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The document discusses bottom-up parsing techniques, including LR(0), SLR(1), and LR(1) parsing. It describes the construction of finite automata from grammar rules to represent the states and transitions of these parsing approaches. The key aspects covered are: 1) The definitions and algorithms for SLR(1) and LR(1) parsing, which extend LR(0) parsing by using lookahead tokens to resolve parsing conflicts. 2) Sources of parsing conflicts like shift-reduce conflicts and reduce-reduce conflicts that can occur for some grammars with these techniques. 3) The limits of SLR(1) parsing power and how some grammars require the more general LR(
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Ch4b
The document discusses shift-reduce parsing and LR parsing methods. It covers:
- Shift-reduce parsing corresponds to a rightmost derivation using shift and reduce actions. Handlers are substrings that match production right-hand sides.
- Shift-reduce conflicts are resolved by favoring shift, while reduce-reduce conflicts favor the first production.
- An LR parser uses a DFA to determine the shift and reduce actions based on the state and next input symbol. This resolves conflicts.
- The states of the DFA correspond to LR items with the dot in different positions. Transitions are determined by goto and closure operations.
Lecture11 syntax analysis_7
LR parsers are shift-reduce parsers that can parse a wide range of grammars. LR parsing is attractive because it is the most general non-backtracking shift-reduce parsing method while still being efficient. The class of grammars that can be parsed by LR methods is a superset of those that can be parsed by LL(1) parsers. LR parsers can detect syntactic errors as soon as possible during a left-to-right scan of the input. The LR parsing algorithm uses action and goto tables constructed from LR(0) items to perform shift and reduce operations.
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This is about a topic of compiler design, LR and SLR parsing algorithm and LR grammar, Canonical collection and Item, Conflict in LR parsing shift reduce. Classification of Bottom up parsing.
Compiler Design LR parsing SLR ,LALR CLR
The document introduces LR parsing and simple LR parsing. It discusses LR(k) parsing which scans input from left to right and constructs a rightmost derivation in reverse. It then focuses on simple LR parsing and describes parser states and items. Examples of parsing expressions are provided to illustrate closure computation. The document also discusses more powerful LR parsers that use lookahead and the canonical LR and LALR methods. It provides examples of LR(1) item sets and describes constructing an LALR parsing table.
Ll(1) Parser in Compilers
This slide is prepared By these following Students of Dept. of CSE JnU, Dhaka. Thanks To: Nusrat Jahan, Arifatun Nesa, Fatema Akter, Maleka Khatun, Tamanna Tabassum.
Parsing LL(1), SLR, LR(1)
This document discusses parsing and different parsing techniques. It defines parsing as the process of verifying that tokens generated by a lexical analyzer follow the syntactic rules of a language. Parsers can be top-down or bottom-up. Top-down parsers build the parse tree from the root to leaves by following leftmost derivations, while bottom-up parsers start from the leaves and work upwards. The document also discusses LL(1), SLR, and LR(1) parsing techniques, including how to construct parsing tables and handle conflicts. LR(1) parsers are more restrictive than SLR(1) parsers in where they allow reduce operations.
Presentation mam saima kanwal
LR parsing techniques include SLR, Canonical LR, and LALR(1) parsing. SLR parsing uses LR(0) items and the FOLLOW set to resolve conflicts, but may introduce conflicts. Canonical LR parsing uses LR(1) items which include lookahead information to avoid conflicts found in SLR parsing. LALR(1) parsing reduces the number of states compared to Canonical LR by merging states with the same core items. LALR(1) can introduce reduce/reduce conflicts, while SLR and Canonical LR can have shift/reduce conflicts.
LL(1) parsing
In System programming , we have 2 parsing techniques to parse a string . From those techniques one technique is LL(1) parsing.
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Ch4b
The document discusses shift-reduce parsing and LR parsing methods. It covers:
- Shift-reduce parsing corresponds to a rightmost derivation using shift and reduce actions. Handlers are substrings that match production right-hand sides.
- Shift-reduce conflicts are resolved by favoring shift, while reduce-reduce conflicts favor the first production.
- An LR parser uses a DFA to determine the shift and reduce actions based on the state and next input symbol. This resolves conflicts.
- The states of the DFA correspond to LR items with the dot in different positions. Transitions are determined by goto and closure operations.
Lecture11 syntax analysis_7
LR parsers are shift-reduce parsers that can parse a wide range of grammars. LR parsing is attractive because it is the most general non-backtracking shift-reduce parsing method while still being efficient. The class of grammars that can be parsed by LR methods is a superset of those that can be parsed by LL(1) parsers. LR parsers can detect syntactic errors as soon as possible during a left-to-right scan of the input. The LR parsing algorithm uses action and goto tables constructed from LR(0) items to perform shift and reduce operations.
