Context-Aware Scanning and Determinism-Preserving Grammar Composition, in Theory and Practice
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Modern Compiler Implementation in Java. Second Edition
Team-Fly Modern Compiler Implementation in Java, Second Edition by Andrew W. ISBN:052182060x Appel and Jens Palsberg Cambridge University Press © 2002 (501 pages) This textbook describes all phases of a compiler, and thorough coverage of current techniques in code generation and register allocation, and the compilation of functional and object-oriented languages. Table of Contents Modern Compiler Implementation in Java, Second Edition Preface Part One - Fundamentals of Compilation Ch apt - Introduction er 1 Ch apt - Lexical Analysis er 2 Ch apt - Parsing er 3 Ch apt - Abstract Syntax er 4 Ch apt - Semantic Analysis er 5 Ch apt - Activation Records er 6 Ch apt - Translation to Intermediate Code er 7 Ch apt - Basic Blocks and Traces er 8 Ch apt - Instruction Selection er 9 Ch apt - Liveness Analysis er 10 Ch apt - Register Allocation er 11 Ch apt - Putting It All Together er 12 Part Two - Advanced Topics Ch apt - Garbage Collection er 13 Ch apt - Object-Oriented Languages er 14 Ch apt - Functional Programming Languages er 15 Ch apt - Polymorphic Types er 16 Ch apt - Dataflow Analysis er 17 Ch apt - Loop Optimizations er 18 Ch apt - Static Single-Assignment Form er 19 Ch apt - Pipelining and Scheduling er 20 Ch apt - The Memory Hierarchy er 21 Ap pe ndi - MiniJava Language Reference Manual x A Bibliography Index List of Figures List of Tables List of Examples Team-Fly Team-Fly Back Cover This textbook describes all phases of a compiler: lexical analysis, parsing, abstract syntax, semantic actions, intermediate representations, instruction selection via tree matching, dataflow analysis, graph-coloring register allocation, and runtime systems. -
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. -
A Declarative Extension of Parsing Expression Grammars for Recognizing Most Programming Languages
Journal of Information Processing Vol.24 No.2 256–264 (Mar. 2016) [DOI: 10.2197/ipsjjip.24.256] Regular Paper A Declarative Extension of Parsing Expression Grammars for Recognizing Most Programming Languages Tetsuro Matsumura1,†1 Kimio Kuramitsu1,a) Received: May 18, 2015, Accepted: November 5, 2015 Abstract: Parsing Expression Grammars are a popular foundation for describing syntax. Unfortunately, several syn- tax of programming languages are still hard to recognize with pure PEGs. Notorious cases appears: typedef-defined names in C/C++, indentation-based code layout in Python, and HERE document in many scripting languages. To recognize such PEG-hard syntax, we have addressed a declarative extension to PEGs. The “declarative” extension means no programmed semantic actions, which are traditionally used to realize the extended parsing behavior. Nez is our extended PEG language, including symbol tables and conditional parsing. This paper demonstrates that the use of Nez Extensions can realize many practical programming languages, such as C, C#, Ruby, and Python, which involve PEG-hard syntax. Keywords: parsing expression grammars, semantic actions, context-sensitive syntax, and case studies on program- ming languages invalidate the declarative property of PEGs, thus resulting in re- 1. Introduction duced reusability of grammars. As a result, many developers need Parsing Expression Grammars [5], or PEGs, are a popu- to redevelop grammars for their software engineering tools. lar foundation for describing programming language syntax [6], In this paper, we propose a declarative extension of PEGs for [15]. Indeed, the formalism of PEGs has many desirable prop- recognizing context-sensitive syntax. The “declarative” exten- erties, including deterministic behaviors, unlimited look-aheads, sion means no arbitrary semantic actions that are written in a gen- and integrated lexical analysis known as scanner-less parsing. -
Maximal-Munch” Tokenization in Linear Time Tom Reps [TOPLAS 1998]
Fall 2016-2017 Compiler Principles Lecture 1: Lexical Analysis Roman Manevich Ben-Gurion University of the Negev Agenda • Understand role of lexical analysis in a compiler • Regular languages reminder • Lexical analysis algorithms • Scanner generation 2 Javascript example • Can you some identify basic units in this code? var currOption = 0; // Choose content to display in lower pane. function choose ( id ) { var menu = ["about-me", "publications", "teaching", "software", "activities"]; for (i = 0; i < menu.length; i++) { currOption = menu[i]; var elt = document.getElementById(currOption); if (currOption == id && elt.style.display == "none") { elt.style.display = "block"; } else { elt.style.display = "none"; } } } 3 Javascript example • Can you some identify basic units in this code? keyword ? ? ? ? ? var currOption = 0; // Choose content to display