Cs6601 Distributed Systems Part A
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Parser Tables for Non-LR(1) Grammars with Conflict Resolution Joel E
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Science of Computer Programming 75 (2010) 943–979 Contents lists available at ScienceDirect Science of Computer Programming journal homepage: www.elsevier.com/locate/scico The IELR(1) algorithm for generating minimal LR(1) parser tables for non-LR(1) grammars with conflict resolution Joel E. Denny ∗, Brian A. Malloy School of Computing, Clemson University, Clemson, SC 29634, USA article info a b s t r a c t Article history: There has been a recent effort in the literature to reconsider grammar-dependent software Received 17 July 2008 development from an engineering point of view. As part of that effort, we examine a Received in revised form 31 March 2009 deficiency in the state of the art of practical LR parser table generation. Specifically, LALR Accepted 12 August 2009 sometimes generates parser tables that do not accept the full language that the grammar Available online 10 September 2009 developer expects, but canonical LR is too inefficient to be practical particularly during grammar development. In response, many researchers have attempted to develop minimal Keywords: LR parser table generation algorithms. In this paper, we demonstrate that a well known Grammarware Canonical LR algorithm described by David Pager and implemented in Menhir, the most robust minimal LALR LR(1) implementation we have discovered, does not always achieve the full power of Minimal LR canonical LR(1) when the given grammar is non-LR(1) coupled with a specification for Yacc resolving conflicts. We also detail an original minimal LR(1) algorithm, IELR(1) (Inadequacy Bison Elimination LR(1)), which we have implemented as an extension of GNU Bison and which does not exhibit this deficiency. -
Chapter 4 Syntax Analysis
Chapter 4 Syntax Analysis By Varun Arora Outline Role of parser Context free grammars Top down parsing Bottom up parsing Parser generators By Varun Arora The role of parser token Source Lexical Parse tree Rest of Intermediate Parser program Analyzer Front End representation getNext Token Symbol table By Varun Arora Uses of grammars E -> E + T | T T -> T * F | F F -> (E) | id E -> TE’ E’ -> +TE’ | Ɛ T -> FT’ T’ -> *FT’ | Ɛ F -> (E) | id By Varun Arora Error handling Common programming errors Lexical errors Syntactic errors Semantic errors Lexical errors Error handler goals Report the presence of errors clearly and accurately Recover from each error quickly enough to detect subsequent errors Add minimal overhead to the processing of correct progrms By Varun Arora Error-recover strategies Panic mode recovery Discard input symbol one at a time until one of designated set of synchronization tokens is found Phrase level recovery Replacing a prefix of remaining input by some string that allows the parser to continue Error productions Augment the grammar with productions that generate the erroneous constructs Global correction Choosing minimal sequence of changes to obtain a globally least-cost correction By Varun Arora Context free grammars Terminals Nonterminals expression -> expression + term Start symbol expression -> expression – term productions expression -> term term -> term * factor term -> term / factor term -> factor factor -> (expression) factor -> id By Varun Arora Derivations Productions are treated as -
Scheme of Teaching and Examination for BE