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This is about a topic of compiler design, LR and SLR parsing algorithm and LR grammar, Canonical collection and Item, Conflict in LR parsing shift reduce. Classification of Bottom up parsing.
Compiler Design LR parsing SLR ,LALR CLR
The document introduces LR parsing and simple LR parsing. It discusses LR(k) parsing which scans input from left to right and constructs a rightmost derivation in reverse. It then focuses on simple LR parsing and describes parser states and items. Examples of parsing expressions are provided to illustrate closure computation. The document also discusses more powerful LR parsers that use lookahead and the canonical LR and LALR methods. It provides examples of LR(1) item sets and describes constructing an LALR parsing table.
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Presentation mam saima kanwal
LR parsing techniques include SLR, Canonical LR, and LALR(1) parsing. SLR parsing uses LR(0) items and the FOLLOW set to resolve conflicts, but may introduce conflicts. Canonical LR parsing uses LR(1) items which include lookahead information to avoid conflicts found in SLR parsing. LALR(1) parsing reduces the number of states compared to Canonical LR by merging states with the same core items. LALR(1) can introduce reduce/reduce conflicts, while SLR and Canonical LR can have shift/reduce conflicts.
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This document discusses bottom-up parsing and LR parsing. Bottom-up parsing starts from the leaf nodes of a parse tree and works upward to the root node by applying grammar rules in reverse. LR parsing is a type of bottom-up parsing that uses shift-reduce parsing with two steps: shifting input symbols onto a stack, and reducing grammar rules on the stack. The document describes LR parsers, types of LR parsers like SLR(1) and LALR(1), and the LR parsing algorithm. It also compares bottom-up LR parsing to top-down LL parsing.
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Recursive descent parsing is a top-down parsing technique that attempts to construct a parse tree for an input starting from the root node and creating child nodes in a preorder traversal. It involves backtracking if the parser reaches a point in the input where it cannot determine the next step. Predictive parsers avoid backtracking by eliminating left recursion and left factoring from the grammar upfront. Transition diagrams can be created for predictive parsers, with states connected by edges labeled with grammar symbols to show the parsing steps. An example transition diagram is provided for a grammar including productions for E, E', T, T', and F.
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Predictive parsing is a technique for parsing context-free grammars where the parser predicts the next production to use based on looking ahead at upcoming tokens. It works for LL(1) grammars, where the production can be determined uniquely from the next token. The parsing process involves building a parsing table from the grammar's first and follow sets and using that table to guide the parser's actions. When an error is detected, various recovery techniques like panic mode or inserting error productions can be used to try to continue parsing.
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Bottom-up parsing builds parse trees starting from the leaves (terminals) and working towards the root (start symbol). It can handle a more general class of grammars than top-down parsing. Shift-reduce parsing splits the input string into two parts separated by a special character, with terminals on the right. It uses two actions: shift moves a terminal from right to left, and reduce applies a production to remove symbols from the left. Conflicts can occur when it is possible to shift or reduce, or to reduce in different ways. Handles mark points where reduction also allows deriving the start symbol.
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The document discusses LR(1) parsing and the construction of LR(1) parsing tables. It describes how LR(1) items include a lookahead terminal symbol to avoid invalid reductions. The closure and goto functions are used to construct the canonical collection of LR(1) item sets. From this, the action and goto tables of the LR(1) parser are derived. The document also discusses how LALR parsing tables are constructed by merging states that have the same core (first component) of LR(1) items, which can introduce reduce/reduce conflicts but not shift/reduce conflicts.
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A bottom-up parser creates a parse tree starting from the leaves and working towards the root by finding the right-most derivation of the input string in reverse order. Bottom-up parsing involves two main actions: shift, which pushes the next input symbol onto a stack; and reduce, which pops symbols from the stack according to grammar rules. LR parsers are a type of bottom-up parser that can handle a wide range of grammars through the use of parsing tables constructed from the grammar to determine the shift and reduce actions.
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Top-down parsing begins with the root symbol and uses productions to construct the parse tree from the top down. It repeats selecting a production for the current non-terminal and adding symbols to the parse tree until the input is fully parsed or a mismatch requires backtracking. Recursive descent parsing is a type of top-down parsing where each non-terminal's productions are represented by recursive functions attempting productions left-to-right with backtracking. Left recursion in grammars prevents recursive descent parsing from terminating, so left-recursive productions must be eliminated before using this approach.
