that all productions have been consecutively numbered (1) S E $ (2) E T (3) E E + T (4) T id (5) T ( E ) 10

11 Parsing strategies 11

12 Broad kinds of parsers Parsers for arbitrary grammars Cocke-Younger-Kasami [ 65] method O(n 3 ) Earley s method (implemented by NLTK) O(n 3 ) but lower for restricted classes Not commonly used by compilers Parsers for restricted classes of grammars Top-Down Predictive LL parsing Backtracking recursive descent / combinators Bottom-Up LR parsing 12

13 Top-down parsing Constructs parse tree in a topdown matter Find leftmost derivation Predictive: for every nonterminal and k-tokens predict the next production LL(k) Challenge: beginning with the start symbol, try to guess the productions to apply to end up at the user's program By Fidelio (Own work) [GFDL ( or CC-BY-SA ( via Wikimedia Commons 13

14 Predictive parsing 14

15 Exercise: show leftmost derivation How did we decide which production of E to take? E not E not ( E OP E ) not ( not E OP E ) not ( not LIT OP E ) not ( not true OP E ) not ( not true or E ) not ( not true or LIT ) not ( not true or false ) (1) E LIT (2) (E OP E) (3) not E (4) LIT true (5) false (6) OP and (7) or (8) xor not E E ( E OP E ) not E or LIT LIT false true 15

16 Predictive parsing Given a grammar G attempt to derive a word ω Idea Scan input from left to right Apply production to leftmost nonterminal Pick production rule based on next (1) input token Problem: there is more than one production based for next token Solution: restrict grammars to LL(1) Parser correctly predicts which production to apply If grammar is not in LL(1) the parser construction algorithm will detect it 16

17 nonterminal LL(1) parsing via pushdown automata Input stream a + b $ Stack of symbols (current sentential form) X Y Z $ Parsing program token Derivation tree / error Prediction table production 17

18 LL(1) parsing algorithm Initialze stack to S $ while true Prediction When top of stack is nonterminal N 1. Pop N 2. lookup Table[N,t] 3. If table[n,t] is not empty, push Table[N,t] on stack else return syntax error Match When top of stack is terminal t If t=next input token, pop t and increment input index else return syntax error End When stack is empty If input is empty return success else return syntax error 18

19 Nonterminals Example prediction table (1) E LIT (2) E ( E OP E ) (3) E not E (4) LIT true (5) LIT false (6) OP and (7) OP or (8) OP xor Input tokens Table entries determine which production to take ( ) not true false and or xor $ E LIT 4 5 OP

20 Running parser example aacbb$ S asb c Input suffix Stack content Move aacbb$ S$ predict(s,a) = S asb aacbb$ asb$ match(a,a) acbb$ Sb$ predict(s,a) = S asb acbb$ asbb$ match(a,a) cbb$ Sbb$ predict(s,c) = S c cbb$ cbb$ match(c,c) bb$ bb$ match(b,b) b$ b$ match(b,b) $ $ match($,$) success a b c S S asb S c 20

21 Illegal input example abcbb$ S asb c Input suffix Stack content Move abcbb$ S$ predict(s,a) = S asb abcbb$ asb$ match(a,a) bcbb$ Sb$ predict(s,b) = ERROR a b c S S asb S c 21

22 Building the prediction table Let G be a grammar Compute FIRST/NULLABLE/FOLLOW Check for conflicts No conflicts => G is an LL(1) grammar Conflicts exit => G is not an LL(1) grammar Attempt to transform G into an equivalent LL(1) grammar G 22

23 First sets 23

24 FIRST sets Definition: For a nonterminal A, FIRST(A) is the set of terminals that can start in a sentence derived from A Formally: FIRST(A) = {t A * t ω} Definition: For a sentential form α, FIRST(α) is the set of terminals that can start in a sentence derived from α Formally: FIRST(α) = {t α * t ω} 24

25 FIRST sets example E LIT (E OP E) not E LIT true false OP and or xor FIRST(E) =? FIRST(LIT) =? FIRST(OP) =? 25

26 FIRST sets example E LIT (E OP E) not E LIT true false OP and or xor FIRST(E) = FIRST(LIT) FIRST(( E OP E )) FIRST(not E) FIRST(LIT) = { true, false } FIRST(OP) = {and, or, xor} A set of recursive equations How do we solve them? 26

27 Computing FIRST sets Assume no null productions (A ) 1. Initially, for all nonterminals A, set FIRST(A) = { t A t ω for some ω } 2. Repeat the following until no changes occur: for each nonterminal A for each production A α 1 α k FIRST(A) := FIRST(α 1 ) FIRST(α k ) This is known as a fixed-point algorithm We will see such iterative methods later in the course and learn to reason about them 27

