# 4 (c) parsing. Parsing. Top down vs. bo5om up parsing

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1 4 (c) parsing Parsing A grammar describes syntac2cally legal strings in a language A recogniser simply accepts or rejects strings A generator produces strings A parser constructs a parse tree for a string Two common types of parsers: bo=om- up or data driven top- down or hypothesis driven A recursive descent parser easily implements a top- down parser for simple grammars Top down vs. bo5om up parsing The parsing problem is to connect the root node S with the tree leaves, the input Top- down parsers: starts construc2ng the parse tree at the top (root) and move A = * 4 / 5 down towards the leaves. Easy to implement by hand, but requires restricted grammars. E.g.: - Predic2ve parsers (e.g., LL(k)) Bo5om- up parsers: build nodes on the bo=om of the parse tree first. Suitable for automa2c parser genera2on, handles larger class of grammars. E.g.: shil- reduce parser (or LR(k) parsers) Both are general techniques that can be made to work for all languages (but not all grammars!) S Top down vs. bo5om up parsing Both are general techniques that can be made to work for all languages (but not all grammars!) Recall that a given language can be described by several grammars Both of these grammars describe the same language E -> E + Num E -> Num E -> Num + E E -> Num The first one, with it s lel recursion, causes problems for top down parsers Q: what? For a given parsing technique, we may have to transform the grammar to work with it 1

2 Parsing complexity How hard is parsing? How to we measure that? Parsing an arbitrary CFG is O(n 3 ) - - it can take 2me propor2onal the cube of the # of input symbols This is bad! Q: why? If we constrain the grammar, we can guarentee linear 2me parsing. This is good! Q: why? Two important (for PL) classes of linear- 2me parsers LL parsers: for LL grammars using a top- down approach LR parsers: for LR grammars using a bo=om- up strategy LL(n) : LeL to right, LeLmost deriva2on, look ahead n symbols LR(n) : LeL to right, Rightmost deriva2on, look ahead n symbols Top Down Parsing Methods Simplest method is a full- backup, recur- sive descent parser OLen used for parsing simple languages Write recursive recognizers (subrou2nes) for each grammar rule If rules succeeds perform some ac2on (i.e., build a tree node, emit code, etc.) If rule fails, return failure. Caller may try another choice or fail On failure it backs up Top Down Parsing Methods: Problems Grammar rules which are lel- recursive lead to non- termina2on! When going forward, parser consumes tokens from input, what happens if we have to back up? Q: sugges2ons? Algorithms that use backup tend to be, in general, inefficient There might be a large number of possibili2es to try before finding the right one or giving up Garden Path Sentences In natural languages, a garden path sentence is one that starts in such a way that a person s most likely interpreta2on is wrong Classic examples: The old man the boat The horse raced past the barn fell Readers are lured into a parse that turns out to be a dead end Recovery is difficult or impossible 2

3 Problems Recursive Decent Parsing Example Some grammars cause problems for top down parsers Top down parsers do not work with lel- recursive grammars E.g., one with a rule like: E - > E + T We can transform a lel- recursive grammar into one which is not A top down grammar can limit backtracking if it only has one rule per non- terminal The technique of rule factoring can be used to eliminate mul2ple rules for a non- terminal LeP- recursive grammars A grammar is lel recursive if it has rules like X -> X β Or if it has indirect lel recursion, as in X -> A β A -> X Q: Why is this a problem? A: can lead to non- termina2ng recursion! LeP- recursive grammars Consider E -> E + Num E -> Num We can manually or automa2cally rewrite any grammar to remove lel- recursion This makes it usable for a top- down parser 3

4 EliminaQon of LeP Recursion General LeP Recursion Consider lel- recursive grammar S S α S -> β S generates strings β β α β α α Rewrite using right- recursion S β S S α S ε Concretely T -> T + id T-> id T generates strings id id+id id+id+id Rewrite using right- recursion T -> id T -> id T The grammar S A α δ A S β is also lel- recursive because S + S β α where + means can be rewri=en in one or more steps This indirect lel- recursion can also be automa2cally eliminated Summary of Recursive Descent Simple and general parsing strategy LeL- recursion must be eliminated first but that can be done automa2cally Unpopular because of backtracking Thought to be too inefficient In prac2ce, backtracking is eliminated by further restric2ng the grammar to allow us to successfully predict which rule to use PredicQve Parsers Non- terminal with many rules makes parsing hard A predic2ve parser processes the input stream typically from lel to right Is there any other way to do it? Yes for programming languages! It peeks ahead at the upcoming terminal symbols to decide which grammar rule to use next And always makes the right choice of which rule to use How much it can peek ahead is an issue 4