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This document discusses bottom-up parsing and LR(0) parsing. It describes viable prefixes, LR(0) items, and how they are used to build an automaton that recognizes viable prefixes of a grammar. This automaton undergoes subset construction to determinize it, resulting in a DFA. SLR parsing improves on LR(0) by adding heuristics to resolve shift-reduce conflicts. An example SLR parsing of the string "int * int$" is provided to illustrate the algorithm.
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This document discusses LR parsers and the process of constructing SLR parsing tables. It begins by defining LR(0) items and the closure operation, which is used to find all LR(0) items that are reachable from a given set. The goto operation finds the set of LR(0) items for a given non-terminal. The canonical LR(0) collection is constructed by applying closure and goto until no new items can be added. This collection forms the basis for the SLR parsing tables, which are constructed by determining shift and reduce actions based on the LR(0) items in each state. The document provides examples of shift-reduce and reduce-reduce conflicts that can occur in SLR parsing tables.
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This document discusses different types of parsers used in parsing strings based on production rules of a grammar. It describes:
1) Top-down parsers which start from the start symbol and derive strings using a parse tree from top to bottom, and bottom-up parsers which start from the string and build the parse tree from bottom to top.
2) Types of top-down parsers including recursive descent parsing which uses recursive procedures and may involve backtracking, and types of bottom-up parsers including SLR(1), LR(1), and LALR(1) parsers.
3) Examples of top-down and bottom-up parsing of strings based on sample grammars to illustrate the parsing process.
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The document discusses the role of the parser in compiler design. It explains that the parser takes a stream of tokens from the lexical analyzer and checks if the source program satisfies the rules of the context-free grammar. If so, it creates a parse tree representing the syntactic structure. Parsers are categorized as top-down or bottom-up based on the direction they build the parse tree. The document also covers context-free grammars, derivations, parse trees, ambiguity, and techniques for eliminating left-recursion from grammars.
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This document provides an outline and overview of bottom-up parsing and LR(0) parsing. It discusses bottom-up parsing using an explicit stack, shift-reduce actions, and the need for arbitrary stack lookahead. It then describes LR(0) items as productions with a distinguished position, and how a NFA and DFA of items is constructed for a grammar. It explains how LR(0) parsing uses the DFA of items to perform bottom-up parsing with shift and reduce actions. Finally, it notes that an LR(0) parsing table can be constructed from the DFA of items to determine parsing actions.
Nonrecursive predictive parsing
A non-recursive predictive parser uses an explicit stack instead of recursion to mimic leftmost derivations in a grammar. The parser has an input buffer, stack, parsing table, and output stream. It uses the parsing table to shift and reduce based on the top of the stack and next input symbol to produce a leftmost derivation if the input is in the language, otherwise reporting an error. The moves of the parser on a sample input correspond to the sentential forms in the leftmost derivation of that input string.
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The document discusses the role of parsers in compilers. It explains that parsers check syntax and report errors, perform semantic checks like type checking, and produce an intermediate representation of the source code. Parsers use syntax-directed translation with methods like abstract syntax trees. The document also covers topics like error handling strategies, the viable prefix property, left recursion elimination, and constructing LL(1) parsing tables.
Topdown parsing
Recursive descent parsing is a top-down parsing technique that attempts to construct a parse tree for an input starting from the root node and creating child nodes in a preorder traversal. It involves backtracking if the parser reaches a point in the input where it cannot determine the next step. Predictive parsers avoid backtracking by eliminating left recursion and left factoring from the grammar upfront. Transition diagrams can be created for predictive parsers, with states connected by edges labeled with grammar symbols to show the parsing steps. An example transition diagram is provided for a grammar including productions for E, E', T, T', and F.
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Predictive parsing is a technique for parsing context-free grammars where the parser predicts the next production to use based on looking ahead at upcoming tokens. It works for LL(1) grammars, where the production can be determined uniquely from the next token. The parsing process involves building a parsing table from the grammar's first and follow sets and using that table to guide the parser's actions. When an error is detected, various recovery techniques like panic mode or inserting error productions can be used to try to continue parsing.
Lecture9 syntax analysis_5
Bottom-up parsing builds parse trees starting from the leaves (terminals) and working towards the root (start symbol). It can handle a more general class of grammars than top-down parsing. Shift-reduce parsing splits the input string into two parts separated by a special character, with terminals on the right. It uses two actions: shift moves a terminal from right to left, and reduce applies a production to remove symbols from the left. Conflicts can occur when it is possible to shift or reduce, or to reduce in different ways. Handles mark points where reduction also allows deriving the start symbol.
