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.
The document discusses different types of parsing including:
1) Top-down parsing which starts at the root node and builds the parse tree recursively, requiring backtracking for ambiguous grammars.
2) Bottom-up parsing which starts at the leaf nodes and applies grammar rules in reverse to reach the start symbol using shift-reduce parsing.
3) LL(1) and LR parsing which are predictive parsing techniques using parsing tables constructed from FIRST and FOLLOW sets to avoid backtracking.
This document describes shift-reduce parsing. Shift-reduce parsing is a bottom-up parsing approach where the input string is collapsed by reducing parts of the string according to production rules until the start symbol is reached, as opposed to top-down parsing which expands symbols. It uses two main data structures: an input buffer and a stack. Initially, it puts the input string in the buffer and a start symbol on the stack. It then performs the basic operations of shift, which moves symbols from the buffer to the stack, and reduce, which replaces symbols on the stack according to production rules. It halts when the start symbol remains on the stack and the buffer is empty, indicating successful parsing.
DBScan stands for Density-Based Spatial Clustering of Applications with Noise.
DBScan Concepts
DBScan Parameters
DBScan Connectivity and Reachability
DBScan Algorithm , Flowchart and Example
Advantages and Disadvantages of DBScan
DBScan Complexity
Outliers related question and its solution.
This document discusses user administration concepts and mechanisms in UNIX/Linux operating systems. It covers topics like users, groups, permissions, and how to manage users and groups. Specific commands to manage files, directories and permissions are also described, such as chown, chgrp, and chmod. The structure of standard UNIX/Linux directories like /bin, /dev, /etc, and others are outlined as well.
Network slicing in 5G allows a single UE to connect to multiple network slices simultaneously. Each slice is identified by a Specific Network Slice Selection Assistance Information (S-NSSAI). The 5G core uses the S-NSSAI to select the appropriate functions like the Session Management Function (SMF) for each slice. This enables isolation of services and network functions on a per-slice basis. The Access and Mobility Management Function (AMF) is common across all slices, but the SMF and User Plane Function (UPF) can differ per slice. This facilitates customized network slices for different use cases and isolation of traffic and functions.
The role of the parser and Error recovery strategies ppt in compiler designSadia Akter
This document summarizes error recovery strategies used by parsers. It discusses the role of parsers in validating syntax based on grammars and producing parse trees. It then describes several error recovery strategies like panic-mode recovery, phrase-level recovery using local corrections, adding error productions to the grammar, and global correction aiming to make minimal changes to parse invalid inputs.
This document discusses syntax-directed translation, which refers to a method of compiler implementation where the source language translation is completely driven by the parser. The parsing process and parse trees are used to direct semantic analysis and translation of the source program. Attributes and semantic rules are associated with the grammar symbols and productions to control semantic analysis and translation. There are two main representations of semantic rules: syntax-directed definitions and syntax-directed translation schemes. Syntax-directed translation schemes embed program fragments called semantic actions within production bodies and are more efficient than syntax-directed definitions as they indicate the order of evaluation of semantic actions. Attribute grammars can be used to represent syntax-directed translations.
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.
The document discusses lexical analysis in compilers. It describes how the lexical analyzer reads source code characters and divides them into tokens. Regular expressions are used to specify patterns for token recognition. The lexical analyzer generates a finite state automaton to recognize these patterns. Lexical analysis is the first phase of compilation that separates the input into tokens for the parser.
Hashing is the process of converting a given key into another value. A hash function is used to generate the new value according to a mathematical algorithm. The result of a hash function is known as a hash value or simply, a hash.
Hashing is a technique used to uniquely identify objects by assigning each object a key, such as a student ID or book ID number. A hash function converts large keys into smaller keys that are used as indices in a hash table, allowing for fast lookup of objects in O(1) time. Collisions, where two different keys hash to the same index, are resolved using techniques like separate chaining or linear probing. Common applications of hashing include databases, caches, and object representation in programming languages.
The document discusses the FIRST and FOLLOW sets used in compiler construction for predictive parsing. FIRST(X) is the set of terminals that can begin strings derived from X. FOLLOW(A) is the set of terminals that can immediately follow A. Rules are provided to compute the FIRST and FOLLOW sets for a grammar. Examples demonstrate applying the rules to sample grammars and presenting the resulting FIRST and FOLLOW sets.
The document provides an overview of compilers by discussing:
1. Compilers translate source code into executable target code by going through several phases including lexical analysis, syntax analysis, semantic analysis, code optimization, and code generation.
2. An interpreter directly executes source code statement by statement while a compiler produces target code as translation. Compiled code generally runs faster than interpreted code.
3. The phases of a compiler include a front end that analyzes the source code and produces intermediate code, and a back end that optimizes and generates the target code.
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.
This document describes the steps to construct a LALR parser from a context-free grammar:
1. Create an augmented grammar by adding a new start symbol and productions.
2. Generate kernel items by introducing dots in productions and adding second components. Then take closures of the items.
3. Compute the goto function to fill the parsing table.
4. Construct the CLR parsing table from the items and gotos.
5. Shrink the CLR parser by merging equivalent states to produce the more efficient LALR parsing table with fewer states.
The document discusses symbol tables, which are data structures used by compilers to track semantic information about identifiers, variables, functions, classes, etc. It provides details on:
- How various compiler phases like lexical analysis, syntax analysis, semantic analysis, code generation utilize and update the symbol table.
- Common data structures used to implement symbol tables like linear lists, hash tables and how they work.
- The information typically stored for different symbols like name, type, scope, memory location etc.
- Organization of symbol tables for block-structured vs non-block structured languages, including using multiple nested tables vs a single global table.
This document contains a presentation on Breadth-First Search (BFS) given to students. The presentation includes:
- An introduction to BFS and its inventor Konrad Zuse.
