# Intro To Parsing. Step By Step

Size: px
Start display at page:

Transcription

1 #1 Intro To Parsing Step By Step

2 #2 Self-Test from Last Time Are practical parsers and scanners based on deterministic or non-deterministic automata? How can regular expressions be used to specify nested constructs? How is a two-dimensional transition table used in tabledriven scanning?

3 #3 Self-Test Answers Are practical parsers and scanners based on deterministic or non-deterministic automata? Deterministic Half credit: they are equivalent w/o convert to DFA How can regular expressions be used to specify nested constructs? They cannot. (Scott Book 2.1.2, second sentence) Nested parentheses ( n ) n are the canonical example. How is a two-dimensional transition table used in tabledriven scanning? new_state = table[old_state][new_character]

4 #4 Cunning Plan Formal Languages Regular Languages Revisited Parser Overview Context-Free Grammars (CFGs) Derivations Ambiguity

5 #5 One-Slide Summary A parser takes a sequence of tokens as input. If the input is valid, it produces a parse tree (or derivation). Context-free grammars are a notation for specifying formal languages. They contain terminals, non-terminals and productions (aka rewrite rules).

6 #6 Languages and Automata Formal languages are very important in CS specially in programming languages Regular languages The weakest formal languages widely used Many applications We will also study context-free languages A stronger type of formal language

7 Limitations of Regular Languages Intuition: A finite automaton that runs long enough must repeat states Pigeonhole Principle: imagine 20 states and 300 input characters A finite automaton can t remember how often it has visited a particular state Only enough to store in which state it is in Cannot count, except up to a finite limit Language of balanced parentheses is not regular: { ( i ) i i 0} #7

8 #8 The Functionality of the Parser Input: sequence of tokens from lexer e.g., the.cl-lex files you make in PA2 Output: parse tree of the program Also called an abstract syntax tree Output: error if the input is not valid e.g., parse error on line 3

9 #9 xample Cool program text if x = y then 1 else 2 fi Parser input (tokens) IF ID = ID THN INT LS INT FI Parser output (tree) IF-THN-LS ID = ID INT INT

10

11 The Role of the Parser Not all sequences of tokens are programs then x * / + 3 while x ; y z then The parser must distinguish between valid and invalid sequences of tokens We need A language or formalism to describe valid sequences of tokens A method (an algorithm) for distinguishing valid from invalid sequences of tokens #11

12 #12 Programming Language Structure Programming languages have recursive structure Consider the language of arithmetic expressions with integers, +, *, and ( ) An expression is either: an integer an expression followed by + followed by expression an expression followed by * followed by expression a ( followed by an expression followed by ) int, int + int, ( int + int) * int are expressions

13 Notation for Programming Languages An alternative notation:! int! +! *! ( ) We can view these rules as rewrite rules We start with and replace occurrences of with some right-hand side! *! ( ) *! ( + ) *!...! (int + int) * int #13

14 #14 Observation All arithmetic expressions can be obtained by a sequence of replacements Any sequence of replacements forms a valid arithmetic expression This means that we cannot obtain ( int ) ) by any sequence of replacements. Why? This notation is a context-free grammar

15 #15 Context Free Grammars A context-free grammar consists of A set of non-terminals N Written in uppercase in these notes A set of terminals T Lowercase or punctuation in these notes A start symbol S (a non-terminal) A set of productions (rewrite rules) Assuming 2 N!! Y 1 Y 2... Y n, or where Y i µ N [ T

16 #16 xamples of CFGs Simple arithmetic expressions:! int! +! *! ( ) One non-terminal: Several terminals: int + * ( ) Called terminals because they are never replaced By convention the non-terminal for the first production is the start symbol

17 #17 The Language of a CFG Read productions as replacement rules: X! Y 1... Y n Means X can be replaced by Y 1... Y n X! Means X can be erased or eaten (replaced with empty string)

18 #18 Key Idea To construct a valid sequence of terminals: Begin with a string consisting of the start symbol S Replace any non-terminal X in the string by a right-hand side of some production X! Y 1 Y n Continue replacing until there are only terminals in the string

19 #19 The Language of a CFG:! More formally, write X 1 X i-1 X i X i+1 X n! X 1 X i-1 Y 1 Y m X i+1 X n if there is a production X i! Y 1 Y m

20 #20 The Language of a CFG:! * Write X 1 X n! * Y 1 Y m if X 1 X n!!! Y 1 Y m in 0 or more steps.

21 #21 The Language of a CFG Let G be a context-free grammar with start symbol S. Then the language of G is: L(G) = { a 1 a n S! * a 1 a n and every a i is a terminal } L(G) is a set of strings over the alphabet of terminals.

22 #22 CFG Language xamples S! 0 also written as S! 0 1 S! 1 Generates the language { 0, 1 } What about S! 1 A A! 0 1 What about S! 1 A A! 0 1 A What about S! ( S ) Pencil and paper corner!