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This document provides implementation details for writing a compiler in C using Lex and Yacc. It is meant to accompany a textbook on compiler design that describes compiler implementation using Java. This document contains equivalent information for building a compiler in C, with chapters that correspond to the textbook chapters. It describes how to implement lexical analysis with Lex, parsing with Yacc, semantic analysis, code generation, and more. The document is not intended to be self-contained and should be used along with the textbook.
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The document discusses syntax analysis and creating parsers using Yacc/Bison. It provides examples of writing grammars and semantic actions for simple arithmetic expressions. Key points covered include:
- Yacc/Bison generate LALR(1) parsers from grammar specifications
- A Yacc specification contains declarations, translation rules (productions with semantic actions), and auxiliary C functions
- Productions define the grammar, semantic actions associate values with terminals/nonterminals
- Attributes refer to semantic values, precedence levels resolve ambiguity
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The document provides an overview of yacc (Yet Another Compiler Compiler), which is a tool that parses a stream of tokens according to a user-specified grammar. It describes the structure of a yacc file, which includes definitions, rules, and code sections. It also discusses how yacc interacts with lex to generate tokens, and how values can be returned from lex to yacc using the yylval variable. An example calculator program is provided to demonstrate how yacc can be used to parse arithmetic expressions by defining grammar rules and associating actions with parsing steps.
Lexyacc
This document provides an introduction to using Lex and Yacc to build compilers. Lex is used to generate a lexical analyzer from input patterns, which converts strings to tokens. Yacc generates a parser from a grammar, which analyzes tokens to build a syntax tree. The document describes building a calculator as an example, which can be converted to a compiler by changing the code generation. It also discusses additional Lex and Yacc features like strings, reserved words, debugging, recursion, and attributes.
Yacc lex
This document provides an introduction to Yacc and Lex, which are parser and lexer generator tools. Yacc is used to describe the grammar of a language and automatically generate a parser. The user provides grammar rules in BNF format. Lex is used to generate a lexer (also called a tokenizer) that recognizes tokens in the input based on regular expressions. It returns tokens to the parser. The document gives examples of Yacc and Lex grammar files and explains how they are compiled and used to build a parser for an input language.
Yacc (yet another compiler compiler)
This seminar presentation provides an overview of YACC (Yet Another Compiler Compiler). It discusses what compilers do, the structure of compilers including scanners, parsers, semantic routines, code generators and optimizers. It then reviews parsers and how YACC works by taking a grammar specification and generating C code for a parser. YACC declarations and commands are also summarized.
Yacc
Yacc is a general tool for describing the input to computer programs. It generates a LALR parser that analyzes tokens from Lex and creates a syntax tree based on the grammar rules specified. Yacc was originally developed in the 1970s and generates C code for the syntax analyzer from a grammar similar to BNF. It has been used to build compilers for languages like C, Pascal, and APL as well as for other programs like document retrieval systems.
Lex
Lex is a program generator designed for lexical processing of character input streams. It works by translating a table of regular expressions and corresponding program fragments provided by the user into a program. This program then reads an input stream, partitions it into strings matching the given expressions, and executes the associated program fragments in order. Flex is a fast lexical analyzer generator that is an alternative to Lex. It generates scanners that recognize lexical patterns in text based on pairs of regular expressions and C code provided by the user.
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LEX and YACC are software development tools used for lexical analysis and parsing. LEX is a lexical analyzer generator that accepts an input specification defining lexical units and associated semantic actions. It generates a translator containing tables of lexical units and tokens. YACC is a parser generator that accepts a grammar specification and actions for the language being compiled. It produces a bottom-up parser that uses shift-reduce parsing. These tools allow programmers to specify the syntax of a language and generate code to analyze programs in that language.
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A parser breaks down input into smaller elements for translation into another language. It takes a sequence of tokens as input and builds a parse tree or abstract syntax tree. In the compiler model, the parser verifies that the token string can be generated by the grammar and returns any syntax errors. There are two main types of parsers: top-down parsers start at the root and fill in the tree, while bottom-up parsers start at the leaves and work upwards. Syntax directed definitions associate attributes with grammar symbols and specify attribute values with semantic rules for each production.
Parsing example
This document provides an overview of LALR parsing. It begins by motivating the need for LALR parsing by explaining limitations of LR(1) parsing which can result in many states. It then explains that LALR parsing attempts to reduce the number of states by merging similar LR(1) states. This can result in the same number of states as SLR(1) parsing but retains some LR(1) lookahead abilities. The document provides examples to illustrate LALR state merging and how it can avoid some SLR conflicts. It also notes that state merging can potentially introduce new reduce-reduce conflicts. The document describes two approaches to constructing LALR parsing tables and defines what constitutes a LALR
Compiler design lab programs
The document appears to be a student assignment submission containing programs written by Mukesh Kumar (student ID 1110751908) for their 7th semester Computer Science branch. It includes 7 programs addressing various parsing and lexical analysis tasks, along with the student's name, institution and course details. Each program is presented with its source code, output and description of what it is intended to do.