- Definitions of key terms like graph, tree, vertex, level-order traversal.
- An example visualization of BFS on a graph with 14 steps.
- Pseudocode and a Java program implementing BFS.
- Applications of BFS like shortest paths, social networks, web crawlers.
- The time and space complexity of BFS is O(V+E) and O(V).
- A conclusion that BFS is an important algorithm that traverses
The document discusses code optimization techniques in compilers. It covers the following key points:
1. Code optimization aims to improve code performance by replacing high-level constructs with more efficient low-level code while preserving program semantics. It occurs at various compiler phases like source code, intermediate code, and target code.
2. Common optimization techniques include constant folding, propagation, algebraic simplification, strength reduction, copy propagation, and dead code elimination. Control and data flow analysis are required to perform many optimizations.
3. Optimizations can be local within basic blocks, global across blocks, or inter-procedural across procedures. Representations like flow graphs, basic blocks, and DAGs are used to apply optimizations at
The document discusses different types of queues, including simple, circular, priority, and double-ended queues. It describes the basic queue operations of enqueue and dequeue, where new elements are added to the rear of the queue and existing elements are removed from the front. Circular queues are more memory efficient than linear queues by connecting the last queue element back to the first, forming a circle. Priority queues remove elements based on priority rather than order of insertion. Double-ended queues allow insertion and removal from both ends. Common applications of queues include CPU and disk scheduling, synchronization between asynchronous processes, and call center phone systems.
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.
This document discusses syntax analysis in compiler design. It begins by explaining that the lexer takes a string of characters as input and produces a string of tokens as output, which is then input to the parser. The parser takes the string of tokens and produces a parse tree of the program. Context-free grammars are introduced as a natural way to describe the recursive structure of programming languages. Derivations and parse trees are discussed as ways to parse strings based on a grammar. Issues like ambiguity and left recursion in grammars are covered, along with techniques like left factoring that can be used to transform grammars.
Tries are a data structure for storing strings that allow for fast pattern matching. A trie is a tree where each edge represents a character and each path from the root node to a leaf spells out a key. Standard tries insert strings by adding nodes for each character. Compressed tries reduce redundant nodes by compressing chains. Suffix tries store all suffixes of a text in a compressed trie to enable quick string queries. Tries support faster insertion and lookup compared to hash tables, with no collisions between keys.
Syntax analysis is the second phase of compiler design after lexical analysis. The parser checks if the input string follows the rules and structure of the formal grammar. It builds a parse tree to represent the syntactic structure. If the input string can be derived from the parse tree using the grammar, it is syntactically correct. Otherwise, an error is reported. Parsers use various techniques like panic-mode, phrase-level, and global correction to handle syntax errors and attempt to continue parsing. Context-free grammars are commonly used with productions defining the syntax rules. Derivations show the step-by-step application of productions to generate the input string from the start symbol.
The document describes depth-first search (DFS), an algorithm for traversing or searching trees or graphs. It defines DFS, explains the process as visiting nodes by going deeper until reaching the end and then backtracking, provides pseudocode for the algorithm, gives an example on a directed graph, and discusses time complexity (O(V+E)), advantages like linear memory usage, and disadvantages like possible infinite traversal without a cutoff depth.
This document provides an introduction to finite automata. It defines key concepts like alphabets, strings, languages, and finite state machines. It also describes the different types of automata, specifically deterministic finite automata (DFAs) and nondeterministic finite automata (NFAs). DFAs have a single transition between states for each input, while NFAs can have multiple transitions. NFAs are generally easier to construct than DFAs. The next class will focus on deterministic finite automata in more detail.
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.
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.
The document discusses lexical analysis in compilers. It describes how the lexical analyzer reads source code characters and divides them into tokens. Regular expressions are used to specify patterns for token recognition. The lexical analyzer generates a finite state automaton to recognize these patterns. Lexical analysis is the first phase of compilation that separates the input into tokens for the parser.
Hashing is the process of converting a given key into another value. A hash function is used to generate the new value according to a mathematical algorithm. The result of a hash function is known as a hash value or simply, a hash.
Hashing is a technique used to uniquely identify objects by assigning each object a key, such as a student ID or book ID number. A hash function converts large keys into smaller keys that are used as indices in a hash table, allowing for fast lookup of objects in O(1) time. Collisions, where two different keys hash to the same index, are resolved using techniques like separate chaining or linear probing. Common applications of hashing include databases, caches, and object representation in programming languages.
The document discusses the FIRST and FOLLOW sets used in compiler construction for predictive parsing. FIRST(X) is the set of terminals that can begin strings derived from X. FOLLOW(A) is the set of terminals that can immediately follow A. Rules are provided to compute the FIRST and FOLLOW sets for a grammar. Examples demonstrate applying the rules to sample grammars and presenting the resulting FIRST and FOLLOW sets.
The document provides an overview of compilers by discussing:
1. Compilers translate source code into executable target code by going through several phases including lexical analysis, syntax analysis, semantic analysis, code optimization, and code generation.
2. An interpreter directly executes source code statement by statement while a compiler produces target code as translation. Compiled code generally runs faster than interpreted code.
3. The phases of a compiler include a front end that analyzes the source code and produces intermediate code, and a back end that optimizes and generates the target code.
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.
This document describes the steps to construct a LALR parser from a context-free grammar:
1. Create an augmented grammar by adding a new start symbol and productions.
2. Generate kernel items by introducing dots in productions and adding second components. Then take closures of the items.
3. Compute the goto function to fill the parsing table.
4. Construct the CLR parsing table from the items and gotos.
5. Shrink the CLR parser by merging equivalent states to produce the more efficient LALR parsing table with fewer states.
The document discusses symbol tables, which are data structures used by compilers to track semantic information about identifiers, variables, functions, classes, etc. It provides details on:
- How various compiler phases like lexical analysis, syntax analysis, semantic analysis, code generation utilize and update the symbol table.
