Parsing

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Parsing
Programming Language Concepts Lecture 6

• Prepared by
• Manuel E. Bermúdez, Ph.D.
• Associate Professor
• University of Florida

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Context-Free Grammars

• Definition A context-free grammar (CFG) is a
  quadruple G (?, ?, P, S), where all productions
  are of the form A ? ?, for A ? ? and ? ? (?u? ).
• Re-writing using grammar rules
• ßA? gt ß?? if A ? ? (derivation).

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String Derivations

• Left-most derivation At each step, the
  left-most nonterminal is re-written.
• Right-most derivation At each step, the
  right-most nonterminal is re-written.

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Derivation Trees

• Derivation trees
• Describe re-writes, independently of the order
  (left-most or right-most).
• Each tree branch matches a production rule in the
  grammar.

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Derivation Trees

• Notes
• Leaves are terminals.
• Bottom contour is the sentence.
• Left recursion causes left branching.
• Right recursion causes right branching.

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Goal of Parsing

• Examine input string, determine whether it's
  legal.
• Equivalent to building derivation tree.
• Added benefit tree embodies syntactic structure
  of input.
• Therefore, tree should be unique.

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Ambiguous Grammars

• Definition A CFG is ambiguous if there exist
  two different right-most (or left-most, but not
  both) derivations for some sentence z.
• (Equivalent) Definition A CFG is ambiguous if
  there exist two different derivation trees for
  some sentence z.

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Ambiguous Grammars

• Classic ambiguities
• Simultaneous left/right recursion
• E ? E E
• ? i
• Dangling else problem
• S ? if E then S
• ? if E then S else S
• ?

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Operator Precedence and Associativity

• Lets build a CFG for expressions consisting of
• elementary identifier i.
• and - (binary ops) have lowest precedence, and
  are left associative .
• and / (binary ops) have middle precedence, and
  are right associative.
• and - (unary ops) have highest precedence, and
  are right associative.

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Corresponding Grammar for Expressions

• E ? E T E consists of T's,
  
• ? E - T separated by s and 's
• ? T (lowest precedence).
• T ? F T T consists of F's,
• ? F / T separated by 's and /'s
• ? F (next precedence).
• F ? - F F consists of a single P,
• ? F preceded by 's and -'s.
• ? P (next precedence).
• P ? '(' E ')' P consists of a parenthesized
  E,
• ? i or a single i (highest
  precedence).

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Operator Precedence and Associativity

• Operator precedence
• The lower in the grammar, the higher the
  precedence.
• Operator Associativity
• Tie breaker for precedence.
• Left recursion in the grammar means
• left associativity of the operator,
• left branching in the tree.
• Right recursion in the grammar means
• right associativity of the operator,
• right branching in the tree.

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Building Derivation Trees

• Sample Input
• - i - i ( i i ) / i i
• (Human) derivation tree construction
• Bottom-up.
• On each pass, scan entire expression, process
  operators with highest precedence (parentheses
  are highest).
• Lowest precedence operators are last, at the top
  of tree.

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Abstract Syntax Trees

• AST is a condensed version of the derivation
  tree.
• No noise (intermediate nodes).
• String-to-tree transduction grammar
• rules of the form A ? ? gt 's'.
• Build 's' tree node, with one child per tree from
  each nonterminal in ?.

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Example

• E ? E T gt
• ? E - T gt -
• ? T
• T ? F T gt
• ? F / T gt /
• ? F
• F ? - F gt neg
• ? F gt
• ? P
• P ? '(' E ')'
• ? i gt i

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Sample Input - i - i ( i i ) / i i
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String-to-Tree Transduction

• We transduce from vocabulary of input symbols, to
  vocabulary of tree node names.
• Could eliminate construction of unary node,
  anticipating semantics.
• F ? - F gt neg
• ? F // no more unary node
• ? P

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The Game of Syntactic Dominoes

• The grammar
• E ? ET T ? PT P ? (E)
• ? T ? P ? i
• The playing pieces An arbitrary supply of each
  piece (one per grammar rule).
• The game board
• Start domino at the top.
• Bottom dominoes are the "input."

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The Game of Syntactic Dominoes

• Game rules
• Add game pieces to the board.
• Match the flat parts and the symbols.
• Lines are infinitely elastic.
• Object of the game
• Connect start domino with the input dominoes.
• Leave no unmatched flat parts.

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Parsing Strategies

• Same as for the game of syntactic dominoes.
• Top-down parsing start at the start symbol,
  work toward the input string.
• Bottom-up parsing start at the input string,
  work towards the goal symbol.
• In either strategy, can process the input
  left-to-right ? or right-to-left ?

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Top-Down Parsing

• Attempt a left-most derivation, by predicting the
  re-write that will match the remaining input.
• Use a string (a stack, really) from which the
  input can be derived.

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Top-Down Parsing

• Start with S on the stack.
• At every step, two alternatives
• ? (the stack) begins with a terminal t. Match t
  against the first input symbol.
• ? begins with a nonterminal A. Consult an OPF
  (Omniscient Parsing Function) to determine which
  production for A would lead to a match with the
  first symbol of the input.
• The OPF does the predicting in such a
  predictive parser.

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Classical Top-Down Parsing Algorithm

• Push (Stack, S)
• while not Empty (Stack) do
• if Top(Stack) ??
• then if Top(Stack) Head(input)
• then input tail(input)
• Pop(Stack)
• else error (Stack, input)
• else P OPF (Stack, input)
• Push (Pop(Stack), RHS(P))
• od

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Top-Down Parsing

• Most parsing methods impose bounds on the amount
  of stack lookback and input lookahead. For
  programming languages, a common choice is (1,1).
• We must define OPF (A,t), where A is the top
  element of the stack, and t is the first symbol
  on the input.
• Storage requirements O(n2), where n is the size
  of the grammar vocabulary
• (a few hundred).

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LL(1) Grammars

• Definition
• A CFG G is LL(1) (Left-to-right, Left-most,
  one-symbol lookahead)
• iff for all A??, and for all A??, A??, ? ? ?,
• Select (A ? ?) n Select (A ? ?) ?
• Previous example Grammar is not LL(1).
• More later on why, and what do to about it.

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Example

• S ? A b,?
• A ? bAd b
• ? d, ?

Disjoint! Grammar is LL(1)!
d b ?
S S ? A S ? P
A A ? A ? bAd A ?
(At most) one production per entry.
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Parsing
Programming Language Concepts Lecture 6

• Prepared by
• Manuel E. Bermúdez, Ph.D.
• Associate Professor
• University of Florida