in lower pane. ? function choose ( id ) { var menu = ["about-me", "publications", "teaching", "software", "activities"]; ? for (i = 0; i < menu.length; i++) { currOption = menu[i]; var elt = document.getElementById(currOption); if (currOption == id && elt.style.display == "none") { elt.style.display = "block"; } else { elt.style.display = "none"; } } } 4 Javascript example • Can you some identify basic units in this code? keyword identifier operator numeric literal punctuation comment var currOption = 0; // Choose content to display in lower pane. string literal function choose ( id ) { var menu = ["about-me", "publications", "teaching", "software", "activities"]; whitespace for (i = 0; i < menu.length; i++) { currOption = menu[i]; var elt = document.getElementById(currOption); if (currOption == id && elt.style.display == "none") { elt.style.display = "block"; } else { elt.style.display = "none"; } } } 5 Role of lexical analysis • First part of compiler front-end Lexical Syntax AST Symbol Inter. Code High-level Analysis Analysis Table Rep. -
The Design & Implementation of an Abstract Semantic Graph For
Clemson University TigerPrints All Dissertations Dissertations 12-2011 The esiD gn & Implementation of an Abstract Semantic Graph for Statement-Level Dynamic Analysis of C++ Applications Edward Duffy Clemson University, [email protected] Follow this and additional works at: https://tigerprints.clemson.edu/all_dissertations Part of the Computer Sciences Commons Recommended Citation Duffy, Edward, "The eD sign & Implementation of an Abstract Semantic Graph for Statement-Level Dynamic Analysis of C++ Applications" (2011). All Dissertations. 832. https://tigerprints.clemson.edu/all_dissertations/832 This Dissertation is brought to you for free and open access by the Dissertations at TigerPrints. It has been accepted for inclusion in All Dissertations by an authorized administrator of TigerPrints. For more information, please contact [email protected]. THE DESIGN &IMPLEMENTATION OF AN ABSTRACT SEMANTIC GRAPH FOR STATEMENT-LEVEL DYNAMIC ANALYSIS OF C++ APPLICATIONS A Dissertation Presented to the Graduate School of Clemson University In Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy Computer Science by Edward B. Duffy December 2011 Accepted by: Dr. Brian A. Malloy, Committee Chair Dr. James B. von Oehsen Dr. Jason P. Hallstrom Dr. Pradip K. Srimani In this thesis, we describe our system, Hylian, for statement-level analysis, both static and dynamic, of a C++ application. We begin by extending the GNU gcc parser to generate parse trees in XML format for each of the compilation units in a C++ application. We then provide verification that the generated parse trees are structurally equivalent to the code in the original C++ application. We use the generated parse trees, together with an augmented version of the gcc test suite, to recover a grammar for the C++ dialect that we parse. -
Efficient Recursive Parsing
Purdue University Purdue e-Pubs Department of Computer Science Technical Reports Department of Computer Science 1976 Efficient Recursive Parsing Christoph M. Hoffmann Purdue University, [email protected] Report Number: 77-215 Hoffmann, Christoph M., "Efficient Recursive Parsing" (1976). Department of Computer Science Technical Reports. Paper 155. https://docs.lib.purdue.edu/cstech/155 This document has been made available through Purdue e-Pubs, a service of the Purdue University Libraries. Please contact [email protected] for additional information. EFFICIENT RECURSIVE PARSING Christoph M. Hoffmann Computer Science Department Purdue University West Lafayette, Indiana 47907 CSD-TR 215 December 1976 Efficient Recursive Parsing Christoph M. Hoffmann Computer Science Department Purdue University- Abstract Algorithms are developed which construct from a given LL(l) grammar a recursive descent parser with as much, recursion resolved by iteration as is possible without introducing auxiliary memory. Unlike other proposed methods in the literature designed to arrive at parsers of this kind, the algorithms do not require extensions of the notational formalism nor alter the grammar in any way. The algorithms constructing the parsers operate in 0(k«s) steps, where s is the size of the grammar, i.e. the sum of the lengths of all productions, and k is a grammar - dependent constant. A speedup of the algorithm is possible which improves the bound to 0(s) for all LL(l) grammars, and constructs smaller parsers with some auxiliary memory in form of parameters -
Parsing Techniques