23 #23 Arithmetic xample Simple arithmetic expressions: + () id Some elements of the language: id id + id (id) id id (id) id id (id)

24 #24 Cool xample A fragment of COOL: XPR if XPR then XPR else XPR fi while XPR loop XPR pool id

25 #25 Cool xample (Cont.) Some elements of the language id if id then id else id fi while id loop id pool if while id loop id pool then id else id if if id then id else id fi then id else id fi

26 #26 Notes The idea of a CFG is a big step. But: Membership in a language is yes or no we also need parse tree of the input We must handle errors gracefully Need an implementation of CFGs bison, yacc, ocamlyacc, ply, etc.

27 #27 More Notes Form of the grammar is important Many grammars generate the same language Give me an example. Automatic tools are sensitive to the grammar Note: Tools for regular languages (e.g., flex) are also sensitive to the form of the regular expression, but this is rarely a problem in practice

28 #28 Derivations and Parse Trees A derivation is a sequence of productions S!! A derivation can be drawn as a tree Start symbol is the tree s root For a production X! Y 1 Y n add children Y 1,, Y n to node X

29 #29 Derivation xample Grammar + () id String id id + id We're going to build a derivation!

30 #30 Derivation xample (Cont.) + + id + id id + id id + id Thus!* id * id + id

31 #31 Derivation in Detail (1)

32 #32 Derivation in Detail (2) + +

33 #33 Derivation in Detail (3) *

34 #34 Derivation in Detail (4) * id + id

35 #35 Derivation in Detail (5) id + * id id + id id

36 #36 Derivation in Detail (6) id + * id id id + id id + id id id

37 #37 Notes on Derivations A parse tree has Terminals at the leaves Non-terminals at the interior nodes A left-right traversal of the leaves is the original input The parse tree shows the association of operations, the input string does not!

38 Some CS Research Highlights 80% of CS1 and CS2 courses allow students to collaborate. Is there any evidence that pair programming is helpful? See L. Williams (e.g., Lessons Learned from Seven Years of Pair Programming at North Carolina State University ) About one-third of edits to software are systematic: similar changes to many locations. What can we do to help with such copy-and-paste edits? See M. Kim (e.g., LAS: An xample-based Program Transformation Tool for Locating and Applying Systematic dits ) Searches and clicks are increasingly critical to on-line advertising. How can we make use of such information while preserving privacy? See N. Mishra (e.g., Releasing Search Queries and Clicks Privately ) Crowdsourcing services like Mechanical Turk are increasingly popular and serve as the backbone of many businesses. How can we make the most of such data? See J. Widom (e.g., Query Optimization over Crowdsourced Data ) very day more defects are reported than developers can address. How can we automatically fix bugs? See C. Le Goues (e.g., A systematic study of automated program repair: Fixing 55 out of 105 bugs for \$8 each ) #38

39 Q: Games (548 / 842) In the card game Hearts, how many points would you accumulate if you ended up with all of the Queens and all of the Jacks? (Standard scoring.)

40 Q: Music (158 / 842) Name the "shocking" 1976 line dance created by Ric Silver and sung and choreographed by Marcia Griffiths.

41 Q: Games (582 / 842) Minty, Snuzzle, Butterscotch, Bluebelle, Cotton Candy, and Blossom were the first six characters in the 1982 edition of this series of Hasbro-produced brushable hoofed dolls with designs on their hips.

42 #42 Left-most and Right-most Derivations The previous step-by-step example was a left-most derivation At each step, replace the leftmost non-terminal + +id Right-Most Derivation There is an equivalent notion of a right-most derivation Final result shown here: Step-by-step shown next + id id + id id id + id

43 #43 Right-most Derivation in Detail (1)

44 #44 Right-most Derivation in Detail (2) + +

45 #45 Right-most Derivation in Detail (3) id id

46 #46 Right-most Derivation in Detail (4) + + +id * id + id

47 #47 Right-most Derivation in Detail (5) + + +id + id * id id + id id

48 #48 Right-most Derivation in Detail (6) + + +id + id * id id + id id id + id id id

49 #49 Derivations and Parse Trees Note that for each parse tree there is a left-most and a right-most derivation The difference is the order in which branches are added We will start with a parsing technique that yields left-most derivations Later we'll move on to right-most derivations

50 #50 Summary of Derivations We are not just interested in whether s 2 L(G) We also need a parse tree for s A derivation defines a parse tree But one parse tree may have many derivations Left-most and right-most derivations are important in parser implementation

51 #51 Review A parser consumes a sequence of tokens s and produces a parse tree Issues: How do we recognize that s 2 L(G)? A parse tree of s describes how s L(G) Ambiguity: more than one parse tree (interpretation) for some string s rror: no parse tree for some string s How do we construct the parse tree?