LALR Parser Presentation ppt
This is a presentation on LALR parser. This presentation was created by 6th sem CSE student.
LALR parser is basically used to creating the LR parsing table. LALR parser is used because it is more powerful than SLR and the tables generated by LALR consumes less memory and disk space than CLR parser.
Compiler unit 2&3
A parser is a program component that breaks input data into smaller elements according to the rules of a formal grammar. It builds a parse tree representing the syntactic structure of the input based on these grammar rules. There are two main types of parsers: top-down parsers start at the root of the parse tree and work downward, while bottom-up parsers start at the leaves and work upward. Parser generators use attributes like First and Follow to build parsing tables for predictive parsers like LL(1) parsers, which parse input from left to right based on a single lookahead token.
Operating system kernal
The kernel is the central and most important component of an operating system. It manages hardware resources like the CPU, memory and I/O devices, and allows processes and applications to access these resources through system calls and inter-process communication mechanisms. The kernel translates requests from software into instructions for hardware components. It provides protection from faults and allows for synchronization and communication between processes running concurrently. Kernels can have different designs like monolithic, micro, or hybrid depending on how hardware management is separated from other operating system services.
Bottom up parser
Bottom-up parsing builds a derivation by working from the input sentence back toward the start symbol S. It is preferred in practice and also called LR parsing, where L means tokens are read left to right and R means it constructs a rightmost derivation. The two main types are operator-precedence parsing and LR parsing, which covers a wide range of grammars through techniques like SLR, LALR, and LR parsing. LR parsing reduces a string to the start symbol by inverting productions through identifying handles and replacing them.
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Compiler Components and their Generators - LR Parsing
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sameermlr0parser-200701133032.pptx
1) LR(0) parsers use left-to-right, rightmost derivations with 0 tokens of lookahead to parse context-free grammars deterministically.
2) States of the LR(0) automaton are sets of items where an item represents a point in a production that has been recognized.
3) States are built by closure - if a state includes an item expecting a non-terminal B, it will include all items that can begin with B.
10-SLR parser practice problems-02-06-2023.pptx
LR parsing is an efficient bottom-up parsing technique that can parse large classes of context-free grammars. It works by scanning the input from left to right, constructing the rightmost derivation in reverse using k lookahead symbols. The key steps are:
1. Constructing LR(0) items and closure sets
2. Building the LR parsing table from the LR(0) items
3. Using the table to parse input strings based on lookahead symbols
The main differences between LR parsing techniques are the way lookahead is handled, with CLR using exact lookahead, SLR using limited lookahead, and LALR approximating lookahead.
LR-Parsing.ppt
LR parsing is a powerful shift-reduce parsing technique that is both efficient and handles a wide range of grammars. LR parsers work by maintaining a stack and scanning input from left to right. They determine the next action to take by consulting parsing tables generated from the grammar. LR parsing avoids backtracking and can detect syntactic errors as early as possible. The most general form of LR parsing is LR(k) which uses k tokens of lookahead, while practical parsers often use LR(1) or variants like LALR(1) which have smaller and more efficiently constructed tables.
LR(0) PARSER
1) LR(0) parsers use left-to-right, rightmost derivations with 0-token lookahead to parse context-free grammars deterministically.
2) The states of the LR(0) automaton are sets of parsing items that indicate the progress of recognizing productions.
3) Parsing tables are constructed from the automaton to specify the shift and reduce actions and state transitions based on the next input symbol.
02. chapter 3 lexical analysis
The document discusses lexical analysis in compiler design. It covers the role of the lexical analyzer, tokenization, and representation of tokens using finite automata. Regular expressions are used to formally specify patterns for tokens. A lexical analyzer generator converts these specifications into a finite state machine (FSM) implementation to recognize tokens in the input stream. The FSM is typically a deterministic finite automaton (DFA) for efficiency, even though a nondeterministic finite automaton (NFA) may require fewer states.
lalr. fo engineering student those who to
This document discusses LALR parsing and how LALR parsers are constructed. It covers the following key points:
- LALR parsing uses a deterministic finite automaton called a prefix automaton to determine when reductions need to be made during shift-reduce parsing.