- Common data structures used to implement symbol tables like linear lists, hash tables and how they work.
- The information typically stored for different symbols like name, type, scope, memory location etc.
- Organization of symbol tables for block-structured vs non-block structured languages, including using multiple nested tables vs a single global table.
This document contains a presentation on Breadth-First Search (BFS) given to students. The presentation includes:
- An introduction to BFS and its inventor Konrad Zuse.
- Definitions of key terms like graph, tree, vertex, level-order traversal.
- An example visualization of BFS on a graph with 14 steps.
- Pseudocode and a Java program implementing BFS.
- Applications of BFS like shortest paths, social networks, web crawlers.
- The time and space complexity of BFS is O(V+E) and O(V).
- A conclusion that BFS is an important algorithm that traverses
The document discusses code optimization techniques in compilers. It covers the following key points:
1. Code optimization aims to improve code performance by replacing high-level constructs with more efficient low-level code while preserving program semantics. It occurs at various compiler phases like source code, intermediate code, and target code.
2. Common optimization techniques include constant folding, propagation, algebraic simplification, strength reduction, copy propagation, and dead code elimination. Control and data flow analysis are required to perform many optimizations.
3. Optimizations can be local within basic blocks, global across blocks, or inter-procedural across procedures. Representations like flow graphs, basic blocks, and DAGs are used to apply optimizations at
The document discusses different types of queues, including simple, circular, priority, and double-ended queues. It describes the basic queue operations of enqueue and dequeue, where new elements are added to the rear of the queue and existing elements are removed from the front. Circular queues are more memory efficient than linear queues by connecting the last queue element back to the first, forming a circle. Priority queues remove elements based on priority rather than order of insertion. Double-ended queues allow insertion and removal from both ends. Common applications of queues include CPU and disk scheduling, synchronization between asynchronous processes, and call center phone systems.
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.
This document discusses syntax analysis in compiler design. It begins by explaining that the lexer takes a string of characters as input and produces a string of tokens as output, which is then input to the parser. The parser takes the string of tokens and produces a parse tree of the program. Context-free grammars are introduced as a natural way to describe the recursive structure of programming languages. Derivations and parse trees are discussed as ways to parse strings based on a grammar. Issues like ambiguity and left recursion in grammars are covered, along with techniques like left factoring that can be used to transform grammars.
Tries are a data structure for storing strings that allow for fast pattern matching. A trie is a tree where each edge represents a character and each path from the root node to a leaf spells out a key. Standard tries insert strings by adding nodes for each character. Compressed tries reduce redundant nodes by compressing chains. Suffix tries store all suffixes of a text in a compressed trie to enable quick string queries. Tries support faster insertion and lookup compared to hash tables, with no collisions between keys.
Syntax analysis is the second phase of compiler design after lexical analysis. The parser checks if the input string follows the rules and structure of the formal grammar. It builds a parse tree to represent the syntactic structure. If the input string can be derived from the parse tree using the grammar, it is syntactically correct. Otherwise, an error is reported. Parsers use various techniques like panic-mode, phrase-level, and global correction to handle syntax errors and attempt to continue parsing. Context-free grammars are commonly used with productions defining the syntax rules. Derivations show the step-by-step application of productions to generate the input string from the start symbol.
The document describes depth-first search (DFS), an algorithm for traversing or searching trees or graphs. It defines DFS, explains the process as visiting nodes by going deeper until reaching the end and then backtracking, provides pseudocode for the algorithm, gives an example on a directed graph, and discusses time complexity (O(V+E)), advantages like linear memory usage, and disadvantages like possible infinite traversal without a cutoff depth.
This document provides an introduction to finite automata. It defines key concepts like alphabets, strings, languages, and finite state machines. It also describes the different types of automata, specifically deterministic finite automata (DFAs) and nondeterministic finite automata (NFAs). DFAs have a single transition between states for each input, while NFAs can have multiple transitions. NFAs are generally easier to construct than DFAs. The next class will focus on deterministic finite automata in more detail.
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.
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.
Top-down parsing constructs the parse tree from the top-down and left-to-right. Recursive descent parsing uses backtracking to find the left-most derivation, while predictive parsing does not require backtracking by using a special form of grammars called LL(1) grammars. Non-recursive predictive parsing is also known as LL(1) parsing and uses a table-driven approach without recursion or backtracking.
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.
The document discusses different types of parsing techniques:
- Parsing is the process of analyzing a string of tokens based on the rules of a formal grammar. It involves constructing a parse tree that represents the syntactic structure of the string based on the grammar.
- The main types of parsing are top-down parsing and bottom-up parsing. Top-down parsing constructs the parse tree from the root node down, while bottom-up parsing constructs it from the leaf nodes up.
- Predictive and recursive descent parsing are forms of top-down parsing, while shift-reduce parsing is a common bottom-up technique. Each method has advantages and limitations regarding efficiency and the type of grammar they can handle.
The document discusses parsing and compiler design concepts. It defines parsing as verifying that a string of tokens can be generated by a grammar and constructing a parse tree. It covers parse tree vs syntax tree, different types of grammars, derivation and reduction processes, ambiguous grammars, left recursion elimination, left factoring, and computing first and follow sets. The key topics are role of parsers, parse trees, grammar classification, derivation, ambiguous grammars, parsing techniques like top-down and bottom-up, and syntax analysis concepts.
1) The document discusses parsing methods for context-free grammars including top-down and bottom-up approaches. Top-down parsing starts with the start symbol and works towards the leaves, while bottom-up parsing begins at the leaves and works towards the root.
2) Key aspects of parsing covered include left recursion elimination, left factoring, shift-reduce parsing which uses a stack and parsing table, and constructing parse trees from the parsing process.