52 #52 Ambiguity (Ambiguous) Grammar G! + * ( ) int Some strings in L(G) int + int + int int * int + int

53 #53 Ambiguity. xample The string int + int + int has two parse trees + + int + int in t in t int + int + is left-associative

54 #54 Ambiguity. xample The string int * int + int has two parse trees + * int * int in t in t int + int * has higher precedence than +

55 Ambiguity (Cont.) A grammar is ambiguous if it has more than one parse tree for some string quivalently, there is more than one rightmost or left-most derivation for some string Ambiguity is bad Leaves meaning of some programs ill-defined Ambiguity is common in programming languages Arithmetic expressions IF-THN-LS #55

56 #56 Dealing with Ambiguity There are several ways to handle ambiguity Most direct method is to rewrite the grammar unambiguously! + T T T! T * int int ( ) nforces precedence of * over + nforces left-associativity of + and *

57 #57 Ambiguity. xample The int * int + int has ony one parse tree now + T * T int int + T * int int int int

58 #58 Ambiguity: The Dangling lse Consider this new grammar if then if then else OTHR This grammar is also ambiguous

59 #59 The Dangling lse: xample The string if 1 then if 2 then 3 else 4 has two parse trees if if 1 if 4 1 if Typically we want the second form

60 #60 The Dangling lse: A Fix else matches the closest unmatched then We can describe this in the grammar (distinguish between matched and unmatched then ) MIF /* all then are matched */ UIF /* some then are unmatched */ MIF if then MIF else MIF OTHR UIF if then if then MIF else UIF Describes the same set of strings

61 #61 The Dangling lse: xample Revisited The exp if 1 then if 2 then 3 else 4 if if 1 if 1 if A valid parse tree (for a UIF) Not valid because the then expression is not a MIF

62 Ambiguity No general techniques for handling ambiguity Impossible to convert automatically every ambiguous grammar to an unambiguous one Used with care, ambiguity can simplify the grammar Sometimes allows more natural definitions So we need disambiguation mechanisms As shown next... #62

63 #63 Precedence and Associativity Declarations Instead of rewriting the grammar Use the more natural (ambiguous) grammar Along with disambiguating declarations Most tools allow precedence and associativity declarations to disambiguate grammars xamples

64 #64 Associativity Declarations Consider the grammar + int And the string: int + int + int int int + int int int int Left-associativity declaration: %left + %left *

65 #65 Review We can specify language syntax using CFG A parser will answer whether s L(G) and will build a parse tree and pass on to the rest of the compiler Next: How do we answer s L(G) and build a parse tree?

66 #66 Homework RS1 Recommended for Today PA2 (Lexer) Due You may work in pairs. CA1 (Dead Code) Due You may work in pairs.

### ( ) i 0. Outline. Regular languages revisited. Introduction to Parsing. Parser overview. Context-free grammars (CFG s) Lecture 5.

Outline Regular languages revisited Introduction to Parsing Lecture 5 Parser overview Context-free grammars (CFG s) Derivations Prof. Aiken CS 143 Lecture 5 1 Ambiguity Prof. Aiken CS 143 Lecture 5 2 Languages

### Introduction to Parsing. Lecture 5. Professor Alex Aiken Lecture #5 (Modified by Professor Vijay Ganesh)

Introduction to Parsing Lecture 5 (Modified by Professor Vijay Ganesh) 1 Outline Regular languages revisited Parser overview Context-free grammars (CFG s) Derivations Ambiguity 2 Languages and Automata

### Outline. Regular languages revisited. Introduction to Parsing. Parser overview. Context-free grammars (CFG s) Lecture 5. Derivations.

Outline Regular languages revisited Introduction to Parsing Lecture 5 Parser overview Context-free grammars (CFG s) Derivations Prof. Aiken CS 143 Lecture 5 1 Ambiguity Prof. Aiken CS 143 Lecture 5 2 Languages

### Introduction to Parsing. Lecture 5

Introduction to Parsing Lecture 5 1 Outline Regular languages revisited Parser overview Context-free grammars (CFG s) Derivations Ambiguity 2 Languages and Automata Formal languages are very important

### Introduction to Parsing Ambiguity and Syntax Errors

Introduction to Parsing Ambiguity and Syntax rrors Outline Regular languages revisited Parser overview Context-free grammars (CFG s) Derivations Ambiguity Syntax errors Compiler Design 1 (2011) 2 Languages

### Introduction to Parsing. Lecture 5

Introduction to Parsing Lecture 5 1 Outline Regular languages revisited Parser overview Context-free grammars (CFG s) Derivations Ambiguity 2 Languages and Automata Formal languages are very important

### Introduction to Parsing Ambiguity and Syntax Errors

Introduction to Parsing Ambiguity and Syntax rrors Outline Regular languages revisited Parser overview Context-free grammars (CFG s) Derivations Ambiguity Syntax errors 2 Languages and Automata Formal

### Grammars and ambiguity. CS164 3:30-5:00 TT 10 Evans. Prof. Bodik CS 164 Lecture 8 1

Grammars and ambiguity CS164 3:30-5:00 TT 10 vans 1 Overview derivations and parse trees different derivations produce may produce same parse tree ambiguous grammars what they are and how to fix them 2

### Introduction to Parsing. Lecture 8

Introduction to Parsing Lecture 8 Adapted from slides by G. Necula Outline Limitations of regular languages Parser overview Context-free grammars (CFG s) Derivations Languages and Automata Formal languages

### Outline. Limitations of regular languages. Introduction to Parsing. Parser overview. Context-free grammars (CFG s)

Outline Limitations of regular languages Introduction to Parsing Parser overview Lecture 8 Adapted from slides by G. Necula Context-free grammars (CFG s) Derivations Languages and Automata Formal languages