5 PredicQve Parsers An important class of predic2ve parser only peek ahead one token into the stream An an LL(k) parser, does a LeL- to- right parse, a LeLmost- deriva2on and k- symbol lookahead Grammars where one can decide which rule to use by examining only the next token are LL(1) LL(1) grammars are widely used in prac2ce The syntax of a PL can usually be adjusted to enable it to be described with an LL(1) grammar Example: consider the grammar S if E then S else S S begin S L S print E L end L ; S L E num = num PredicQve Parser An S expression starts with an IF, BEGIN, or PRINT token, and an L expression starts with an END or SEMICOLON token, and an E expression has only one rule. By peeking at the next symbol, a parser always knows what rule to apply for this grammar Remember Given a grammar and a string in the language defined by the grammar There may be more than one way to derive the string leading to the same parse tree It depends on the order in which you apply the rules And what parts of the string you choose to rewrite next All of the deriva2ons are valid To simplify the problem and the algorithms, we olen focus on one of two simple deriva2on strategies A le?most deriva2on A rightmost deriva2on LL(k) and LR(k) parsers Two important parser classes are LL(k) and LR(k) The name LL(k) means: L: Le?- to- right scanning of the input L: Construc2ng le?most deriva2on k: max # of input symbols needed to predict parser ac2on The name LR(k) means: L: Le?- to- right scanning of the input R: Construc2ng rightmost deriva2on in reverse k: max # of input symbols needed to select parser ac2on A LR(1) or LL(1) parser never need to look ahead more than one input token to know what parser produc2on rule applies 5

6 PredicQve Parsing and LeP Factoring Consider the grammar E T + E E T T int T int * T T ( E ) Hard to predict because Even le? recursion is removed, a grammar may not be parsable with a LL(1) parser For T, two produc2ons start with int For E, it is not clear how to predict which rule to use Must lep- factor grammar before use for predic2ve parsing LeL- factoring involves rewri2ng rules so that, if a non- terminal has > 1 rule, each begins with a terminal LeP- Factoring Example Add new non- terminals X and Y to factor out common prefixes of rules E T + E E T T int T int * T T ( E ) For each non- terminal the revised grammar, there is either only one rule or every rule begins with a terminal or ε E T X X + E X ε T ( E ) T int Y Y * T Y ε LeP Factoring Consider a rule of the form A => a B1 a B2 a B3 a Bn A top down parser generated from this grammar is inefficient due to backtracking Avoid problem by lel factor the grammar Collect rules with same lel hand side that begin with the same symbols on the right hand side Combine common strings into a single rule and append a new non- terminal to end of new rule Create new rules using this new non- terminal for each of the suffixes to the common produc2on ALer lel factoring: A > a A1 A1 - > B1 B2 B3 Bn Using Parsing Tables LL(1) means that for each non- terminal and lookahead token there is only one produc2on Can be represented as a simple table One dimension for current non- terminal to expand One dimension for next token A table entry contains one rule s ac2on or empty if error Method similar to recursive descent, except For each non- terminal S Look at the next token a Chose the produc2on shown at table cell [S, a] Use a stack to keep track of pending non- terminals Reject when we encounter an error state, accept when we encounter end- of- input 6

7 LL(1) Parsing Table Example LeP- factored grammar E T X X + E ε T ( E ) int Y Y * T ε The LL(1) parsing table int * + ( ) \$ E T X T X X + E ε ε T int Y ( E ) End of input symbol Y * T ε ε ε E T X X + E ε T ( E ) int Y Consider the [E, int] entry Y * T ε When current non- terminal is E & next input int, use produc2on E T X It s the only produc2on that can generate an int in next place Consider the [Y, +] entry When current non- terminal is Y and current token is +, get rid of Y Y can be followed by + only in a deriva2on where Y ε Consider the [E, *] entry Blank entries indicate error situa2ons There is no way to derive a string star2ng with * from non- terminal E LL(1) Parsing Table Example int * + ( ) \$ E T X T X X + E ε ε T int Y ( E ) Y * T ε ε ε LL(1) Parsing Algorithm initialize stack = <S \$> and next repeat case stack of <X, rest> : if T[X,*next] = Y 1 Y n then stack <Y 1 Y n rest>; else error (); <t, rest> : if t == *next ++ then stack <rest>; else error (); until stack == < > where: (1) next points to the next input token (2) X matches some non- terminal (3) t matches some terminal E TX X +E X ε T (E) T int Y Y *T Y ε LL(1) Parsing Example Stack Input Action E \$ int * int \$ pop();push(t X) T X \$ int * int \$ pop();push(int Y) int Y X \$ int * int \$ pop();next++ Y X \$ * int \$ pop();push(* T) * T X \$ * int \$ pop();next++ T X \$ int \$ pop();push(int Y) int Y X \$ int \$ pop();next++; Y X \$ \$ pop() X \$ \$ pop() \$ \$ ACCEPT! int * + ( ) \$ E T X T X X + E ε ε T int Y ( E ) Y * T ε ε ε 7