3) The output of parsers can include parse sequences, parse trees, and abstract syntax trees which abstract away implementation details.
Theory of automata and formal language lab manualNitesh Dubey
The document describes several experiments related to compiler design including lexical analysis, parsing, and code generation.
Experiment 1 involves writing a program to identify if a given string is an identifier or not using a DFA. Experiment 2 simulates a DFA to check if a string is accepted by the given automaton. Experiment 3 checks if a string belongs to a given grammar using a top-down parsing approach. Experiment 4 implements recursive descent parsing to parse expressions based on a grammar. Experiment 5 computes FIRST and FOLLOW sets and builds a LL(1) parsing table for a given grammar. Experiment 6 implements shift-reduce parsing to parse strings. Experiment 7 generates intermediate code like Polish notation, 3-address code, and quadruples
The document discusses syntax analysis, which is the second phase of compiler construction. It involves parsing the source code using a context-free grammar to check syntax and generate a parse tree. A parser checks if the code satisfies the grammar rules. Grammars can be ambiguous if they allow more than one parse. Left recursion, where a non-terminal derives itself, must be removed as it causes issues for top-down parsers. The document explains how to systematically eliminate immediate and non-immediate left recursion from grammars through substitution.
This document discusses top-down parsing and recursive descent parsing. It provides an example grammar and walks through top-down and bottom-up parses of a sample string. Recursive descent parsing is explained, with examples of how to write parsing functions for different grammar rules. The concepts of first sets and follow sets are introduced, which are needed to write predictive parsers without backtracking. Algorithms for computing first and follow sets are also provided.
This document discusses bottom-up parsing and shift-reduce parsing. It explains that bottom-up parsing constructs a parse tree beginning with the leaves and working up to the root. Shift-reduce parsing uses two main actions: shift, which pushes the current input symbol onto a stack, and reduce, which replaces symbols on the top of the stack with a non-terminal according to a production rule. An example is provided to demonstrate shift-reduce parsing through handle pruning, which finds handles within right sentential forms to trace the reverse of a rightmost derivation.
5-Introduction to Parsing and Context Free Grammar-09-05-2023.pptxvenkatapranaykumarGa
The document provides information about parsing and context-free grammars. It defines key concepts such as nonterminals, terminals, productions, derivations, ambiguity, left recursion, left factoring, LL(1) parsing, and computing first sets. It also lists different types of parsing including top-down parsing, bottom-up parsing, backtracking, predictive parsing, LR parsing, operator precedence parsing, and recursive descent parsing.
This chapter discusses syntax analysis and parsing. It covers topics such as syntax analyzers, context-free grammars, parse trees, ambiguity, left-recursion, left-factoring, and predictive parsing. Syntax analyzers check that a program satisfies the rules of a context-free grammar and build a parse tree. Grammars must be unambiguous and free of left-recursion to be suitable for top-down parsing techniques.
This document discusses top-down parsing and different types of top-down parsers, including recursive descent parsers, predictive parsers, and LL(1) grammars. It explains how to build predictive parsers without recursion by using a parsing table constructed from the FIRST and FOLLOW sets of grammar symbols. The key steps are: 1) computing FIRST and FOLLOW, 2) filling the predictive parsing table based on FIRST/FOLLOW, 3) using the table to parse inputs in a non-recursive manner by maintaining the parser's own stack. An example is provided to illustrate constructing the FIRST/FOLLOW sets and parsing table for a sample grammar.
The document describes a syntax analyzer (also known as a parser) which checks if a given source program satisfies the rules of a context-free grammar. The parser creates a parse tree representing the syntactic structure of the program if it satisfies the grammar. Context-free grammars use productions rules and define the syntax of a programming language. Parsers can be top-down or bottom-up and work on a stream of tokens from a lexical analyzer. Ambiguous grammars require disambiguation to ensure a unique parse tree for each program.
what is Parsing
different types of parsing
what is parser and role of parser
what is top-down parsing and bottom-up parsing
what is the problem in top-down parsing
design of top-down parsing and bottom-up parsing
examples of top-down parsing and bottom-up parsing
Credit : Nusrat Jahan & Fahima Hossain , Dept. of CSE, JnU, Dhaka.
Randomized Algorithm- Advanced Algorithm, Deterministic, Non Deterministic, LAS Vegas, MONTE Carlo Algorithm.
Cloudonomics is the economics of cloud computing. It provides an overall understanding of the business value of cloud computing for managers, executives, and strategists across industries. Some key economic aspects of cloud computing include economies of scale, location independence through dispersed infrastructure, unit or pay-per-use pricing, and on-demand scalable resources without upfront costs. The laws of cloudonomics establish that utility pricing is more cost effective than fixed infrastructure when demand varies, on-demand resources reduce the need for forecasting, aggregate cloud demand is smoother than individual demands, and large cloud providers benefit from economies of scale.
Constraint satisfaction problems (CSPs) involve assigning values to variables from given domains so that all constraints are satisfied. CSPs provide a general framework that can model many combinatorial problems. A CSP is defined by variables that take values from domains, and constraints specifying allowed value combinations. Real-world CSPs include scheduling, assignment problems, timetabling, mapping coloring and puzzles. Examples provided include cryptarithmetic, Sudoku, 4-queens, and graph coloring.
This document summarizes geographical routing in wireless sensor networks. It begins with an introduction to geographic routing protocols, which route packets based on the geographic position of nodes rather than their network addresses. It then discusses several specific geographic routing protocols, including Greedy Perimeter Stateless Routing (GPSR) and Geographical and Energy Aware Routing (GEAR). The document also covers topics like how nodes obtain location information, security issues in geographic routing like the Sybil attack, and concludes that geographic routing can enable scalable and energy-efficient routing in wireless sensor networks.