### E E+E E E (E) id. id + id E E+E. id E + E id id + E id id + id. Overview. derivations and parse trees. Grammars and ambiguity. ambiguous grammars

Overview Grammars and ambiguity CS164 3:30-5:00 TT 10 vans derivations and parse trees dferent derivations produce may produce same parse tree ambiguous grammars what they are and how to fix them 1 2 Recall:

### Parsing: Derivations, Ambiguity, Precedence, Associativity. Lecture 8. Professor Alex Aiken Lecture #5 (Modified by Professor Vijay Ganesh)

Parsing: Derivations, Ambiguity, Precedence, Associativity Lecture 8 (Modified by Professor Vijay Ganesh) 1 Topics covered so far Regular languages and Finite automaton Parser overview Context-free grammars

### Context-Free Grammars

Context-Free Grammars Lecture 7 http://webwitch.dreamhost.com/grammar.girl/ Outline Scanner vs. parser Why regular expressions are not enough Grammars (context-free grammars) grammar rules derivations

### Outline. Parser overview Context-free grammars (CFG s) Derivations Syntax-Directed Translation

Outline Introduction to Parsing (adapted from CS 164 at Berkeley) Parser overview Context-free grammars (CFG s) Derivations Syntax-Directed ranslation he Functionality of the Parser Input: sequence of

### Outline. Limitations of regular languages Parser overview Context-free grammars (CFG s) Derivations Syntax-Directed Translation

Outline Introduction to Parsing Lecture 8 Adapted from slides by G. Necula and R. Bodik Limitations of regular languages Parser overview Context-free grammars (CG s) Derivations Syntax-Directed ranslation

### Ambiguity. Lecture 8. CS 536 Spring

Ambiguity Lecture 8 CS 536 Spring 2001 1 Announcement Reading Assignment Context-Free Grammars (Sections 4.1, 4.2) Programming Assignment 2 due Friday! Homework 1 due in a week (Wed Feb 21) not Feb 25!

### Programming Languages & Translators PARSING. Baishakhi Ray. Fall These slides are motivated from Prof. Alex Aiken: Compilers (Stanford)

Programming Languages & Translators PARSING Baishakhi Ray Fall 2018 These slides are motivated from Prof. Alex Aiken: Compilers (Stanford) Languages and Automata Formal languages are very important in

### Ambiguity, Precedence, Associativity & Top-Down Parsing. Lecture 9-10

Ambiguity, Precedence, Associativity & Top-Down Parsing Lecture 9-10 (From slides by G. Necula & R. Bodik) 9/18/06 Prof. Hilfinger CS164 Lecture 9 1 Administrivia Please let me know if there are continued

### Formal Languages and Compilers Lecture V: Parse Trees and Ambiguous Gr

Formal Languages and Compilers Lecture V: Parse Trees and Ambiguous Grammars Free University of Bozen-Bolzano Faculty of Computer Science POS Building, Room: 2.03 artale@inf.unibz.it http://www.inf.unibz.it/

### Context-Free Grammars

CFG2: Ambiguity Context-Free Grammars CMPT 379: Compilers Instructor: Anoop Sarkar anoopsarkar.github.io/compilers-class Ambiguity - / - / ( ) - / / - 16-06-22 2 Ambiguity Grammar is ambiguous if more

### Syntax Analysis Check syntax and construct abstract syntax tree

Syntax Analysis Check syntax and construct abstract syntax tree if == = ; b 0 a b Error reporting and recovery Model using context free grammars Recognize using Push down automata/table Driven Parsers

### Ambiguity. Grammar E E + E E * E ( E ) int. The string int * int + int has two parse trees. * int

Administrivia Ambiguity, Precedence, Associativity & op-down Parsing eam assignments this evening for all those not listed as having one. HW#3 is now available, due next uesday morning (Monday is a holiday).

### Compilers and computer architecture From strings to ASTs (2): context free grammars

1 / 1 Compilers and computer architecture From strings to ASTs (2): context free grammars Martin Berger October 2018 Recall the function of compilers 2 / 1 3 / 1 Recall we are discussing parsing Source

### CSE P 501 Compilers. Parsing & Context-Free Grammars Hal Perkins Winter /15/ Hal Perkins & UW CSE C-1

CSE P 501 Compilers Parsing & Context-Free Grammars Hal Perkins Winter 2008 1/15/2008 2002-08 Hal Perkins & UW CSE C-1 Agenda for Today Parsing overview Context free grammars Ambiguous grammars Reading:

### Ambiguity and Errors Syntax-Directed Translation

Outline Ambiguity (revisited) Ambiguity and rrors Syntax-Directed Translation xtensions of CFG for parsing Precedence declarations rror handling Semantic actions Constructing a parse tree CS780(Prasad)

### Theoretical Part. Chapter one:- - What are the Phases of compiler? Answer:

Theoretical Part Chapter one:- - What are the Phases of compiler? Six phases Scanner Parser Semantic Analyzer Source code optimizer Code generator Target Code Optimizer Three auxiliary components Literal

### Optimizing Finite Automata

Optimizing Finite Automata We can improve the DFA created by MakeDeterministic. Sometimes a DFA will have more states than necessary. For every DFA there is a unique smallest equivalent DFA (fewest states

### programming languages need to be precise a regular expression is one of the following: tokens are the building blocks of programs

Chapter 2 :: Programming Language Syntax Programming Language Pragmatics Michael L. Scott Introduction programming languages need to be precise natural languages less so both form (syntax) and meaning

### ([1-9] 1[0-2]):[0-5][0-9](AM PM)? What does the above match? Matches clock time, may or may not be told if it is AM or PM.