Scheme of Teaching and Examination for B.E (CS&E) SEMESTER: III Sl. Subject Course Title Teaching Credits Contact Marks Exam No. Code Department Hours Duration in hrs L T P TOTAL CIE SEE Total 1 MA310 Mathematics III Mathematics 4 0 0 4 4 50 50 100 03 2 CS310 Digital System CSE 4 0 1 5 6 50 50 100 03 Design 3 CS320 Discrete CSE 4 0 0 4 4 50 50 100 03 Mathematical Structures and Combinatorics 4 CS330 Computer CSE 4 0 0 4 4 50 50 100 03 Organization 5 CS340 Data Structures CSE 4 0 1 5 6 50 50 100 03 6 CS350 Object Oriented CSE 4 0 1 5 6 50 50 100 03 Programming with C++ Total Total 27 Total Marks 600 Credits Scheme of Teaching and Examination for B.E (CS&E) SEMESTER: IV Sl. Subject Course Title Teaching Credits Contact Marks Exam No. Code Department Hours Duration in hrs L T P TOTAL CIE SEE Total 1 MA410 Probability, Mathematics 4 0 0 4 4 50 50 100 03 Statistics and Queuing 2 CS410 Operating CSE 4 0 1 5 6 50 50 100 03 Systems 3 CS420 Design and CSE 4 0 1 5 6 50 50 100 03 Analysis of Algorithms 4 CS430 Theory of CSE 4 0 0 4 4 50 50 100 03 Computation 5 CS440 Microprocessors CSE 4 0 1 5 6 50 50 100 03 6 CS450 Data CSE 4 0 0 4 4 50 50 100 03 Communication Total Total 27 Total Marks 600 Credits Scheme of Teaching and Examination for B.E (CS&E) SEMESTER: V Sl. -
CWI Scanprofile/PDF/300
Centrum voor Wiskunde en lnformatica Centre for Mathematics and Computer Science J. Heering, P. Klint, J.G. Rekers Incremental generation of parsers , Computer Science/Department of Software Technology Report CS-R8822 May Biblk>tlleek Centrum ypor Wisl~unde en lnformatk:a Am~tel>dam The Centre for Mathematics and Computer Science is a research institute of the Stichting Mathematisch Centrum, which was founded on February 11, 1946, as a nonprofit institution aim ing at the promotion of mathematics, computer science, and their applications. It is sponsored by the Dutch Government through the Netherlands Organization for the Advancement of Pure Research (Z.W.0.). q\ ' Copyright (t:: Stichting Mathematisch Centrum, Amsterdam 1 Incremental Generation of Parsers J. Heering Department of Software Technology, Centre for Mathematics and Computer Science P.O. Box 4079, 1009 AS Amsterdam, The Netherlands P. Klint Department of Software Technology, Centre for Mathematics and Computer Science P.O. Box 4079, 1009 AS Amsterdam, The Netherlands and Programming Research Group, University of Amsterdam P.O. BOX 41882, 1009 DB Amsterdam, The Netherlands J. Rekers Department of Software Technology, Centre for Mathematics and Computer Science P.O. Box 4079, 1009 AB Amsterdam, The Netherlands A parser checks whether a text is a sentence in a language. Therefore, the parser is provided with the grammar of the language, and it usually generates a structure (parse tree) that represents the text according to that grammar. Most present-day parsers are not directly driven by the grammar but by a 'parse table', which is generated by a parse table generator. A table based parser wolks more efficiently than a grammar based parser does, and provided that the parser is used often enough, the cost of gen erating the parse table is outweighed by the gain in parsing efficiency. -
B.E Computer Science and Engineering
CURRICULUM B.E. – Computer Science and Engineering Regulations 2019 VISION MISSION “To become a center of excellence • To produce technocrats in the in Computer Science and industry and academia by Engineering and Research to create educating computer concepts and global leaders with holistic growth techniques. and ethical values for the industry • To facilitate the students to and academics.” trigger more creativity by applying modern tools and technologies in the field of computer science and engineering. • To inculcate the spirit of ethical values contributing to the welfare of the society. Department of Computer Science and Engineering Department of CSE, Francis Xavier Engineering College | Regulation 2019 2 Department of CSE, Francis Xavier Engineering College | Regulation 2019 5 B.E.-COMPUTER SCIENCE AND ENGINEERING (REGULATIONS 2019) CHOICE BASED CREDIT SYSTEM SUMMARY OF CREDIT DISTRIBUTION Range Of CREDITS PER SEMESTER Total S. TOTAL CREDITS CATEGORY Credits No CREDIT IN % I II III IV V VI VII VIII Min Max 1 HSS 3 2 3 8 4.5% 9 11 2 BS 12 4 4 4 24 14.5% 21 21 3 ES 8 11 3 22 13.9% 23 26 4 PC 13 17 10 11 8 59 35.75% 59 59 5 PE 6 6 6 6 24 14.5% 24 27 6 OE 3 3 3 3 12 7.3% 12 15 7 EEC 2 2 1 10 15 9.1% 12 15 TOTAL 23 18 20 23 22 22 21 16 165 100% - - BS - Basic Sciences ES - Engineering Sciences HSS - Humanities and Social Sciences PC - Professional Core PE - Professional Elective OE - Open Elective EEC - Employability Enhancement Course Department of CSE, Francis Xavier Engineering College | Regulation 2019 6 B.E.- COMPUTER SCIENCE AND ENGINEERING (REGULATIONS 2019) CHOICE BASED CREDIT SYSTEM I – VIII SEMESTERS CURRICULUM AND SYLLABI FIRST SEMESTER Code No. -