Streaming stored video allows video playback to begin before the entire file has been downloaded. It works by storing/buffering portions of the video at the client. There are three main types of streaming: UDP streaming, HTTP streaming, and adaptive HTTP streaming. HTTP streaming is most common today and works by transmitting the video file over HTTP as quickly as the network allows. Adaptive streaming addresses limitations of standard HTTP streaming by allowing clients to switch between multiple encodings of the video to adapt to changing network conditions.
Random Oracle Model & Hashing - Cryptography & Network SecurityMahbubur Rahman
This document discusses hashing and the random oracle model. It defines cryptographic hash functions as deterministic functions that map arbitrary strings to fixed-length outputs in a way that appears random. The random oracle model assumes an ideal hash function that behaves like a random function. The document discusses collision resistance, preimage resistance, and birthday attacks as they relate to finding collisions or preimages with a given hash function. It provides examples of calculating the number of messages an attacker would need to find collisions or preimages with different probabilities. The document concludes by listing some applications of cryptographic hash functions like password storage, file authenticity, and digital signatures.
Modern Block Cipher- Modern Symmetric-Key CipherMahbubur Rahman
Introduction to Modern Symmetric-Key Ciphers- This lecture will cover only "Modern Block Cipher".
Slide Credit: Maleka Khatun & Mahbubur Rahman
Dept. of CSE, JnU, BD.
The document provides information about web servers, database servers, and popular open source software used for each. It discusses what a web server and database server are, how they work, examples of common software like Apache and MySQL, and steps to install and configure Apache and MySQL on Ubuntu.
This document contains information about Lex, Yacc, Flex, and Bison. It provides definitions and descriptions of each tool. Lex is a lexical analyzer generator that reads input specifying a lexical analyzer and outputs C code implementing a lexer. Yacc is a parser generator that takes a grammar description and snippets of C code as input and outputs a shift-reduce parser in C. Flex is a tool similar to Lex for generating scanners based on regular expressions. Bison is compatible with Yacc and can be used to develop language parsers.
Transform tomorrow: Master benefits analysis with Gen AI today webinar
Wednesday 30 April 2025
Joint webinar from APM AI and Data Analytics Interest Network and APM Benefits and Value Interest Network
Presenter:
Rami Deen
Content description:
We stepped into the future of benefits modelling and benefits analysis with this webinar on Generative AI (Gen AI), presented on Wednesday 30 April. Designed for all roles responsible in value creation be they benefits managers, business analysts and transformation consultants. This session revealed how Gen AI can revolutionise the way you identify, quantify, model, and realised benefits from investments.
We started by discussing the key challenges in benefits analysis, such as inaccurate identification, ineffective quantification, poor modelling, and difficulties in realisation. Learnt how Gen AI can help mitigate these challenges, ensuring more robust and effective benefits analysis.
We explored current applications and future possibilities, providing attendees with practical insights and actionable recommendations from industry experts.
This webinar provided valuable insights and practical knowledge on leveraging Gen AI to enhance benefits analysis and modelling, staying ahead in the rapidly evolving field of business transformation.
Form View Attributes in Odoo 18 - Odoo SlidesCeline George
Odoo is a versatile and powerful open-source business management software, allows users to customize their interfaces for an enhanced user experience. A key element of this customization is the utilization of Form View attributes.
How to Manage Amounts in Local Currency in Odoo 18 PurchaseCeline George
In this slide, we’ll discuss on how to manage amounts in local currency in Odoo 18 Purchase. Odoo 18 allows us to manage purchase orders and invoices in our local currency.
How To Maximize Sales Performance using Odoo 18 Diverse views in sales moduleCeline George
One of the key aspects contributing to efficient sales management is the variety of views available in the Odoo 18 Sales module. In this slide, we'll explore how Odoo 18 enables businesses to maximize sales insights through its Kanban, List, Pivot, Graphical, and Calendar views.
Ancient Stone Sculptures of India: As a Source of Indian HistoryVirag Sontakke
This Presentation is prepared for Graduate Students. A presentation that provides basic information about the topic. Students should seek further information from the recommended books and articles. This presentation is only for students and purely for academic purposes. I took/copied the pictures/maps included in the presentation are from the internet. The presenter is thankful to them and herewith courtesy is given to all. This presentation is only for academic purposes.
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Clearing Karma, Letting go.
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2. MODEL OF COMPILER FRONT END 2
Front End
Also called parsing , where
generates parse tree
Syntax analysis
3. PARSING 3
When the parser starts constructing the
parse tree from the start symbol and then
tries to transform the start symbol to the
input, it is called top-down parsing.
Where bottom-up parsing starts with
the input symbols and tries to construct
the parse tree up to the start symbol.
4. TOP DOWN PERSER 4
Predictive parser is a recursive descent
parser, which has the capability to predict
which production is to be used to replace
the input string. The predictive parser
does not suffer from backtracking.
5. PREDICTIVE PARSER 5
Predictive parsing uses a stack and
a parsing table to parse the input
and generate a parse tree.
Both the stack and the input
contains an end symbol $to denote
that the stack is empty and the input
is consumed.
The parser refers to the parsing
table to take any decision on the
input and stack element
combination.
6. LL(1) PARSER 6
An LL parser is called an LL(k) parser if
it uses k tokens of look ahead when
parsing a sentence.
LL grammars, particularly LL(1)
grammars, as parsers are easy to
construct, and many computer
languages are designed to be LL(1) for
this reason.
The 1 stands for using one input symbol
of look ahead at each step to make
parsing action decision.
7. CONTINUE…
LL(k) parsers must predict which production replace a non-terminal with as soon as
they see the non-terminal. The basic LL algorithm starts with a stack containing [S, $]
(top to bottom) and does whichever of the following is applicable until done:
If the top of the stack is a non-terminal, replace the top of the stack with one of
the productions for that non-terminal, using the next k input symbols to decide
which one (without moving the input cursor), and continue.