Dick Grune, Ceriel J.H. Jacobs Parsing Techniques 2nd edition — Monograph — September 27, 2007 Springer Berlin Heidelberg NewYork Hong Kong London Milan Paris Tokyo Contents Preface to the Second Edition : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : v Preface to the First Edition : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : xi 1 Introduction : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 1 1.1 Parsing as a Craft. 2 1.2 The Approach Used . 2 1.3 Outline of the Contents . 3 1.4 The Annotated Bibliography . 4 2 Grammars as a Generating Device : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 5 2.1 Languages as Infinite Sets . 5 2.1.1 Language . 5 2.1.2 Grammars . 7 2.1.3 Problems with Infinite Sets . 8 2.1.4 Describing a Language through a Finite Recipe . 12 2.2 Formal Grammars . 14 2.2.1 The Formalism of Formal Grammars . 14 2.2.2 Generating Sentences from a Formal Grammar . 15 2.2.3 The Expressive Power of Formal Grammars . 17 2.3 The Chomsky Hierarchy of Grammars and Languages . 19 2.3.1 Type 1 Grammars . 19 2.3.2 Type 2 Grammars . 23 2.3.3 Type 3 Grammars . 30 2.3.4 Type 4 Grammars . 33 2.3.5 Conclusion . 34 2.4 Actually Generating Sentences from a Grammar. 34 2.4.1 The Phrase-Structure Case . 34 2.4.2 The CS Case . 36 2.4.3 The CF Case . 36 2.5 To Shrink or Not To Shrink . 38 xvi Contents 2.6 Grammars that Produce the Empty Language . 41 2.7 The Limitations of CF and FS Grammars . 42 2.7.1 The uvwxy Theorem . 42 2.7.2 The uvw Theorem . -
GLR* - an Efficient Noise-Skipping Parsing Algorithm for Context Free· Grammars
GLR* - An Efficient Noise-skipping Parsing Algorithm For Context Free· Grammars Alon Lavie and Masaru Tomita School of Computer Scienc�, Carnegie Mellon University 5000 Forbes- Avenue, Pittsburgh, PA 15213 email: lavie©cs. emu . edu Abstract This paper describes GLR*, a parser that can parse any input sentence by ignoring unrec ognizable parts of the sentence. In case the standard parsing procedure fails to parse an input sentence, the parser nondeterministically skips some word(s) in the sentence, and returns the parse with fewest skipped words. Therefore, the parser will return some parse(s) with any input sentence, unless no part of the sentence can be recognized at all. The problem can be defined in the following way: Given a context-free grammar G and a sentence S, find and parse S' - the largest subset of words of S, such that S' E L(G). The algorithm described in this paper is a modificationof the Generalized LR (Tomita) parsing algorithm [Tomita, 1986]. The parser accommodates the skipping of words by allowing shift operations to be performed from inactive state nodes of the Graph Structured Stack. A heuristic similar to beam search makes the algorithm computationally tractable. There have been several other approaches to the problem of robust parsing, most of which are special purpose algorithms [Carbonell and Hayes, 1984), [Ward, 1991] and others. Because our approach is a modification to a standard context-free parsing algorithm, all the techniques and grammars developed for the standard parser can be applied as they are. Also, in case the input sentence is by itself grammatical, our parser behaves exactly as the standard GLR parser. -
A Simple, Possibly Correct LR Parser for C11 Jacques-Henri Jourdan, François Pottier
A Simple, Possibly Correct LR Parser for C11 Jacques-Henri Jourdan, François Pottier To cite this version: Jacques-Henri Jourdan, François Pottier. A Simple, Possibly Correct LR Parser for C11. ACM Transactions on Programming Languages and Systems (TOPLAS), ACM, 2017, 39 (4), pp.1 - 36. 10.1145/3064848. hal-01633123 HAL Id: hal-01633123 https://hal.archives-ouvertes.fr/hal-01633123 Submitted on 11 Nov 2017 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. 14 A simple, possibly correct LR parser for C11 Jacques-Henri Jourdan, Inria Paris, MPI-SWS François Pottier, Inria Paris The syntax of the C programming language is described in the C11 standard by an ambiguous context-free grammar, accompanied with English prose that describes the concept of “scope” and indicates how certain ambiguous code fragments should be interpreted. Based on these elements, the problem of implementing a compliant C11 parser is not entirely trivial. We review the main sources of difficulty and describe a relatively simple solution to the problem. Our solution employs the well-known technique of combining an LALR(1) parser with a “lexical feedback” mechanism. It draws on folklore knowledge and adds several original as- pects, including: a twist on lexical feedback that allows a smooth interaction with lookahead; a simplified and powerful treatment of scopes; and a few amendments in the grammar. -
Advanced Parsing Techniques