Compiler Design
CCOOMMPPIILLEERR DDEESSIIGGNN -- PPAARRSSEERR http://www.tutorialspoint.com/compiler_design/compiler_design_parser.htm Copyright © tutorialspoint.com In the previous chapter, we understood the basic concepts involved in parsing. In this chapter, we will learn the various types of parser construction methods available. Parsing can be defined as top-down or bottom-up based on how the parse-tree is constructed. Top-Down Parsing We have learnt in the last chapter that the top-down parsing technique parses the input, and starts constructing a parse tree from the root node gradually moving down to the leaf nodes. The types of top-down parsing are depicted below: Recursive Descent Parsing Recursive descent is a top-down parsing technique that constructs the parse tree from the top and the input is read from left to right. It uses procedures for every terminal and non-terminal entity. This parsing technique recursively parses the input to make a parse tree, which may or may not require back-tracking. But the grammar associated with it ifnotleftfactored cannot avoid back- tracking. A form of recursive-descent parsing that does not require any back-tracking is known as predictive parsing. This parsing technique is regarded recursive as it uses context-free grammar which is recursive in nature. Back-tracking Top- down parsers start from the root node startsymbol and match the input string against the production rules to replace them ifmatched. To understand this, take the following example of CFG: S → rXd | rZd X → oa | ea Z → ai For an input string: read, a top-down parser, will behave like this: It will start with S from the production rules and will match its yield to the left-most letter of the input, i.e. -
Compiler Construction
UNIVERSITY OF CAMBRIDGE Compiler Construction An 18-lecture course Alan Mycroft Computer Laboratory, Cambridge University http://www.cl.cam.ac.uk/users/am/ Lent Term 2007 Compiler Construction 1 Lent Term 2007 Course Plan UNIVERSITY OF CAMBRIDGE Part A : intro/background Part B : a simple compiler for a simple language Part C : implementing harder things Compiler Construction 2 Lent Term 2007 A compiler UNIVERSITY OF CAMBRIDGE A compiler is a program which translates the source form of a program into a semantically equivalent target form. • Traditionally this was machine code or relocatable binary form, but nowadays the target form may be a virtual machine (e.g. JVM) or indeed another language such as C. • Can appear a very hard program to write. • How can one even start? • It’s just like juggling too many balls (picking instructions while determining whether this ‘+’ is part of ‘++’ or whether its right operand is just a variable or an expression ...). Compiler Construction 3 Lent Term 2007 How to even start? UNIVERSITY OF CAMBRIDGE “When finding it hard to juggle 4 balls at once, juggle them each in turn instead ...” character -token -parse -intermediate -target stream stream tree code code syn trans cg lex A multi-pass compiler does one ‘simple’ thing at once and passes its output to the next stage. These are pretty standard stages, and indeed language and (e.g. JVM) system design has co-evolved around them. Compiler Construction 4 Lent Term 2007 Compilers can be big and hard to understand UNIVERSITY OF CAMBRIDGE Compilers can be very large. In 2004 the Gnu Compiler Collection (GCC) was noted to “[consist] of about 2.1 million lines of code and has been in development for over 15 years”. -
Unit-5 Parsers