If the top of the stack is a terminal, read the next input token. If it is the same
terminal, pop the stack and continue. Otherwise, the parse has failed and the
algorithm finishes.
If the stack is empty, the parse has succeeded and the algorithm finishes. (We
assume that there is a unique EOF-marker $ at the end of the input.)
So look ahead meaning is - looking at input tokens without moving the input
cursor.
7
8. PRIME REQUIREMENT OF LL(1)
The grammar must be -
no left factoring
no left recursion
FIRST() & FOLLOW()
Parsing Table
Stack Implementation
Parse Tree
8
10. LEFT FACTORING
A grammar is said to be left factored when it is of the form –
A -> αβ1 | αβ2 | αβ3 | …… | αβn | γ
The productions start with the same terminal (or set of terminals).
When the choice between two alternative A-productions is not clear, we
may be able to rewrite the productions to defer the decision until enough
of the input has been seen to make the right choice.
For the grammar
A -> αβ1 | αβ2 | αβ3 | …… | αβn | γ
The equivalent left factored grammar will be –
A -> αA’ | γ
A’ -> β1 | β2 | β3 | …… | βn
10
11. CONTINUE…
For example :
the input string is - aab & grammar is
S ->aAb|aA|ab
A ->bAc|ab
After removing left factoring -
S ->aA’
A’ ->Ab|A|b
A ->ab|bAc
11
13. RECURSION
RECURSION:
The process in which a function calls itself directly or indirectly is called recursion
and the corresponding function is called as recursive function.
TYPES OF RECURSION
LEFT RECURSION RIGHT RECURSION
13
14. Left Recursion Right Recursion
For grammar: For grammar:
A -> A | β A -> A| β
A
A A
A A
A A
β A
β
This parse tree generate β * This parse tree generate * β
14
15. Right recursion-
A production of grammar is said to have right recursion if
the right most variable RHS is same as
variable of its LHS. e.g. A -> A| β
A grammar containing a production having right recursion is
called as a right recursive grammar.
Right recursion does not create any problem for the top
down parsers.
Therefore, there is no need of eliminating right recursion
from the grammar.
15
16. Left recursion-
A production of grammar is said to have left
recursion if the leftmost variable of its RHS is same
as variable of its LHS. e.g. A -> A | β
A grammar containing a production having left
recursion is called as a left recursive grammar.
Left recursion is eliminated because top down
parsing method can not handle left recursive
grammar.
16
17. Left Recursion
A grammar is left recursive if it has a nonterminal A such that there is a
derivation
A -> A | β for some string .
Immediate/direct left recursion:
A production is immediately left recursive if its left hand side and the head of its
right hand side are the same symbol, e.g. A ->A , where α is sequence
of non terminals and terminals.
Indirect left recursion:
Indirect left recursion occurs when the definition of left recursion is satisfied via
several substitutions. It entails a set of rules following the pattern
. A → Br
B → Cs
C → At
Here, starting with a, we can derive A -> Atsr
17
18. Elimination of Left-Recursion
Suppose the grammar were
A A |
How could the parser decide how many times to use the production A
A before using the production A --> ?
Left recursion in a production may be removed by transforming the
grammar in the following way.
Replace
A A |
With
A A'
A' A' |
18
19. EXAMPLE OF IMMEDIATE LEFT RECURSION:
Consider the left recursive grammar
E E + T | T
T T * F | F
F (E) | id
Apply the transformation to E:
E T E'
E' + T E' |
Then apply the transformation to T:
T F T'
T' * F T' |
Now the grammar is
E T E'
E' + T E' |
T F T'
T' * F T' |
F (E) | id
19
20. Continue…
The case of several immediate left recursive -productions. Assume
that the set of all -productions has the form
A → A 1 | A 2 | · · · | A m | β1 | β2| · · · | βn
Represents all the -productions of the grammar, and no βi begins
with A, then we can replace these -productions by
A →β1A′ | β2A′| · · · | βnA′
A′ → 1A′ | 2A′ | · · · | mA′ |
20
21. Example:
Consider the left recursive grammar
S → SX | SSb| XS | a
X → Xb | Sa
Apply the transformation to S:
S → XSS′ | aS′
S′ → XS′ | SbS′ | ε
Apply the transformation to X:
X → SaX′
X′ → bX′ | ε
Now the grammar is
S → XSS′ | aS′
S′ → XS′ | SbS′ | ε
X → SaX′
X′ → bX′ | ε
21
22. Example of elimination indirect left
recursion:
S A A | 0
A S S | 1
Considering the ordering S, A, we get:
S A A | 0
A S | 0S | 1
And removing immediate left recursion, we get
S A A | 0
A 0S A′ | 1A′
A′ ε | AS A′
22
24. Why using FIRST and FOLLOW:
During parsing FIRST and FOLLOW help us to choose
which production to apply , based on the next input signal.
We know that we need of backtracking in syntax analysis, which is
really a complex process to implement. There can be easier way to
sort out this problem by using FIRST AND FOLLOW.
If the compiler would have come to know in advance, that what is the
“first character of the string produced when a production rule is
applied”, and comparing it to the current character or token in the input
string it sees, it can wisely take decision on which production rule to
apply .
FOLLOW is used only if the current non terminal can derive ε .
24
25. Rules of FIRST
FIRST always find out the terminal symbol from the grammar.
When we check out FIRST for any symbol then if we find any
terminal symbol in first place then we take it. And not to see the
next symbol.
If a grammar is
A → a then FIRST ( A )={ a }
If a grammar is
A → a B then FIRST ( A )={ a }
25
26. Rules of FIRST
If a grammar is
A → aB ǀ ε then FIRST ( A )={ a, ε }
If a grammar is
A → BcD ǀ ε
B → eD ǀ ( A )
Here B is non terminal. So, we check the transition of B and
find the FIRST of A.
then FIRST ( A )={ e,( , ε }
26
27. Rules of FOLLOW
For doing FOLLOW operation we need FIRST operation mostly. In FOLLOW
we use a $ sign for the start symbol. FOLLOW always check the right
portion of the symbol.
