Chap. 5, Top-Down Parsing

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Chap. 5, Top-Down Parsing. J. H. Wang Mar. 29, 2011. Outline. Overview LL(k) Grammars Recursive-Descent LL(1) Parsers Table-Driven LL(1) Parsers Obtaining LL(1) Grammars A Non-LL(1) Language Properties of LL(1) Parsers Parse Table Representation Syntactic Error Recovery and Repair. - PowerPoint PPT Presentation

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Chap. 5, Top-Down Parsing

J. H. WangOct. 26, 2015

Outline

• Overview• LL(k) Grammars• Recursive-Descent LL(1) Parsers• Table-Driven LL(1) Parsers• Obtaining LL(1) Grammars• A Non-LL(1) Language• Properties of LL(1) Parsers• Parse Table Representation• Syntactic Error Recovery and Repair

Overview

• Two forms of top-down parsers– Recursive-descent parsers– Table-driven LL parsers: LL(k) – to be explained

later

• Compiler compilers (or parser generators)– CFG as a language’s definition, parsers can be

automatically constructed– Language revision, update, or extension can be

easily applied to a new parser– Grammar can be proved unambiguous if parser

construction is successful

Top-Down Parsing

• Top-down– To grow a parse tree from root to leaves

• Predictive– Must predict which production rule to be

applied

• LL(k)– Scan input left to right, leftmost derivation, k

symbol lookahead

• Recursive descent– Can be implemented by a set of mutually

recursive procedures

LL(k) Grammars

• Recall from Chap.2– A parsing procedure for each nonterminal A– The procedure is responsible for

accomplishing one step of derivation for the corresponding production

– Choosing production by inspecting the next k tokens. • Predict set for production A is the set of

tokens that trigger the production

– Predict set is determined by the right-hand side (RHS)

• We need a strategy for choosing productions– Predictk(p): the set of length-k token strings

that predict the application of rule p• Input string: a*

• S=>*lmAy1…yn

– P={pProductionsFor(A)|aPredict(p)}• P: empty set -> syntax error• P: more than one productions -> nondeterminism• P: exactly one production -> leftmost parse can proceed

deterministically

How to Compute Predict(p)

• To predict production p: AX1…Xm, m>=0– The set of terminal symbols that are first

produced in some derivation from X1…Xm

– Those terminal symbols that can follow A

– (Fig. 5.1)

• For LL(1) grammar, the productions for each nonterminal A must have disjoint predict sets– Most programming languages have LL(1)

grammars, but some constructs require special attention

• Not all CFGs are LL(1)– More lookahead may be needed: LL(k), k>1– A more powerful parsing method may be

required (Chap. 6)– The grammar may be ambiguous

S

MATCH

PEEK

ADVANCE

ERROR

Recursive-Descent LL(1) Parsers

• Input: token stream ts– PEEK(): to examine the next input token without

advancing the input– ADVANCE(): to advances the input by one token

• To construct a recursive-descent parser– We write a separate procedure for each

nonterminal A– For each production pi, we check each symbol in

the RHS X1…Xm

• Terminal symbol: MATCH(ts, Xi)• Nonterminal symbol: call Xi(ts)

PEEK

PEEK

PEEK

PEEK

PEEK

PEEK

PEEK

PEEK

PEEK

PEEK

PEEK

MATCH

MATCH

MATCH

MATCH

MATCH

MATCH

PEEK

Table-Driven LL(1) Parsers

• Creating recursive-descent parsers can be automated, but– Size of parser code grows with the size of

grammar– Inefficiency: overhead of method calls and returns

• To create table-driven parsers, we use stack to simulate the actions by MATCH() and calls to nonterminals’ procedures– Terminal symbol: MATCH– Nonterminal symbol: table lookup– (Fig. 5.8)

PUSH

MATCH

POP

ERROR

APPLY

APPLY

POP

PUSH

PEEK

PARSER

How to Build LL(1) Parse Table

• The table is indexed by the top-of-stack (TOS) symbol and the next input token– Row: nonterminal symbol– Column: next input token– (Fig. 5.9)

ILL ABLE

Obtaining LL(1) Grammars

• It’s easy to violate the requirement of a unique prediction for each combination of nonterminal and lookahead symbols– Common prefixes– Left recursion

Common Prefixes

• Two productions for the same nonterminal begin with the same string of grammar symbols– Ex. (Fig. 5.12) Not LL(k)• Factoring transformation (Fig. 5.13)

– A-> p

– Ex. (Fig. 5.14)

ACTOR

LIMINATE EFT ECURSION

Left Recursion

• A production is left recursive if its LHS symbol is also the first symbol of its RHS– E.g. StmtList StmtList ; Stmt– AA

| • Eliminating left recursion (Fig. 5.15)

– Ex. (Fig. 5.16)

• Greibach normal form (GNF)– The right-hand sides of all productions begin

with a terminal symbol

A Non-LL(1) Language

• Almost all common programming language constructs: LL(1)– One exception: if-then-else (dangling

else program)– Can be resolved by mandating that each

else is matched to its closest unmatched then

– (Fig. 5.17)

• Ambiguous (Chap. 6)– E.g. if expr then if expr then other else

other• If expr then { if expr then other else other }• If expr then { if expr then other } else other• -> at least two distinct parses

• Dangling bracket language (DBL)– DBL={[i]j|i≥j≥0}

• if expr then Stmt -> [ (opening bracket)• else Stmt -> ] (optional closing bracket)

• Fig. 5.18(a)– S [ S CL

| λCL ] | λ

• E.g. [[] -> ambiguous

• Fig. 5.18(b)– S [ S

| TT [ T ] | λ

– Not ambiguous, but not LL(1)

• Reasons why it’s not LL(k) for any k– [Predict( S[S )

[Predict( ST )[[Predict2( S[S )[[Predict2( ST )…[kPredictk( S[S )[kPredictk( ST )

• When there’s conflict, the else should match the closest then – -> we resolve the conflict in favor of rule 4 (Fig.

5.19)– Some parser generators offer mechanisms for

establishing priorities when conflicts arises

Properties of LL(1) Parsers• A correct, leftmost parse is constructed• All grammars in LL(1) are unambiguous• All table-driven LL(1) parsers operate in linear time and

space with respect to the length of the parsed input– Linear time:

• Suppose grammar is –free, no production can be applied twice without advancing the input

• If the grammar includes , the number of nonterminals that could pop from stack because of the application of -rules is proportional to the length of input

– Linear space: • Stack grows only when a production is applied of the form A->

– If we regard the number and size of productions to be bounded by some constant, then each input token contributes to a constant increase in stack size

• If stack grew superlinearly, then the parser would require more than linear time to push entries on stack

Sections Skipped…

• Parse Table Representation– Compaction– Compression

• Syntactic Error Recovery and Repair– Error detection– Error recovery– Error repair

Thanks for Your Attention!