UNIT-5 PARSERS LR Parsers: • The most powerful shift-reduce parsing (yet efficient) is: • LR parsing is attractive because: – LR parsing is most general non-backtracking shift-reduce parsing, yet it is still efficient. – The class of grammars that can be parsed using LR methods is a proper superset of the class of grammars that can be parsed with predictive parsers. LL(1)-Grammars ⊂ LR(1)-Grammars – An LR-parser can detect a syntactic error as soon as it is possible to do so a left-to-right scan of the input. – covers wide range of grammars. • SLR – simple LR parser • LR – most general LR parser • LALR – intermediate LR parser (look-head LR parser) • SLR, LR and LALR work same (they used the same algorithm), only their parsing tables are different. LR Parsing Algorithm: A Configuration of LR Parsing Algorithm: A configuration of a LR parsing is: • Sm and ai decides the parser action by consulting the parsing action table. (Initial Stack contains just So ) • A configuration of a LR parsing represents the right sentential form: X1 ... Xm ai ai+1 ... an $ Actions of A LR-Parser: 1. shift s -- shifts the next input symbol and the state s onto the stack ( So X1 S1 ... Xm Sm, ai ai+1 ... an $ ) è ( So X1 S1 ..Xm Sm ai s, ai+1 ...an $ ) 2. reduce Aβ→ (or rn where n is a production number) – pop 2|β| (=r) items from the stack; – then push A and s where s=goto[sm-r,A] ( So X1 S1 ... Xm Sm, ai ai+1 .. -
Bottom-Up Parsing Swarnendu Biswas
CS 335: Bottom-up Parsing Swarnendu Biswas Semester 2019-2020-II CSE, IIT Kanpur Content influenced by many excellent references, see References slide for acknowledgements. Rightmost Derivation of 푎푏푏푐푑푒 푆 → 푎퐴퐵푒 Input string: 푎푏푏푐푑푒 퐴 → 퐴푏푐 | 푏 푆 → 푎퐴퐵푒 퐵 → 푑 → 푎퐴푑푒 → 푎퐴푏푐푑푒 → 푎푏푏푐푑푒 푆 푟푚 푆 푟푚 푆 푟푚 푆 푟푚 푆 푎 퐴 퐵 푒 푎 퐴 퐵 푒 푎 퐴 퐵 푒 푎 퐴 퐵 푒 푑 퐴 푏 푐 푑 퐴 푏 푐 푑 푏 CS 335 Swarnendu Biswas Bottom-up Parsing Constructs the parse tree starting from the leaves and working up toward the root 푆 → 푎퐴퐵푒 Input string: 푎푏푏푐푑푒 퐴 → 퐴푏푐 | 푏 푆 → 푎퐴퐵푒 푎푏푏푐푑푒 퐵 → 푑 → 푎퐴푑푒 → 푎퐴푏푐푑푒 → 푎퐴푏푐푑푒 → 푎퐴푑푒 → 푎푏푏푐푑푒 → 푎퐴퐵푒 → 푆 reverse of rightmost CS 335 Swarnendu Biswas derivation Bottom-up Parsing 푆 → 푎퐴퐵푒 Input string: 푎푏푏푐푑푒 퐴 → 퐴푏푐 | 푏 푎푏푏푐푑푒 퐵 → 푑 → 푎퐴푏푐푑푒 → 푎퐴푑푒 → 푎퐴퐵푒 → 푆 푎푏푏푐푑푒⇒ 푎 퐴 푏 푐 푑 푒 ⇒ 푎 퐴 푑 푒 ⇒ 푎 퐴 퐵 푒 ⇒ 푆 푏 퐴 푏 푐 퐴 푏 푐 푑 푎 퐴 퐵 푒 푏 푏 퐴 푏 푐 푑 푏 CS 335 Swarnendu Biswas Reduction • Bottom-up parsing reduces a string 푤 to the start symbol 푆 • At each reduction step, a chosen substring that is the rhs (or body) of a production is replaced by the lhs (or head) nonterminal Derivation 푆 훾0 훾1 훾2 … 훾푛−1 훾푛 = 푤 푟푚 푟푚 푟푚 푟푚 푟푚 푟푚 Bottom-up Parser CS 335 Swarnendu Biswas Handle • Handle is a substring that matches the body of a production • Reducing the handle is one step in the reverse of the rightmost derivation Right Sentential Form Handle Reducing Production 퐸 → 퐸 + 푇 | 푇 ∗ 퐹 → 푇 → 푇 ∗ 퐹 | 퐹 id1 id2 id1 id 퐹 → 퐸 | id 퐹 ∗ id2 퐹 푇 → 퐹 푇 ∗ id2 id2 퐹 → id 푇 ∗ 퐹 푇 ∗ 퐹 푇 → 푇 ∗ 퐹 푇 푇 퐸 → 푇 CS 335 Swarnendu Biswas Handle Although 푇 is the body of the production 퐸 → 푇, -
2017-18 MCA – I Integrated.Pdf
North Maharashtra University, Jalgaon North Maharashtra University, Jalgaon (NAAC Accredited ‘A’ Grade University) FACULTY OF SCIENCE INTEGRATED MCA (I-MCA) Syllabus (With effect from July 2017-18) First Year I-MCA – ( Sem I & II ) w.e.f. AY 2017-18 Paper Semester-I Paper Semester-II Mathematical Foundations in CA-1.1 CA-2.1 Discrete Mathematics Computer Science CA-1.2 Computer & Internet Fundamentals CA-2.2 System Programming CA-1.3 Computer Organization & Architecture CA-2.3 Object Oriented Analysis & Design CA-1.4 Programming using C CA-2.4 Programming using C++ CA-1.5 Essentials of Web Designing CA-2.5 Data Structure – I CA-1.6 Lab on Programming using C CA-2.6 Lab on Programming using C++ CA-1.7 Lab on Essentials of Web Designing CA-2.7 Lab on Data Structure - I Second Year I-MCA – ( Sem III & IV ) Paper Semester-III Paper Semester-IV CA-3.1 Computer Networks CA-4.1 Basics of Accounting CA-3.2 Operating System – I CA-4.2 Operating System - II CA-3.3 