What is the corresponding regex? [2-9]: ([1-9] 1[0-2]):[0-5][0-9](AM PM)? What does the above match? Matches clock time, may or may not be told if it is AM or PM. CS 230 - Spring 2018 4-1 More CFG Notation

### COP 3402 Systems Software Syntax Analysis (Parser)

COP 3402 Systems Software Syntax Analysis (Parser) Syntax Analysis 1 Outline 1. Definition of Parsing 2. Context Free Grammars 3. Ambiguous/Unambiguous Grammars Syntax Analysis 2 Lexical and Syntax Analysis

### Chapter 3: CONTEXT-FREE GRAMMARS AND PARSING Part2 3.3 Parse Trees and Abstract Syntax Trees

Chapter 3: CONTEXT-FREE GRAMMARS AND PARSING Part2 3.3 Parse Trees and Abstract Syntax Trees 3.3.1 Parse trees 1. Derivation V.S. Structure Derivations do not uniquely represent the structure of the strings

### CSE P 501 Compilers. Parsing & Context-Free Grammars Hal Perkins Spring UW CSE P 501 Spring 2018 C-1

CSE P 501 Compilers Parsing & Context-Free Grammars Hal Perkins Spring 2018 UW CSE P 501 Spring 2018 C-1 Administrivia Project partner signup: please find a partner and fill out the signup form by noon

### Syntax Analysis. Prof. James L. Frankel Harvard University. Version of 6:43 PM 6-Feb-2018 Copyright 2018, 2015 James L. Frankel. All rights reserved.

Syntax Analysis Prof. James L. Frankel Harvard University Version of 6:43 PM 6-Feb-2018 Copyright 2018, 2015 James L. Frankel. All rights reserved. Context-Free Grammar (CFG) terminals non-terminals start

### Architecture of Compilers, Interpreters. CMSC 330: Organization of Programming Languages. Front End Scanner and Parser. Implementing the Front End

Architecture of Compilers, Interpreters : Organization of Programming Languages ource Analyzer Optimizer Code Generator Context Free Grammars Intermediate Representation Front End Back End Compiler / Interpreter

### Lexical Analysis. Finite Automata. (Part 2 of 2)

# Lexical Analysis Finite Automata (Part 2 of 2) PA0, PA Although we have included the tricky file ends without a newline testcases in previous years, students made good cases against them (e.g., they

### CMSC 330: Organization of Programming Languages

CMSC 330: Organization of Programming Languages Context Free Grammars and Parsing 1 Recall: Architecture of Compilers, Interpreters Source Parser Static Analyzer Intermediate Representation Front End Back

### CMSC 330: Organization of Programming Languages

CMSC 330: Organization of Programming Languages Context Free Grammars 1 Architecture of Compilers, Interpreters Source Analyzer Optimizer Code Generator Abstract Syntax Tree Front End Back End Compiler

### Parsing Part II. (Ambiguity, Top-down parsing, Left-recursion Removal)

Parsing Part II (Ambiguity, Top-down parsing, Left-recursion Removal) Ambiguous Grammars Definitions If a grammar has more than one leftmost derivation for a single sentential form, the grammar is ambiguous

### CMSC 330: Organization of Programming Languages. Architecture of Compilers, Interpreters

: Organization of Programming Languages Context Free Grammars 1 Architecture of Compilers, Interpreters Source Scanner Parser Static Analyzer Intermediate Representation Front End Back End Compiler / Interpreter

### Bottom-Up Parsing. Lecture 11-12

Bottom-Up Parsing Lecture 11-12 (From slides by G. Necula & R. Bodik) 9/22/06 Prof. Hilfinger CS164 Lecture 11 1 Bottom-Up Parsing Bottom-up parsing is more general than topdown parsing And just as efficient

### Bottom-Up Parsing. Lecture 11-12

Bottom-Up Parsing Lecture 11-12 (From slides by G. Necula & R. Bodik) 2/20/08 Prof. Hilfinger CS164 Lecture 11 1 Administrivia Test I during class on 10 March. 2/20/08 Prof. Hilfinger CS164 Lecture 11

### CMSC 330: Organization of Programming Languages

CMSC 330: Organization of Programming Languages Context Free Grammars 1 Architecture of Compilers, Interpreters Source Analyzer Optimizer Code Generator Abstract Syntax Tree Front End Back End Compiler