If a grammar is
A → BAc ; A is start symbol.
Here firstly check if the selected symbol stays in right side of the grammar.
We see that c is right in A.
then FOLLOW (A) = {c , $ }
27
28. Rules of FOLLOW
If a grammar is
A → BA’
A' →*Bc
Here we see that there is nothing at the right side of A' . So
FOLLOW ( A' )= FOLLOW ( A )= { $ }
Because A' follows the start symbol.
28
29. Rules of FOLLOW
If a grammar is
A → BC
B → Td
C →*D ǀ ε
When we want to find FOLLOW (B),we see that B follows by C . Now
put the FIRST( C) in the there.
FIRST(C)={*, ε }.
But when the value is € it follows the parents symbol. So
FOLLOW(B)={*,$ }
29
30. Example of FIRST and FOLLOW
Symbol FIRST FOLLOW
E
E’
T
T’
F
GRAMMAR:
E -> TE'
E'-> +TE'|ε
T -> FT'
T' -> *FT'|ε
F -> (E)|id
30
31. Example of FIRST and FOLLOW
Symbol FIRST FOLLOW
E { ( , id }
E'
T
T'
F
GRAMMAR:
E -> TE'
E'-> +TE'|ε
T -> FT'
T' -> *FT'|ε
F -> (E)|id
31
32. Example of FIRST and FOLLOW
Symbol FIRST FOLLOW
E { ( , id }
E' { + , ε }
T
T'
F
GRAMMAR:
E -> TE'
E'-> +TE'|ε
T -> FT'
T' -> *FT'|ε
F -> (E)|id
32
33. Example of FIRST and FOLLOW
Symbol FIRST FOLLOW
E { ( , id }
E' { + , ε }
T { id , ( }
T'
F
GRAMMAR:
E -> TE'
E'-> +TE'|ε
T -> FT'
T' -> *FT'|ε
F -> (E)|id
33
34. Example of FIRST and FOLLOW
Symbol FIRST FOLLOW
E { ( , id }
E' { + , ε }
T { id , ( }
T' { * , ε }
F
GRAMMAR:
E -> TE'
E'-> +TE'|ε
T -> FT'
T' -> *FT'|ε
F -> (E)|id
34
35. Example of FIRST and FOLLOW
Symbol FIRST FOLLOW
E { ( , id }
E' { + , ε }
T { id , ( }
T' { * , ε }
F { id , ( }
GRAMMAR:
E -> TE'
E'-> +TE'|ε
T -> FT'
T' -> *FT'|ε
F -> (E)|id
35
36. Example of FIRST and FOLLOW
Symbol FIRST FOLLOW
E { ( , id } { $ , ) }
E' { + , ε }
T { id , ( }
T' { * , ε }
F { id , ( }
GRAMMAR:
E -> TE'
E'-> +TE'|ε
T -> FT'
T' -> *FT'|ε
F -> (E)|id
36
37. Example of FIRST and FOLLOW
Symbol FIRST FOLLOW
E { ( , id } { $ , ) }
E' { + , ε } { $ , ) }
T { id , ( }
T' { * , ε }
F { id , ( }
GRAMMAR:
E -> TE'
E'-> +TE'|ε
T -> FT'
T' -> *FT'|ε
F -> (E)|id
37
38. Example of FIRST and FOLLOW
Symbol FIRST FOLLOW
E { ( , id } { $ , ) }
E' { + , ε } { $ , ) }
T { id , ( } { $ , ) ,+ }
T' { * , ε }
F { id , ( }
GRAMMAR:
E -> TE'
E'-> +TE'|ε
T -> FT'
T' -> *FT'|ε
F -> (E)|id
38
39. Example of FIRST and FOLLOW
Symbol FIRST FOLLOW
E { ( , id } { $ , ) }
E' { + , ε } { $ , ) }
T { id , ( } { $ , ) ,+ }
T' { * , ε } { $ , ) , + }
F { id , ( }
GRAMMAR:
E -> TE'
E'-> +TE'|ε
T -> FT'
T' -> *FT'|ε
F -> (E)|id
39
40. Example of FIRST and FOLLOW
Symbol FIRST FOLLOW
E { ( , id } { $ , ) }
E' { + , ε } { $ , ) }
T { id , ( } { $ , ) ,+ }
T' { * , ε } { $ , ) , + }
F { id , ( } { $ , ) , + , * }
GRAMMAR:
E -> TE'
E'-> +TE'|ε
T -> FT'
T' -> *FT'|ε
F -> (E)|id
40
42. Example of LL(1) grammar
E -> TE’
E’ -> +TE’|ε
T -> FT’
T’ -> *FT’|ε
F -> (E)|id
42
43. TABLE:
PARSING
TABLE
TABLE:
FIRST & FOLLOW
43
Production Symbol FOLLOW
E -> TE’ { ( , id } { $ , ) }
E’ -> +TE’|ε { + , ε } { $ , ) }
T -> FT’ { ( , id } { + , $ , ) }
T’ -> *FT’|ε { * , ε } { + , $ , ) }
F -> (E)|id { ( , id } { *, + , $ , ) }
Non
Terminal
INPUT SYMBOLS
id + * ( ) $
E
E’
T
T’
F
44. TABLE:
PARSING
TABLE
TABLE:
FIRST & FOLLOW
44
Production Symbol FOLLOW
E -> TE’ { ( , id } { $ , ) }
E’ -> +TE’|ε { + , ε } { $ , ) }