28 Exercise: compute FIRST FIRST(STMT) = FIRST(if EXPR then STMT) FIRST(while EXPR do STMT) FIRST(EXPR) FIRST(EXPR) = FIRST(TERM -> id) FIRST(zero? TERM) FIRST(not EXPR) FIRST(++ id) FIRST(-- id) FIRST(TERM) = FIRST(id) FIRST(constant) STMT if EXPR then STMT while EXPR do STMT EXPR ; EXPR TERM -> id zero? TERM not EXPR ++ id -- id TERM id constant STMT EXPR TERM 28

29 Exercise: compute FIRST FIRST(STMT) = {if, while} FIRST(EXPR) FIRST(EXPR) = {zero?, not, ++, --} FIRST(TERM) FIRST(TERM) = {id, constant} STMT if EXPR then STMT while EXPR do STMT EXPR ; EXPR TERM -> id zero? TERM not EXPR ++ id -- id TERM id constant STMT EXPR TERM 29

30 1. Initialization FIRST(STMT) = {if, while} FIRST(EXPR) FIRST(EXPR) = {zero?, not, ++, --} FIRST(TERM) FIRST(TERM) = {id, constant} STMT if EXPR then STMT while EXPR do STMT EXPR ; EXPR TERM -> id zero? TERM not EXPR ++ id -- id TERM id constant STMT if while EXPR zero? Not TERM id constant 30

31 2. Iterate 1 FIRST(STMT) = {if, while} FIRST(EXPR) FIRST(EXPR) = {zero?, not, ++, --} FIRST(TERM) FIRST(TERM) = {id, constant} STMT if EXPR then STMT while EXPR do STMT EXPR ; EXPR TERM -> id zero? TERM not EXPR ++ id -- id TERM id constant STMT if while zero? Not EXPR zero? Not TERM id constant 31

32 2. Iterate 2 FIRST(STMT) = {if, while} FIRST(EXPR) FIRST(EXPR) = {zero?, not, ++, --} FIRST(TERM) FIRST(TERM) = {id, constant} STMT if EXPR then STMT while EXPR do STMT EXPR ; EXPR TERM -> id zero? TERM not EXPR ++ id -- id TERM id constant STMT if while zero? Not EXPR zero? Not id constant TERM id constant 32

33 2. Iterate 3 fixed-point FIRST(STMT) = {if, while} FIRST(EXPR) FIRST(EXPR) = {zero?, not, ++, --} FIRST(TERM) FIRST(TERM) = {id, constant} STMT if EXPR then STMT while EXPR do STMT EXPR ; EXPR TERM -> id zero? TERM not EXPR ++ id -- id TERM id constant STMT if while zero? Not EXPR zero? Not id constant TERM id constant id constant 33

34 Reasoning about the algorithm Assume no null productions (A ) 1. Initially, for all nonterminals A, set FIRST(A) = { t A t ω for some ω } 2. Iterate to fixpoint: for each nonterminal A for each production A α 1 α k FIRST(A) := FIRST(α 1 ) FIRST(α k ) Is the algorithm correct? Does it terminate? (complexity) 34

35 Reasoning about the algorithm Termination: Correctness: 35

36 LL(1) Parsing of grammars without epsilon productions 36

37 Using FIRST sets Assume G has no epsilon productions and for every non-terminal X and every pair of productions X and X we have that FIRST( ) FIRST( ) = {} No intersection between FIRST sets => can always pick a single rule 37

38 Using FIRST sets In our Boolean expressions example FIRST( LIT ) = { true, false } FIRST( ( E OP E ) ) = { ( } FIRST( not E ) = { not } If the FIRST sets intersect, may need longer lookahead LL(k) = class of grammars in which production rule can be determined using a lookahead of k tokens LL(1) is an important and useful class 38

39 Exercise: LL(1) prediction table Terminals: id. num $ (1) S E $ (2) E A B (3) E B (4) A id B (5) B. id A (6) B num FIRST(S) = FIRST(E) = FIRST(A) = FIRST(B) = S E A B id. num $ 39

40 Extending LL(1) Parsing for epsilon productions 40

41 FIRST, FOLLOW, NULLABLE sets For each non-terminal X FIRST(X) = set of terminals that can start in a sentence derived from X FIRST(X) = {t X * t ω} NULLABLE(X) if X * FOLLOW(X) = set of terminals that can follow X in some derivation FOLLOW(X) = {t S * X t } 41

42 Computing the NULLABLE set Lemma: NULLABLE( 1 k ) = NULLABLE( 1 ) NULLABLE( k ) If X 1 k then we have the following equation: NULLABLE(X) = NULLABLE( 1 ) NULLABLE( k ) 1. Initially NULLABLE(X) = false 2. Iterate to fixpoint: for each production Y 1 k if NULLABLE( 1 k ) then NULLABLE(Y) = true 42

43 Exercise: compute NULLABLE S A a b A a B A B C C b NULLABLE(S) = NULLABLE(A) NULLABLE(a) NULLABLE(b) NULLABLE(A) = NULLABLE(a) NULLABLE( ) NULLABLE(B) = NULLABLE(A) NULLABLE(B) NULLABLE(C) NULLABLE(C) = NULLABLE(b) NULLABLE( ) 43