System Analysis and Design CA-4.3 Network Security CA-3.4 Programming using C#.NET CA-4.4 Java Programming CA-3.5 Data Structure – II CA-4.5 Database Management System CA-3.6 Lab on Programming using C#.NET CA-4.6 Lab on Java Programming CA-3.7 Lab on Data Structure - II CA-4.7 Lab on DBMS Third Year I – MCA – ( Sem V & VI ) Paper Semester-V Paper Semester-VI CA-5.1 Theoretical Computer Science CA-6.1 Automata Theory and Computability CA-5.2 Software Engineering-I CA-6.2 Software Engineering-II CA-5.3 Computer Graphics CA-6.3 Advanced Data Base Management System CA-5.4 Advanced Java CA-6.4 -
Compiler Construction
Compiler construction PDF generated using the open source mwlib toolkit. See http://code.pediapress.com/ for more information. PDF generated at: Sat, 10 Dec 2011 02:23:02 UTC Contents Articles Introduction 1 Compiler construction 1 Compiler 2 Interpreter 10 History of compiler writing 14 Lexical analysis 22 Lexical analysis 22 Regular expression 26 Regular expression examples 37 Finite-state machine 41 Preprocessor 51 Syntactic analysis 54 Parsing 54 Lookahead 58 Symbol table 61 Abstract syntax 63 Abstract syntax tree 64 Context-free grammar 65 Terminal and nonterminal symbols 77 Left recursion 79 Backus–Naur Form 83 Extended Backus–Naur Form 86 TBNF 91 Top-down parsing 91 Recursive descent parser 93 Tail recursive parser 98 Parsing expression grammar 100 LL parser 106 LR parser 114 Parsing table 123 Simple LR parser 125 Canonical LR parser 127 GLR parser 129 LALR parser 130 Recursive ascent parser 133 Parser combinator 140 Bottom-up parsing 143 Chomsky normal form 148 CYK algorithm 150 Simple precedence grammar 153 Simple precedence parser 154 Operator-precedence grammar 156 Operator-precedence parser 159 Shunting-yard algorithm 163 Chart parser 173 Earley parser 174 The lexer hack 178 Scannerless parsing 180 Semantic analysis 182 Attribute grammar 182 L-attributed grammar 184 LR-attributed grammar 185 S-attributed grammar 185 ECLR-attributed grammar 186 Intermediate language 186 Control flow graph 188 Basic block 190 Call graph 192 Data-flow analysis 195 Use-define chain 201 Live variable analysis 204 Reaching definition 206 Three address -
Pondicherry Engineering College Puducherry – 605 014
1 PONDICHERRY ENGINEERING COLLEGE PUDUCHERRY – 605 014 Bachelor of Technology B.Tech., INFORMATION TECHNOLOGY Regulations, Curriculum & Syllabus Effective from the academic year 2013-2014 of PONDICHERRY UNIVERSITY PUDUCHERRY – 605 014. 2 PONDICHERRY UNIVERSITY BACHELOR OF TECHNOLOGY PROGRAMMES (EIGHT SEMESTERS) REGULATIONS 1. Conditions for Admission: (a ) Candidates for admission to the first semester of the 8 semester B.Tech Degree programme should be required to have passed : The Higher Secondary Examination of the (10+2) curriculum (Academic Stream) prescribed by the Government of Tamil Nadu or any other examination equivalent there to with minimum of 45% marks (40% marks for OBC and SC/ST candidates) in aggregate of subjects – Mathematics, Physics and any one of the following optional subjects: Chemistry / Biotechnology/ Computer Science / Biology (Botany & Zoology) or an Examination of any University or Authority recognized by the Executive Council of the Pondicherry University as equivalent thereto. (b) For Lateral entry in to third semester of the eight semester B.Tech programme : The minimum qualification for admission is a pass in three year diploma or four year sandwich diploma course in engineering / technology with a minimum of 45% marks ( 40% marks for OBC and SC/ST candidates) in aggregate in the subjects covered from 3 rd to final semester or a pass in any B.Sc. course with mathematics as one of the subjects of study in XII standard with a minimum of 45% marks ( 40% marks for OBC and a mere pass for SC/ST candidates) in aggregate in main and ancillary subjects excluding language subjects. The list of diploma programs approved for admission for each of the degree programs is given in Annexure A .