1. Fall 2016-2017 Compiler Principles Lecture 2: LL parsing
Roman Manevich
Ben-Gurion University of the Negev

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

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

4. Parsing background Context-free grammars Context-free languages
Terminals
Nonterminals
Start nonterminal
Productions (rules)
Context-free languages
Derivations (leftmost, rightmost)
Derivation tree (also called parse tree)
Ambiguous grammars

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

6. Role of syntax analysis
High-level Language (scheme)
Executable
Code
Lexical Analysis
Syntax Analysis
Parsing
AST
Symbol Table etc.
Inter. Rep. (IR)
Code Generation
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. From tokens to abstract syntax trees
program text
59 + (1257 * xPosition)
Lexical Analyzer
Regular expressions Finite automata
Lexical error
valid
token stream ) id *
num ( +
Grammar: E  id
E  num
E  E + E E  E * E E  ( E )
Parser
Context-free grammars Push-down automata
syntax error
valid +
num x *
Abstract Syntax Tree

8. 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

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 )

10. Parsing strategies

11. Broad kinds of parsers Parsers for arbitrary grammars
Cocke-Younger-Kasami [‘65] method O(n3)
Earley’s method (implemented by NLTK) O(n3) but lower for restricted classes
Not commonly used by compilers
Parsers for restricted classes of grammars
Top-Down
With/without backtracking
Bottom-Up

12. Top-down parsing Constructs parse tree in a top-down matter
Find leftmost derivation
Predictive: for every non-terminal 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. Predictive parsing

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

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

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

17. LL(1) parsing algorithm
Set stack=S$
while true
Prediction When top of stack is nonterminal N
Pop N
lookup Table[N,t]
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

18. 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 )’ )
Table entries determine which production to take
Input tokens ( )
not
true
false
and or
xor $ E 2 3 1
LIT 4 5 OP 6 7 8
Nonterminals

19. Running parser example
aacbb$
S  aSb | c
Input suffix
Stack content
Move
aacbb$ S$
predict(S,a) = S  aSb
aSb$
match(a,a)
acbb$
Sb$
aSbb$
cbb$
Sbb$
predict(S,c) = S  c
match(c,c)
bb$
match(b,b) b$ $
match($,$) – success a b c S
S  aSb
S  c

20. Illegal input example abcbb$ S  aSb | c Input suffix Stack content
Move
abcbb$ S$
predict(S,a) = S  aSb
aSb$
match(a,a)
bcbb$
Sb$
predict(S,b) = ERROR a b c S
S  aSb
S  c

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’

22. First sets

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}

24. FIRST sets example E  LIT | (E OP E) | not E LIT  true | false
OP  and | or | xor
FIRST(E) = …?
FIRST(LIT) = …?
FIRST(OP) = …?

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?

26. Assume no null productions (A  )
Computing FIRST sets
Assume no null productions (A  )
Initially, for all nonterminals A, set FIRST(A) = { t | A  t ω for some ω }
Repeat the following until no changes occur: for each nonterminal A for each production A  α1 | … | αk FIRST(A) := FIRST(α1) ∪ … ∪ FIRST(αk)
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. 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
TERM
EXPR
STMT

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
TERM
EXPR
STMT

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
TERM
EXPR
STMT
id constant
zero? Not ++ --
if while

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
TERM
EXPR
STMT
id constant
zero? Not ++ --
if while

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
TERM
EXPR
STMT
id constant
zero? Not ++ --
if while

32. 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
TERM
EXPR
STMT
id constant
zero? Not ++ --
if while

33. Reasoning about the algorithm
Assume no null productions (A  )
Initially, for all nonterminals A, set FIRST(A) = { t | A  t ω for some ω }
Repeat the following until no changes occur: for each nonterminal A for each production A  α1 | … | αk FIRST(A) := FIRST(α1) ∪ … ∪ FIRST(αk)
Is the algorithm correct?
Does it terminate? (complexity)

34. Reasoning about the algorithm
Termination:
Correctness:

35. LL(1) Parsing of grammars without epsilon productions

36. 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. 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?

38. Extending LL(1) Parsing for epsilon productions

39. 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 }

40. Computing the NULLABLE set
Lemma: NULLABLE(1 … k) = NULLABLE(1) …  NULLABLE(k)
Initially NULLABLE(X) = false
For each non-terminal X if exists a production X   then NULLABLE(X) = true
Repeat for each production Y  1 … k if NULLABLE(1 … k) then NULLABLE(Y) = true until NULLABLE stabilizes

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()

42. FIRST with epsilon productions
How do we compute FIRST(1 … k) when epsilon productions are allowed?
FIRST(1 … k) = ?

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)

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}

45. FOLLOW sets
p. 189
if X  α Y  then FOLLOW(Y) ? if NULLABLE() or = then FOLLOW(Y) ?

46. FOLLOW sets
p. 189
if X  α Y  then FOLLOW(Y)  FIRST() if NULLABLE() or = then FOLLOW(Y) ?

47. FOLLOW sets
p. 189
if X  α Y  then FOLLOW(Y)  FIRST() if NULLABLE() or = then FOLLOW(Y)  FOLLOW(X)

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”?

49. LL(1) conflicts

50. Conflicts FIRST-FIRST conflict X  α and X   and
If FIRST(α)  FIRST(β)  {}
FIRST-FOLLOW conflict
NULLABLE(X)
If FIRST(X)  FOLLOW(X)  {}

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

52. LL(k) grammars

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

54. Agenda LL(k) via pushdown automata
Predicting productions via FIRST/FOLLOW/NULLABLE sets
Handling conflicts

55. Handling conflicts

56. Problem 1: FIRST-FIRST 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?

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)

58. Exercise: apply left factoring
S  if E then S else S
| if E then S
| T

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 | 

60. 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?

61. Solution: substitution
S  A a b
A  a | 
Substitute A in S
S  a a b | a b

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

63. 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?

64. Solution: left recursion removal
p. 130
N  Nα | β
N  βN’
N’  αN’ |  G1 G2
L(G1) = β, βα, βαα, βααα, …
L(G2) = same
Can be done algorithmically.
Problem 1: grammar becomes mangled beyond recognition Problem 2: grammar may not be LL(1)
For our 3rd example:
E  E - term | term
E  term TE | term
TE  - term TE | 

65. 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

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 context-free language
Program included in a given attribute grammar (type checking, legal inheritance graph, variables initialized before used)
Memory safety: null dereference, array-out-of-bounds access, data races, functional correctness (program meets specification)

67. Next lecture: bottom-up parsing