### Compilers Course Lecture 4: Context Free Grammars

Compilers Course Lecture 4: Context Free Grammars Example: attempt to define simple arithmetic expressions using named regular expressions: num = [0-9]+ sum = expr "+" expr expr = "(" sum ")" num Appears

### Properties of Regular Expressions and Finite Automata

Properties of Regular Expressions and Finite Automata Some token patterns can t be defined as regular expressions or finite automata. Consider the set of balanced brackets of the form [[[ ]]]. This set

### Lecture 4: Syntax Specification

The University of North Carolina at Chapel Hill Spring 2002 Lecture 4: Syntax Specification Jan 16 1 Phases of Compilation 2 1 Syntax Analysis Syntax: Webster s definition: 1 a : the way in which linguistic

### Introduction to Parsing

Introduction to Parsing The Front End Source code Scanner tokens Parser IR Errors Parser Checks the stream of words and their parts of speech (produced by the scanner) for grammatical correctness Determines

### CMSC 330: Organization of Programming Languages. Context Free Grammars

CMSC 330: Organization of Programming Languages Context Free Grammars 1 Architecture of Compilers, Interpreters Source Analyzer Optimizer Code Generator Abstract Syntax Tree Front End Back End Compiler

### Formal Languages and Compilers Lecture VI: Lexical Analysis

Formal Languages and Compilers Lecture VI: Lexical Analysis Free University of Bozen-Bolzano Faculty of Computer Science POS Building, Room: 2.03 artale@inf.unibz.it http://www.inf.unibz.it/ artale/ Formal

### CS 314 Principles of Programming Languages

CS 314 Principles of Programming Languages Lecture 5: Syntax Analysis (Parsing) Zheng (Eddy) Zhang Rutgers University January 31, 2018 Class Information Homework 1 is being graded now. The sample solution

### Compiler Design Concepts. Syntax Analysis

Compiler Design Concepts Syntax Analysis Introduction First task is to break up the text into meaningful words called tokens. newval=oldval+12 id = id + num Token Stream Lexical Analysis Source Code (High

### EECS 6083 Intro to Parsing Context Free Grammars

EECS 6083 Intro to Parsing Context Free Grammars Based on slides from text web site: Copyright 2003, Keith D. Cooper, Ken Kennedy & Linda Torczon, all rights reserved. 1 Parsing sequence of tokens parser

### CMSC 330: Organization of Programming Languages. Context Free Grammars

CMSC 330: Organization of Programming Languages Context Free Grammars 1 Architecture of Compilers, Interpreters Source Analyzer Optimizer Code Generator Abstract Syntax Tree Front End Back End Compiler

### Chapter 3: CONTEXT-FREE GRAMMARS AND PARSING Part 1

Chapter 3: CONTEXT-FREE GRAMMARS AND PARSING Part 1 1. Introduction Parsing is the task of Syntax Analysis Determining the syntax, or structure, of a program. The syntax is defined by the grammar rules

### Fall Compiler Principles Context-free Grammars Refresher. Roman Manevich Ben-Gurion University of the Negev

Fall 2016-2017 Compiler Principles Context-free Grammars Refresher Roman Manevich Ben-Gurion University of the Negev 1 xample grammar S S ; S S id := S print (L) id num + L L L, shorthand for Statement

### MIT Specifying Languages with Regular Expressions and Context-Free Grammars. Martin Rinard Massachusetts Institute of Technology

MIT 6.035 Specifying Languages with Regular essions and Context-Free Grammars Martin Rinard Massachusetts Institute of Technology Language Definition Problem How to precisely define language Layered structure

### MIT Specifying Languages with Regular Expressions and Context-Free Grammars

MIT 6.035 Specifying Languages with Regular essions and Context-Free Grammars Martin Rinard Laboratory for Computer Science Massachusetts Institute of Technology Language Definition Problem How to precisely

### Parsing II Top-down parsing. Comp 412

COMP 412 FALL 2018 Parsing II Top-down parsing Comp 412 source code IR Front End Optimizer Back End IR target code Copyright 2018, Keith D. Cooper & Linda Torczon, all rights reserved. Students enrolled

### Chapter 3: Lexing and Parsing

Chapter 3: Lexing and Parsing Aarne Ranta Slides for the book Implementing Programming Languages. An Introduction to Compilers and Interpreters, College Publications, 2012. Lexing and Parsing* Deeper understanding

### Where We Are. CMSC 330: Organization of Programming Languages. This Lecture. Programming Languages. Motivation for Grammars

CMSC 330: Organization of Programming Languages Context Free Grammars Where We Are Programming languages Ruby OCaml Implementing programming languages Scanner Uses regular expressions Finite automata Parser

### CS415 Compilers. Syntax Analysis. These slides are based on slides copyrighted by Keith Cooper, Ken Kennedy & Linda Torczon at Rice University

CS415 Compilers Syntax Analysis These slides are based on slides copyrighted by Keith Cooper, Ken Kennedy & Linda Torczon at Rice University Limits of Regular Languages Advantages of Regular Expressions

### UNIT -2 LEXICAL ANALYSIS

OVER VIEW OF LEXICAL ANALYSIS UNIT -2 LEXICAL ANALYSIS o To identify the tokens we need some method of describing the possible tokens that can appear in the input stream. For this purpose we introduce