- Items are rules with a dot added somewhere in the right-hand side, representing the part of the rule that has been read. Itemsets are sets of items.
- The prefix automaton is constructed from a grammar by starting with an initial itemset and repeatedly taking the closure and transition of itemsets until no new states are generated.
- The parse algorithm uses the prefix automaton to make shift and reduce decisions based on
Ch3
The document discusses lexical analysis and lexical analyzer generators. It provides background on why lexical analysis is a separate phase in compiler design and how it simplifies parsing. It also describes how a lexical analyzer interacts with a parser and some key attributes of tokens like lexemes and patterns. Finally, it explains how regular expressions are used to specify patterns for tokens and how tools like Lex and Flex can be used to generate lexical analyzers from regular expression definitions.
COMPILER DESIGN- Syntax Analysis
This document provides an overview of syntax analysis in compiler design. It discusses context-free grammars, top-down parsing including recursive descent and LL(1) parsing, and bottom-up parsing including LR parsing. It describes the key concepts of context-free grammars, ambiguous and unambiguous grammars. It explains top-down parsing as constructing a parse tree from the root node down and bottom-up parsing as building the tree from the leaf nodes up. It discusses the closure and goto operations used in LR parsing and describes the differences between LR(0), SLR, CLR, and LALR parsing techniques.
BOTTOM UP PARSING GROUP 3.pptx
A bottom-up parser constructs a parse tree from the bottom (leaves) to the top (root) by reducing the input string to the start symbol of the grammar. The document provides examples of LR(0) and LR(1) grammars and shows the steps to construct the parsing tables and parse input strings for these grammars using bottom-up parsing. It also includes some sample questions about bottom-up parsing and parser types.
lr parsers bottom up parsers slr parser.pptx
This document discusses LR parsers and LR parsing. It begins by describing the different types of LR parsers, including SLR, CLR, and LALR parsers. It then explains the basic process of LR parsing using parsing tables with action and goto functions. Several key aspects of LR parsing are summarized, such as LR(0) items, augmented grammars, shift-reduce actions, and constructing SLR parsing tables for a sample grammar.
Syntactic analysis in NLP
This is the presentation on Syntactic Analysis in NLP.It includes topics like Introduction to parsing, Basic parsing strategies, Top-down parsing, Bottom-up
parsing, Dynamic programming – CYK parser, Issues in basic parsing methods, Earley algorithm, Parsing
using Probabilistic Context Free Grammars.
Ch3.ppt
The document discusses lexical analysis and lexical analyzer generators. It begins by explaining that lexical analysis separates a program into tokens, which simplifies parser design and implementation. It then covers topics like token attributes, patterns and lexemes, regular expressions for specifying patterns, converting regular expressions to nondeterministic finite automata (NFAs) and then deterministic finite automata (DFAs). The document provides examples and algorithms for these conversions to generate a lexical analyzer from token specifications.
Compiler Design File
The document discusses compiler theory and provides code examples. It covers:
1. Lex theory - how regular expressions are used to specify patterns for tokenization and how these are implemented as finite state automata.
2. Yacc theory - how context-free grammars are specified in BNF and parsed using shift-reduce parsing. Issues like shift-reduce conflicts and reduce-reduce conflicts are explained.
3. Code examples of stack implementations using arrays and linked lists, and a program to check if a string is a keyword.
Loops and functions in r
This document discusses basic loops and functions in R programming. It covers control statements like loops and if/else, arithmetic and boolean operators, default argument values, and returning values from functions. It also describes R programming structures, recursion, and provides an example of implementing quicksort recursively and constructing a binary search tree. The key topics are loops, control flow, functions, recursion, and examples of sorting and binary trees.
Ch3.ppt
The document discusses lexical analysis and lexical analyzer generators. It covers topics such as:
- Lexical analysis separates the compiler into distinct phases for simpler design and more efficient implementation.
- Lexical analyzers are specified using regular expressions which are translated into nondeterministic finite automata (NFA) and then deterministic finite automata (DFA) for efficient scanning.
- Tools like Lex and Flex can automatically generate a lexical analyzer in C from a specification file defining tokens with regular expressions and actions.
Ch3.ppt
The document discusses lexical analysis and lexical analyzer generators. It begins by explaining that lexical analysis separates a program into tokens, which simplifies parser design and implementation. It then covers how the lexical analyzer interacts with the parser by returning tokens. The rest of the document details how to specify patterns for tokens using regular expressions and regular definitions, and how lexical analyzer generators like Lex and Flex translate those specifications into a scanner that recognizes tokens.