8 ConstrucQng Parsing Tables No table entry can be mul2ply defined If A α, where in the line of A we place α? In column t where t can start a string derived from α α * t β We say that t First(α) In the column t if α is ε and t can follow an A S * β A t δ We say t Follow(A) With the first and follow sets, we can construct the LL(1) parsing table CompuQng First Sets Defini2on: First(X) = {t X * tα} {ε X * ε} Algorithm sketch (see book for details): 1. for all terminals t do First(t) ß { t } 2. for each produc2on X ε do First(X) ß { ε } 3. if X A 1 A n α and ε First(A i ), 1 i n do add First(α) to First(X) 4. for each X A 1 A n s.t. ε First(A i ), 1 i n do add ε to First(X) 5. repeat steps 4 and 5 un2l no First set can be grown First Sets. Example Recall the grammar E T X X + E ε T ( E ) int Y Y * T ε First sets First( ( ) = { ( } First( T ) = {int, ( } First( ) ) = { ) } First( E ) = {int, ( } First( int) = { int } First( X ) = {+, ε } First( + ) = { + } First( Y ) = {*, ε } First( * ) = { * } CompuQng Follow Sets Defini2on: Follow(X) = { t S * β X t δ } Intui2on If S is the start symbol then \$ Follow(S) If X A B then First(B) Follow(A) and Follow(X) Follow(B) Also if B * ε then Follow(X) Follow(A) 8

9 CompuQng Follow Sets Algorithm sketch: 1. Follow(S) ß { \$ } 2. For each produc2on A α X β add First(β) - {ε} to Follow(X) 3. For each A α X β where ε First(β) add Follow(A) to Follow(X) repeat step(s) un2l no Follow set grows Follow Sets. Example Recall the grammar E T X T ( E ) int Y Follow sets X + E ε Y * T ε Follow( + ) = { int, ( } Follow( * ) = { int, ( } Follow( ( ) = { int, ( } Follow( E ) = {), \$} Follow( X ) = {\$, ) } Follow( T ) = {+, ), \$} Follow( ) ) = {+, ), \$} Follow( Y ) = {+, ), \$} Follow( int) = {*, +, ), \$} ConstrucQng LL(1) Parsing Tables Construct a parsing table T for CFG G For each produc2on A α in G do: For each terminal t First(α) do T[A, t] = α If ε First(α), for each t Follow(A) do T[A, t] = α If ε First(α) and \$ Follow(A) do T[A, \$] = α Notes on LL(1) Parsing Tables If any entry is mul2ply defined then G is not LL(1) Reasons why a grammar is not LL(1) include G is ambiguous G is lel recursive G is not lel- factored Most programming language grammars are not strictly LL(1) There are tools that build LL(1) tables 9

10 Bo5om- up Parsing YACC uses bo=om up parsing. There are two important opera2ons that bo=om- up parsers use: ship and reduce In abstract terms, we do a simula2on of a Push Down Automata as a finite state automata Input: given string to be parsed and the set of produc2ons. Goal: Trace a rightmost deriva2on in reverse by star2ng with the input string and working backwards to the start symbol Algorithm 1. Start with an empty stack and a full input buffer. (The string to be parsed is in the input buffer.) 2. Repeat un2l the input buffer is empty and the stack contains the start symbol. a. ShiL zero or more input symbols onto the stack from input buffer un2l a handle (beta) is found on top of the stack. If no handle is found report syntax error and exit. b. Reduce handle to the nonterminal A. (There is a produc2on A - > beta) 3. Accept input string and return some representa2on of the deriva2on sequence found (e.g.., parse tree) The four key opera2ons in bo=om- up parsing are shil, reduce, accept and error. Bo=om- up parsing is also referred to as shil- reduce parsing. Important thing to note is to know when to shil and when to reduce and to which reduce. Example of Bo5om- up Parsing STACK INPUT BUFFER ACTION \$ num1+num2*num3\$ shift \$num1 +num2*num3\$ reduc \$F +num2*num3\$ reduc \$T +num2*num3\$ reduc \$E +num2*num3\$ shift \$E+ num2*num3\$ shift \$E+num2 *num3\$ reduc \$E+F *num3\$ reduc \$E+T *num3\$ shift E+T* num3\$ shift E+T*num3 \$ reduc E+T*F \$ reduc E+T \$ reduc E \$ accept E - > E+T T E- T T - > T*F F T/F F - > (E) id - E num 10

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