### CMSC 350: COMPILER DESIGN

Lecture 11 CMSC 350: COMPILER DESIGN see HW3 LLVMLITE SPECIFICATION Eisenberg CMSC 350: Compilers 2 Discussion: Defining a Language Premise: programming languages are purely formal objects We (as language

### CSE 401 Midterm Exam Sample Solution 2/11/15

Question 1. (10 points) Regular expression warmup. For regular expression questions, you must restrict yourself to the basic regular expression operations covered in class and on homework assignments:

### CMSC 330: Organization of Programming Languages. Context Free Grammars

CMSC 330: Organization of Programming Languages Context Free Grammars 1 Architecture of Compilers, Interpreters Source Analyzer Optimizer Code Generator Abstract Syntax Tree Front End Back End Compiler

### Parsing. Note by Baris Aktemur: Our slides are adapted from Cooper and Torczon s slides that they prepared for COMP 412 at Rice.

Parsing Note by Baris Aktemur: Our slides are adapted from Cooper and Torczon s slides that they prepared for COMP 412 at Rice. Copyright 2010, Keith D. Cooper & Linda Torczon, all rights reserved. Students

### CSCI312 Principles of Programming Languages!

CSCI312 Principles of Programming Languages!! Chapter 3 Regular Expression and Lexer Xu Liu Recap! Copyright 2006 The McGraw-Hill Companies, Inc. Clite: Lexical Syntax! Input: a stream of characters from

### Part 5 Program Analysis Principles and Techniques

1 Part 5 Program Analysis Principles and Techniques Front end 2 source code scanner tokens parser il errors Responsibilities: Recognize legal programs Report errors Produce il Preliminary storage map Shape

### Syntax Analysis Part I

Syntax Analysis Part I Chapter 4: Context-Free Grammars Slides adapted from : Robert van Engelen, Florida State University Position of a Parser in the Compiler Model Source Program Lexical Analyzer Token,

### Formal Languages and Grammars. Chapter 2: Sections 2.1 and 2.2

Formal Languages and Grammars Chapter 2: Sections 2.1 and 2.2 Formal Languages Basis for the design and implementation of programming languages Alphabet: finite set Σ of symbols String: finite sequence

### Lecture 8: Deterministic Bottom-Up Parsing

Lecture 8: Deterministic Bottom-Up Parsing (From slides by G. Necula & R. Bodik) Last modified: Fri Feb 12 13:02:57 2010 CS164: Lecture #8 1 Avoiding nondeterministic choice: LR We ve been looking at general

### A Simple Syntax-Directed Translator

Chapter 2 A Simple Syntax-Directed Translator 1-1 Introduction The analysis phase of a compiler breaks up a source program into constituent pieces and produces an internal representation for it, called

### THE COMPILATION PROCESS EXAMPLE OF TOKENS AND ATTRIBUTES

THE COMPILATION PROCESS Character stream CS 403: Scanning and Parsing Stefan D. Bruda Fall 207 Token stream Parse tree Abstract syntax tree Modified intermediate form Target language Modified target language

### CS 315 Programming Languages Syntax. Parser. (Alternatively hand-built) (Alternatively hand-built)

Programming languages must be precise Remember instructions This is unlike natural languages CS 315 Programming Languages Syntax Precision is required for syntax think of this as the format of the language

### CS 403: Scanning and Parsing

CS 403: Scanning and Parsing Stefan D. Bruda Fall 2017 THE COMPILATION PROCESS Character stream Scanner (lexical analysis) Token stream Parser (syntax analysis) Parse tree Semantic analysis Abstract syntax

### Parsing. source code. while (k<=n) {sum = sum+k; k=k+1;}

Compiler Construction Grammars Parsing source code scanner tokens regular expressions lexical analysis Lennart Andersson parser context free grammar Revision 2012 01 23 2012 parse tree AST builder (implicit)

### MA513: Formal Languages and Automata Theory Topic: Context-free Grammars (CFG) Lecture Number 18 Date: September 12, 2011

MA53: Formal Languages and Automata Theory Topic: Context-free Grammars (CFG) Lecture Number 8 Date: September 2, 20 xercise: Define a context-free grammar that represents (a simplification of) expressions

### Lecture 7: Deterministic Bottom-Up Parsing

Lecture 7: Deterministic Bottom-Up Parsing (From slides by G. Necula & R. Bodik) Last modified: Tue Sep 20 12:50:42 2011 CS164: Lecture #7 1 Avoiding nondeterministic choice: LR We ve been looking at general

### Structure of a compiler. More detailed overview of compiler front end. Today we ll take a quick look at typical parts of a compiler.