Advanced Parsing Techniques Announcements ● Written Set 1 graded. ● Hard copies available for pickup right now. ● Electronic submissions: feedback returned later today. Where We Are Where We Are Parsing so Far ● We've explored five deterministic parsing algorithms: ● LL(1) ● LR(0) ● SLR(1) ● LALR(1) ● LR(1) ● These algorithms all have their limitations. ● Can we parse arbitrary context-free grammars? Why Parse Arbitrary Grammars? ● They're easier to write. ● Can leave operator precedence and associativity out of the grammar. ● No worries about shift/reduce or FIRST/FOLLOW conflicts. ● If ambiguous, can filter out invalid trees at the end. ● Generate candidate parse trees, then eliminate them when not needed. ● Practical concern for some languages. ● We need to have C and C++ compilers! Questions for Today ● How do you go about parsing ambiguous grammars efficiently? ● How do you produce all possible parse trees? ● What else can we do with a general parser? The Earley Parser Motivation: The Limits of LR ● LR parsers use shift and reduce actions to reduce the input to the start symbol. ● LR parsers cannot deterministically handle shift/reduce or reduce/reduce conflicts. ● However, they can nondeterministically handle these conflicts by guessing which option to choose. ● What if we try all options and see if any of them work? The Earley Parser ● Maintain a collection of Earley items, which are LR(0) items annotated with a start position. ● The item A → α·ω @n means we are working on recognizing A → αω, have seen α, and the start position of the item was the nth token. ● Using techniques similar to LR parsing, try to scan across the input creating these items. -
CS 444: Compiler Construction
CS 444: Compiler Construction Gabriel Wong Contents Introduction 3 Front-end Analysis . .3 Formal Languages . .3 Lexical Analysis / Scanning 3 Regular Expressions . .3 Regex to DFA . .4 Definition of NFA and DFA . .4 Computing -closure . .4 NFA to DFA Conversion . .5 Scanning . .6 Constructing Scanning DFA . .6 Parsing 7 Context-Free Grammar . .7 Top-down / Bottom-up Parsing . .8 LL(1) Parsing . .9 Augmented Grammar . 10 LL(1) Algorithm . 10 LR(0) Parsing . 11 LR(1) Parsing . 15 SLR(1) Parser . 15 Comparison Between LR Parsers . 16 LR(1) NFA . 16 LALR(1) Parser . 17 Abstract Syntax Tree . 19 Semantic Analysis 19 Implementing Environments . 20 Namespaces . 20 Java Name Resolution . 21 1. Create class environment . 21 2. Resolve type names . 21 3. Check class hierachy . 21 4. Disambiguate ambiguous names . 23 5. Resolve expressions (variables, fields) . 23 6. Type checking . 24 7. Resolve methods and instance fields . 27 Static Analysis 28 Java Reachability Analysis (JLS 14.20) . 28 Java Definite Assignment Analysis (JLS 16) . 29 1 CONTENTS CONTENTS Live Variable Analysis . 30 Code Generation 31 IA-32 Assembly . 32 Assembler Directives . 32 Strategy for Code Generation . 33 Data Layout . 33 Constants . 34 Local Variables . 34 Method Calls . 35 Object Layout . 36 Vtables . 37 Dispatching Interface Methods . 37 Subtype Testing . 38 Arrays................................................. 38 2 Regular Expressions LEXICAL ANALYSIS / SCANNING Notes taken from lectures by Ondřej Lhoták in Winter 2016. Introduction A compiler translates from a source language (eg. Java) to a target machine language (eg. x86). Scanning, parsing (A1) and context sensitive analysis (A234) are part of the compiler front end. -
Verifiable Parse Table Composition for Deterministic Parsing*
Verifiable Parse Table Composition for Deterministic Parsing? August Schwerdfeger and Eric Van Wyk Department of Computer Science and Engineering University of Minnesota, Minneapolis, MN {schwerdf,evw}@cs.umn.edu Abstract. One obstacle to the implementation of modular extensions to programming languages lies in the problem of parsing extended lan- guages. Specifically, the parse tables at the heart of traditional LALR(1) parsers are so monolithic and tightly constructed that, in the general case, it is impossible to extend them without regenerating them from the source grammar. Current extensible frameworks employ a variety of solutions, ranging from a full regeneration to using pluggable binary mod- ules for each different extension. But recompilation is time-consuming, while the pluggable modules in many cases cannot support the addition of more than one extension, or use backtracking or non-deterministic parsing techniques. We present here a middle-ground approach that allows an extension, if it meets certain restrictions, to be compiled into a parse table fragment. The host language parse table and fragments from multiple extensions can then always be efficiently composed to produce a conflict-free parse table for the extended language. This allows for the distribution of de- terministic parsers for extensible languages in a pre-compiled format, eliminating the need for the “source code” grammar to be distributed. In practice, we have found these restrictions to be reasonable and admit many useful language extensions. 1 Introduction In parsing programming languages, the usual practice is to generate a single parser for the language to be parsed. A well known and often-used approach is LR parsing [1] which relies on a process, sometimes referred to as grammar compilation, to generate a monolithic parse table representing the grammar being parsed.