44 FIRST with epsilon productions How do we compute FIRST( 1 k ) when epsilon productions are allowed? FIRST( 1 k ) =? 44

45 FIRST with epsilon productions How do we compute FIRST( 1 k ) when epsilon productions are allowed? FIRST( 1 k ) = if not NULLABLE( 1 ) then FIRST( 1 ) else FIRST( 1 ) FIRST ( 2 k ) 45

46 Exercise: compute FIRST S A c b A a NULLABLE(S) = NULLABLE(A) NULLABLE(c) NULLABLE(b) NULLABLE(A) = NULLABLE(a) NULLABLE( ) FIRST(S) = FIRST(A) FIRST(cb) FIRST(A) = FIRST(a) FIRST ( ) FIRST(S) = FIRST(A) {c} FIRST(A) = {a} S A c b A a What should we predict for input acb? What should we predict for input cb? 46

47 FOLLOW sets FOLLOW(X) = set of terminals that can follow X in some derivation FOLLOW(X) = {t S * X t } 47

48 FOLLOW sets if X α Y then FOLLOW(Y)? if NULLABLE( ) or = then FOLLOW(Y)? p

49 FOLLOW sets if X α Y then FOLLOW(Y) FIRST( ) if NULLABLE( ) or = then FOLLOW(Y)? p

50 FOLLOW sets if X α Y then FOLLOW(Y) FIRST( ) if NULLABLE( ) or = then FOLLOW(Y) FOLLOW(X) p

51 FOLLOW sets if X α Y then FOLLOW(Y) FIRST( ) if NULLABLE( ) (or = ) then FOLLOW(Y) FOLLOW(X) Allows predicting nullable productions: X α where NULLABLE(α) when the lookahead token is in FOLLOW(X) p. 189 S A c b A a c What should we predict for input cb? What should we predict for input acb? 51

52 Filling the prediction table Table[N, t] = N α if 1. t FIRST(α) or 2. NULLABLE(α) and t FOLLOW(N) 52

53 LL(1) conflicts 53

54 Conflicts FIRST-FIRST conflict X α and X and If FIRST(α) FIRST(β) {} FIRST-FOLLOW conflict X α NULLABLE(α) If FIRST(α) FOLLOW(X) {} 54

55 LL(1) grammars A grammar is in the class LL(1) when its LL(1) prediction table contains no conflicts A language is said to be LL(1) when it has an LL(1) grammar 55

56 LL(k) grammars 56

57 LL(k) grammars Generalizes LL(1) for k lookahead tokens Need to generalize FIRST and FOLLOW for k lookahead tokens 57

58 Agenda Understand role of syntax analysis Parsing strategies LL parsing Building a predictor table via FIRST/FOLLOW/NULLABLE sets Handling conflicts 58

59 Handling conflicts 59

60 Problem 1: FIRST-FIRST conflict term ID indexed_elem indexed_elem ID [ expr ] FIRST(indexed_elem) = { ID } How can we transform the grammar into an equivalent grammar that does not have this conflict? 60

61 Solution: left factoring Rewrite the grammar to be in LL(1) term ID indexed_elem indexed_elem ID [ expr ] New grammar is more complex has epsilon production term ID after_id After_ID [ expr ] Intuition: just like factoring in algebra: x*y + x*z into x*(y+z) 61

62 Exercise: apply left factoring S if E then S else S if E then S T 62

63 Exercise: apply left factoring S if E then S else S if E then S T S if E then S S T S else S 63

64 Problem 2: FIRST-FOLLOW conflict S A a b A a FIRST(S) = { a } FOLLOW(S) = { } FIRST(A) = { a } FOLLOW(A) = { a } How can we transform the grammar into an equivalent grammar that does not have this conflict? 64

65 Solution: substitution S A a b A a Substitute A in S S a a b a b 65

66 Solution: substitution S A a b A a Substitute A in S S a a b a b Left factoring S a after_a after_a a b b 66

67 Problem 3: FIRST-FIRST conflict E E - term term Left recursion cannot be handled with a bounded lookahead How can we transform the grammar into an equivalent grammar that does not have this conflict? 67

68 Solution: left recursion removal p. 130 N Nα β N βn N αn G 1 G 2 L(G 1 ) = β, βα, βαα, βααα, L(G 2 ) = same For our 3 rd example: Can be done algorithmically. Problem 1: grammar becomes mangled beyond recognition Problem 2: grammar may not be LL(1) E E - term term E term TE term TE - term TE 68

69 Recap Given a grammar Compute for each non-terminal NULLABLE FIRST using NULLABLE FOLLOW using FIRST and NULLABLE Compute FIRST for each sentential form appearing on right-hand side of a production Check for conflicts If exist, attempt to remove conflicts by rewriting grammar 69

70 Next lecture: bottom-up parsing

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