More detailed overview of compiler front end Structure of a compiler Today we ll take a quick look at typical parts of a compiler. This is to give a feeling for the overall structure. source program lexical

### Chapter 2 :: Programming Language Syntax

Chapter 2 :: Programming Language Syntax Michael L. Scott kkman@sangji.ac.kr, 2015 1 Regular Expressions A regular expression is one of the following: A character The empty string, denoted by Two regular

### Context Free Languages

Context Free Languages COMP2600 Formal Methods for Software Engineering Katya Lebedeva Australian National University Semester 2, 2016 Slides by Katya Lebedeva and Ranald Clouston. COMP 2600 Context Free

### Context-Free Languages & Grammars (CFLs & CFGs) Reading: Chapter 5

Context-Free Languages & Grammars (CFLs & CFGs) Reading: Chapter 5 1 Not all languages are regular So what happens to the languages which are not regular? Can we still come up with a language recognizer?

### COP4020 Programming Languages. Syntax Prof. Robert van Engelen

COP4020 Programming Languages Syntax Prof. Robert van Engelen Overview n Tokens and regular expressions n Syntax and context-free grammars n Grammar derivations n More about parse trees n Top-down and

### CSCE 314 Programming Languages

CSCE 314 Programming Languages Syntactic Analysis Dr. Hyunyoung Lee 1 What Is a Programming Language? Language = syntax + semantics The syntax of a language is concerned with the form of a program: how

### Principles of Programming Languages COMP251: Syntax and Grammars

Principles of Programming Languages COMP251: Syntax and Grammars Prof. Dekai Wu Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong, China Fall 2006

### MIDTERM EXAMINATION - CS130 - Spring 2003

MIDTERM EXAMINATION - CS130 - Spring 2003 Your full name: Your UCSD ID number: This exam is closed book and closed notes Total number of points in this exam: 120 + 10 extra credit This exam counts for

### Lexical Analysis. COMP 524, Spring 2014 Bryan Ward

Lexical Analysis COMP 524, Spring 2014 Bryan Ward Based in part on slides and notes by J. Erickson, S. Krishnan, B. Brandenburg, S. Olivier, A. Block and others The Big Picture Character Stream Scanner

### Regular Expressions. Agenda for Today. Grammar for a Tiny Language. Programming Language Specifications

Agenda for Today Regular Expressions CSE 413, Autumn 2005 Programming Languages Basic concepts of formal grammars Regular expressions Lexical specification of programming languages Using finite automata

### COP4020 Programming Languages. Syntax Prof. Robert van Engelen

COP4020 Programming Languages Syntax Prof. Robert van Engelen Overview Tokens and regular expressions Syntax and context-free grammars Grammar derivations More about parse trees Top-down and bottom-up

### CSE 3302 Programming Languages Lecture 2: Syntax

CSE 3302 Programming Languages Lecture 2: Syntax (based on slides by Chengkai Li) Leonidas Fegaras University of Texas at Arlington CSE 3302 L2 Spring 2011 1 How do we define a PL? Specifying a PL: Syntax:

### A simple syntax-directed

Syntax-directed is a grammaroriented compiling technique Programming languages: Syntax: what its programs look like? Semantic: what its programs mean? 1 A simple syntax-directed Lexical Syntax Character

### Introduction to Lexical Analysis

Introduction to Lexical Analysis Outline Informal sketch of lexical analysis Identifies tokens in input string Issues in lexical analysis Lookahead Ambiguities Specifying lexical analyzers (lexers) Regular

### CSE450 Translation of Programming Languages. Lecture 4: Syntax Analysis

CSE450 Translation of Programming Languages Lecture 4: Syntax Analysis http://xkcd.com/859 Structure of a Today! Compiler Source Language Lexical Analyzer Syntax Analyzer Semantic Analyzer Int. Code Generator

### Lexical and Syntax Analysis. Top-Down Parsing

Lexical and Syntax Analysis Top-Down Parsing Easy for humans to write and understand String of characters Lexemes identified String of tokens Easy for programs to transform Data structure Syntax A syntax

### LR Parsing LALR Parser Generators

Outline LR Parsing LALR Parser Generators Review of bottom-up parsing Computing the parsing DFA Using parser generators 2 Bottom-up Parsing (Review) A bottom-up parser rewrites the input string to the

### Semantic Analysis. Lecture 9. February 7, 2018

Semantic Analysis Lecture 9 February 7, 2018 Midterm 1 Compiler Stages 12 / 14 COOL Programming 10 / 12 Regular Languages 26 / 30 Context-free Languages 17 / 21 Parsing 20 / 23 Extra Credit 4 / 6 Average

### Introduction to Lexing and Parsing

Introduction to Lexing and Parsing ECE 351: Compilers Jon Eyolfson University of Waterloo June 18, 2012 1 Riddle Me This, Riddle Me That What is a compiler? 1 Riddle Me This, Riddle Me That What is a compiler?

### Syntax. Syntax. We will study three levels of syntax Lexical Defines the rules for tokens: literals, identifiers, etc.

Syntax Syntax Syntax defines what is grammatically valid in a programming language Set of grammatical rules E.g. in English, a sentence cannot begin with a period Must be formal and exact or there will

### Part 3. Syntax analysis. Syntax analysis 96

Part 3 Syntax analysis Syntax analysis 96 Outline 1. Introduction 2. Context-free grammar 3. Top-down parsing 4. Bottom-up parsing 5. Conclusion and some practical considerations Syntax analysis 97 Structure