Ch5b.pdf
The document discusses various methods for implementing syntax-directed translation schemes (SDTs). It covers:
1) Any SDT can be implemented by building a parse tree and performing actions in a depth-first, left-to-right order.
2) Some SDTs can be implemented during parsing without building a parse tree.
3) Postfix SDTs have all actions at the end of production bodies and can be implemented during an LR parse.
4) SDTs with embedded actions inside productions require inserting marker nonterminals to implement as a postfix SDT.
hsu-Chapter 6 Laplace transform.pdf
The document provides an introduction to the Laplace transform and its applications in engineering analysis. It discusses key topics including:
- The history and development of the Laplace transform by mathematician Pierre-Simon Laplace.
- How the Laplace transform is used to transform a variable like time or position into a parameter to solve differential equations.
- Examples of using Laplace transform properties like linearity, shifting, and change of scale to calculate transforms of functions.
- How Laplace transforms can be used to solve ordinary and partial differential equations that model physical systems.
- Tables of common Laplace transforms to help with transforming functions.
Preparatory_questions_final_exam_DigitalElectronics1 (1).pdf
The Quine-McCluskey method is used to minimize Boolean functions expressed in sum-of-products form. It works by generating prime implicants from the minterms and then eliminating variables to find an essential prime implicant. The method uses the Boolean rule A + A' = 1 repeatedly. It can handle incompletely specified functions using don't care conditions. The main steps are: 1) generate prime implicants, 2) construct a prime implicant table, 3) reduce the table by removing essential prime implicants and applying row and column dominance, 4) solve the reduced table.
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Preparatory_questions_final_exam_DigitalElectronics1 (1).pdf
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Chapter 2 2 1 1
This document summarizes the process of converting a regular expression to a deterministic finite automaton (DFA) via a nondeterministic finite automaton (NFA). It first explains Thompson's construction for building an NFA from a regular expression using epsilon transitions. It then describes the subset construction algorithm for eliminating epsilon transitions and nondeterminism to produce an equivalent DFA. The algorithm works by considering sets of NFA states as DFA states and computing the epsilon closures and resulting state sets after each input symbol.
Chapter 2 2 1 2
The document discusses the subset construction method for simulating nondeterministic finite automata (NFAs).
It explains that the subset construction avoids constructing the entire deterministic finite automaton (DFA) and instead constructs states on-the-fly based on the next input character. As an example, it shows applying the subset construction to an NFA with the input string "a".
The document also covers minimizing the number of states in a DFA by starting with sets of accepting and non-accepting states and iteratively splitting sets based on whether states can be distinguished by their transitions. It provides examples of applying this process to specific regular expressions.
Chapter Three(2)
The document summarizes key concepts about context-free grammars and parsing from the book "Compiler Construction: Principles and Practice" by Kenneth C. Louden. It covers notations like EBNF and syntax diagrams for representing grammars, properties of context-free languages, and provides grammar rules and diagrams for a sample TINY language as an example.
Chapter Three(1)
This document discusses context-free grammars and parsing. It defines context-free grammars and how they are used to specify the syntactic structure of programming languages. Key points include:
- Context-free grammars use recursive rules and regular expressions to define a language's syntax.
- Parsing involves using a context-free grammar to derive a syntax tree from a sequence of tokens.
- Derivations show how strings of tokens are generated from a grammar's start symbol through replacements.
- The language defined by a grammar consists of all strings that can be derived from the start symbol.
Chapter Seven(2)
The document discusses runtime environments and memory management techniques for programming languages. It covers stack-based vs dynamic environments, parameter passing mechanisms like pass by value and reference, and garbage collection algorithms. Dynamic memory allocation uses a heap structure with malloc and free functions. Object-oriented languages require special runtime support for objects, inheritance etc. Fully dynamic environments are needed for functional languages that allow nested functions.
Chapter Eight(3)
The document describes code generation for two commercial compilers:
1) The Borland C 3.0 compiler for the 80X86 generates assembly code using static simulation and frame pointers for function calls and local variable access.
2) The Sun 2.0 compiler for SPARCstations uses register-based calling conventions and generates efficient SPARC assembly code.
Both compilers handle code generation for arithmetic expressions, arrays, structures, pointers, control flow, and function calls.
Chapter One
This document provides an overview of compiler construction principles and practices. It introduces the basic components of a compiler, including scanning, parsing, semantic analysis, code generation, and optimization phases. It also discusses related tools like assemblers, linkers, and debuggers. The document outlines the translation process from source code to target code and describes major data structures used in compilers like symbol tables and syntax trees.
Chapter Seven(1)
The document discusses different runtime environments for programming languages:
(1) Fully static environments where all data remains fixed in memory like FORTRAN77. No dynamic allocation.
