Fall Compiler Principles Lecture 2: LL parsing. Roman Manevich BenGurion University of the Negev


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1 Fall Compiler Principles Lecture 2: LL parsing Roman Manevich BenGurion 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 Topdown Parsing (LL) Lowering Loop Optimizations Energy Optimization Bottomup Parsing (LR) Instruction Selection midterm exam 3
4 Parsing background Contextfree grammars Terminals Nonterminals Start nonterminal Productions (rules) Contextfree languages Derivations (leftmost, rightmost) Derivation tree (also called parse tree) Ambiguous grammars 4
5 Agenda Understand role of syntax analysis Parsing strategies LL parsing Building a predictor table via FIRST/FOLLOW/NULLABLE sets Pushdown automata algorithm Handling conflicts 5
6 Role of syntax analysis Highlevel 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 prettyprinted version of the program, e.g., Auto Formatting function in IDE 6
7 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 Contextfree grammars Pushdown automata Abstract Syntax Tree num * num x 7
8 Marking endoffile Sometimes it will be useful to transform a grammar G with start nonterminal S into a grammar G with a new start nonterminal S and a new production rule S S $ $ is not part of the set of tokens It is a special EndOfFile (EOF) token To parse α with G we change it into α $ Simplifies parsing grammars with null productions Also simplifies parsing LR grammars 8
9 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 ) 9
10 Parsing strategies 10
11 Broad kinds of parsers Parsers for arbitrary grammars CockeYoungerKasami [ 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 TopDown With/without backtracking BottomUp 11
12 Topdown parsing Constructs parse tree in a topdown matter Find leftmost derivation Predictive: for every nonterminal and ktokens 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 CCBYSA ( via Wikimedia Commons 12
13 Predictive parsing 13
14 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 14
15 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 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 15
16 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 16
17 LL(1) parsing algorithm Set stack=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 toke, 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 17
18 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 ( FIRST( ( E OP E ) ) Input tokens Table entries determine which production to take ( ) not true false and or xor $ E LIT 4 5 OP
19 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 19
20 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 20
21 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 21
22 First sets 22
23 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} 23
24 FIRST sets example E LIT (E OP E) not E LIT true false OP and or xor FIRST(E) =? FIRST(LIT) =? FIRST(OP) =? 24
25 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? 25
26 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 fixedpoint algorithm We will see such iterative methods later in the course and learn to reason about them 26
27 Exercise: compute FIRST FIRST(STMT) = FIRST(if) FIRST(while) FIRST(EXPR) FIRST(EXPR) = FIRST(TERM) FIRST(zero?) FIRST(not) FIRST(++) FIRST() 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 27
28 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 28
29 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 29
30 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 30
31 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 31
32 2. Iterate 3 fixedpoint 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 32
33 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. 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 ) Is the algorithm correct? Does it terminate? (complexity) 33
34 Reasoning about the algorithm Termination: Correctness: 34
35 LL(1) Parsing of grammars without epsilon productions 35
36 Using FIRST sets Assume G has no epsilon productions and for every nonterminal 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 36
37 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 What if there are epsilon productions? 37
38 Extending LL(1) Parsing for epsilon productions 38
39 FIRST, FOLLOW, NULLABLE sets For each nonterminal 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 } 39
40 Computing the NULLABLE set Lemma: NULLABLE( 1 k ) = NULLABLE( 1 ) NULLABLE( k ) 1. Initially NULLABLE(X) = false 2. For each nonterminal X if exists a production X then NULLABLE(X) = true 3. Repeat for each production Y 1 k if NULLABLE( 1 k ) then NULLABLE(Y) = true until NULLABLE stabilizes 40
41 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( ) 41
42 FIRST with epsilon productions How do we compute FIRST( 1 k ) when epsilon productions are allowed? FIRST( 1 k ) =? 42
43 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 ) 43
44 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} 44
45 FOLLOW sets if X α Y then FOLLOW(Y)? if NULLABLE( ) or = then FOLLOW(Y)? p
46 FOLLOW sets if X α Y then FOLLOW(Y) FIRST( ) if NULLABLE( ) or = then FOLLOW(Y)? p
47 FOLLOW sets if X α Y then FOLLOW(Y) FIRST( ) if NULLABLE( ) or = then FOLLOW(Y) FOLLOW(X) p
48 FOLLOW sets p. 189 if X α Y then FOLLOW(Y) FIRST( ) if NULLABLE( ) or = then FOLLOW(Y) FOLLOW(X) Allows predicting epsilon productions: X when the lookahead token is in FOLLOW(X) S A c b A a What should we predict for input cb? What should we predict for input acb? 48
49 LL(1) conflicts 49
50 Conflicts FIRSTFIRST conflict X α and X and If FIRST(α) FIRST(β) {} FIRSTFOLLOW conflict NULLABLE(X) If FIRST(X) FOLLOW(X) {} 50
51 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 51
52 LL(k) grammars 52
53 LL(k) grammars Generalizes LL(1) for k lookahead tokens Need to generalize FIRST and FOLLOW for k lookahead tokens 53
54 Agenda LL(k) via pushdown automata Predicting productions via FIRST/FOLLOW/NULLABLE sets Handling conflicts 54
55 Handling conflicts 55
56 Problem 1: FIRSTFIRST conflict term ID indexed_elem indexed_elem ID [ expr ] FIRST(term) = { ID } FIRST(indexed_elem) = { ID } How can we transform the grammar into an equivalent grammar that does not have this conflict? 56
57 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) 57
58 Exercise: apply left factoring S if E then S else S if E then S T 58
59 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 59
60 Problem 2: FIRSTFOLLOW 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? 60
61 Solution: substitution S A a b A a Substitute A in S S a a b a b 61
62 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 62
63 Problem 3: FIRSTFIRST 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? 63
64 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 64
65 Recap Given a grammar Compute for each nonterminal NULLABLE FIRST using NULLABLE FOLLOW using FIRST and NULLABLE Compute FIRST for each sentential form appearing on righthand side of a production Check for conflicts If exist: attempt to remove conflicts by rewriting grammar 65
66 The bigger picture Compilers include different kinds of program analyses each further constrains the set of legal programs Lexical constraints Syntax constraints Semantic constraints Logical constraints (Verifying Compiler grand challenge) Program consists of legal tokens Program included in a given contextfree language Program included in a given attribute grammar (type checking, legal inheritance graph, variables initialized before used) Memory safety: null dereference, arrayoutofbounds access, data races, functional correctness (program meets specification) 66
67 Next lecture: bottomup parsing
Fall Compiler Principles Lecture 2: LL parsing. Roman Manevich BenGurion University of the Negev
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