(2) Stack-based environments used by languages allowing recursion and dynamic allocation like C/C++. Activation records are allocated on a runtime stack.
(3) Dynamic environments like LISP where data is allocated on a heap.
It covers key aspects of runtime environments like memory organization, calling conventions, parameter passing, and handling local variables and procedures. Different languages require different solutions for variable-length data, nested declarations, non-local references, and procedure parameters.
Chapter Two(1)
The document discusses scanning (lexical analysis) in compiler construction. It covers the scanning process, regular expressions, and finite automata. The scanning process identifies tokens from source code by categorizing characters as reserved words, special symbols, or other tokens. Regular expressions are used to represent patterns of character strings and define the language of tokens. Finite automata are mathematical models for describing scanning algorithms using states, transitions, and acceptance.
Chapter Eight(1)
The document discusses code generation techniques in compiler construction. It describes generating executable code from source code by using intermediate representations like three-address code and P-code. It covers generating code from syntax trees, implementing intermediate codes using data structures, and translating between different intermediate representations and target machine code.
Chapter Eight(2)
The document discusses code generation techniques in compiler construction. It covers generating code for control structures like if-statements and while-loops, as well as addressing techniques for data structures like arrays. Intermediate representations like three-address code and P-code are used. Label generation and back-patching allow jumps to not-yet defined code locations.
Chapter 1 1
The document describes the structure and process of a compiler. It discusses the major phases of a compiler including scanning, parsing, semantic analysis, code generation and optimization. It also summarizes the key data structures used in a compiler like the symbol table and syntax tree. The document uses the TINY programming language and its compiler for the TM machine as an example to illustrate the compiler construction process.
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Chapter Five(2)
- 1. COMPILER CONSTRUCTION Principles and Practice Kenneth C. Louden
- 2. 5. Bottom-Up Parsing PART TWO
- 5. DFA and the LR(0) Parsing of The grammar: A -> ( A ) | a shift shift shift reduce A->a shift reduce A->(A) shift reduce A->(A) accept ( (a) )$ ( a) )$ a )$ ) )$ ) )$ )$ )$ $ $ $ 0 $ 0 ( 3 $ 0 ( 3 ( 3 $ 0 ( 3 ( 3 a 2 $ 0 ( 3 ( 3 A 4 $ 0 ( 3 ( 3 A 4 ) 5 $ 0 ( 3 A 4 $ 0 ( 3 A 4 ) 5 $ 0 A 1 Parsing stack input Action 1 2 3 4 5 6 7 8 9
- 9. 5.3.1 The SLR(1) Parsing Algorithm
- 16. The parsing process for n+n+n shift 2 reduce E ->n shift3 shift4 reduce E -> E+n shift3 shift4 reduce E -> E+n accept n + n + n $ +n + n $ +n + n $ n + n $ + n $ + n $ n $ $ $ $0 $0 n 2 $0E1 $0E1+3 $0E1+3n4 $0E1 $0E1+3 $0E1+3n4 $0E1 Action Input Parsing stack 1 2 3 4 5 6 7 8 9
- 20. 5.3.2 Disambiguating Rules for Parsing Conflicts
- 24. 5.3.3 Limits of SLR(1) Parsing Power
- 29. 5.4 General LR(1) and LALR(1) Parsing
- 30. 5.4.1 Finite Automata of LR(1) Items
- 35. 5.4.2 The LR(1) Parsing Algorithm
- 41. The DFA of LR(1) item
- 51. The DFA of LR(1)
- 52. The DFA of LALR(1) Note: An LALR( l ) parser will perform the reduction A->a , before declaring error; A general LR( l) parser will declare error immediately after a shift of the token a.
- 54. Computing the DFA of LALR( l) items directly from the DFA of LR(0) items
- 57. 5.5 Yacc: LALR(1) PARSING GENERATOR
- 81. 5.5.3 Parsing Conflicts and Disambiguating Rule 5.5.4 Tracing the Execution of a Yacc Parsing 5.5.5 Arbitrary Value Types in Yacc 5.5.6 Embedded Action in Yacc Back
- 82. 5.6 GENERATION OF A TINY PARSER USING Yacc
- 83. 5.7 ERROR RECOVERY IN BOTTOM-UP PARSERS
- 84. 5.7.1 Detecting Errors in Bottom-up Parsing
- 89. 5.7.2 Panic Mode Error Recovery
- 97. 5.7.3 Error Recovery in Yacc 5.7.4 Error Recovery in TINY
- 98. End of Part Two THANKS