T -> FT’ { ( , id } { + , $ , ) }
T’ -> *FT’|ε { * , ε } { + , $ , ) }
F -> (E)|id { ( , id } { *, + , $ , ) }
Non
Terminal
INPUT SYMBOLS
id + * ( ) $
E E -> TE’
E’
T
T’
F
45. TABLE:
PARSING
TABLE
TABLE:
FIRST & FOLLOW
45
Production Symbol FOLLOW
E -> TE’ { ( , id } { $ , ) }
E’ -> +TE’|ε { + , ε } { $ , ) }
T -> FT’ { ( , id } { + , $ , ) }
T’ -> *FT’|ε { * , ε } { + , $ , ) }
F -> (E)|id { ( , id } { *, + , $ , ) }
Non
Terminal
INPUT SYMBOLS
id + * ( ) $
E E -> TE’ E -> TE’
E’
T
T’
F
46. TABLE:
PARSING
TABLE
TABLE:
FIRST & FOLLOW
46
Production Symbol FOLLOW
E -> TE’ { ( , id } { $ , ) }
E’ -> +TE’|ε { + , ε } { $ , ) }
T -> FT’ { ( , id } { + , $ , ) }
T’ -> *FT’|ε { * , ε } { + , $ , ) }
F -> (E)|id { ( , id } { *, + , $ , ) }
Non
Terminal
INPUT SYMBOLS
id + * ( ) $
E E -> TE’ E -> TE’
E’ E’-> +TE’
T
T’
F
47. TABLE:
PARSING
TABLE
TABLE:
FIRST & FOLLOW
47
Production Symbol FOLLOW
E -> TE’ { ( , id } { $ , ) }
E’ -> +TE’|ε { + , ε } { $ , ) }
T -> FT’ { ( , id } { + , $ , ) }
T’ -> *FT’|ε { * , ε } { + , $ , ) }
F -> (E)|id { ( , id } { *, + , $ , ) }
Non
Terminal
INPUT SYMBOLS
id + * ( ) $
E E -> TE’ E -> TE’
E’ E’-> +TE’ E’ -> ε E’ -> ε
T
T’
F
48. TABLE:
PARSING
TABLE
TABLE:
FIRST & FOLLOW
48
Production Symbol FOLLOW
E -> TE’ { ( , id } { $ , ) }
E’ -> +TE’|ε { + , ε } { $ , ) }
T -> FT’ { ( , id } { + , $ , ) }
T’ -> *FT’|ε { * , ε } { + , $ , ) }
F -> (E)|id { ( , id } { *, + , $ , ) }
Non
Terminal
INPUT SYMBOLS
id + * ( ) $
E E -> TE’ E -> TE’
E’ E’-> +TE’ E’ -> ε E’ -> ε
T T -> FT’
T’
F
49. TABLE:
PARSING
TABLE
TABLE:
FIRST & FOLLOW
49
Production Symbol FOLLOW
E -> TE’ { ( , id } { $ , ) }
E’ -> +TE’|ε { + , ε } { $ , ) }
T -> FT’ { ( , id } { + , $ , ) }
T’ -> *FT’|ε { * , ε } { + , $ , ) }
F -> (E)|id { ( , id } { *, + , $ , ) }
Non
Terminal
INPUT SYMBOLS
id + * ( ) $
E E -> TE’ E -> TE’
E’ E’-> +TE’ E’ -> ε E’ -> ε
T T -> FT’ T -> FT’
T’
F
50. TABLE:
PARSING
TABLE
TABLE:
FIRST & FOLLOW
50
Production Symbol FOLLOW
E -> TE’ { ( , id } { $ , ) }
E’ -> +TE’|ε { + , ε } { $ , ) }
T -> FT’ { ( , id } { + , $ , ) }
T’ -> *FT’|ε { * , ε } { + , $ , ) }
F -> (E)|id { ( , id } { *, + , $ , ) }
Non
Terminal
INPUT SYMBOLS
id + * ( ) $
E E -> TE’ E -> TE’
E’ E’-> +TE’ E’ -> ε E’ -> ε
T T -> FT’ T -> FT’
T’ T’ -> *FT’
F
51. TABLE:
PARSING
TABLE
TABLE:
FIRST & FOLLOW
51
Production Symbol FOLLOW
E -> TE’ { ( , id } { $ , ) }
E’ -> +TE’|ε { + , ε } { $ , ) }
T -> FT’ { ( , id } { + , $ , ) }
T’ -> *FT’|ε { * , ε } { + , $ , ) }
F -> (E)|id { ( , id } { *, + , $ , ) }
Non
Terminal
INPUT SYMBOLS
id + * ( ) $
E E -> TE’ E -> TE’
E’ E’-> +TE’ E’ -> ε E’ -> ε
T T -> FT’ T -> FT’
T’ T’ -> ε T’ -> *FT’ T’ -> ε T’ -> ε
F
52. TABLE:
PARSING
TABLE
TABLE:
FIRST & FOLLOW
52
Production Symbol FOLLOW
E -> TE’ { ( , id } { $ , ) }
E’ -> +TE’|ε { + , ε } { $ , ) }
T -> FT’ { ( , id } { + , $ , ) }
T’ -> *FT’|ε { * , ε } { + , $ , ) }
F -> (E)|id { ( , id } { *, + , $ , ) }
Non
Terminal
INPUT SYMBOLS
id + * ( ) $
E E -> TE’ E -> TE’
E’ E’-> +TE’ E’ -> ε E’ -> ε
T T -> FT’ T -> FT’
T’ T’ -> ε T’ -> *FT’ T’ -> ε T’ -> ε
F F -> id
53. TABLE:
PARSING
TABLE
TABLE:
FIRST & FOLLOW
53
Production Symbol FOLLOW
E -> TE’ { ( , id } { $ , ) }
E’ -> +TE’|ε { + , ε } { $ , ) }
T -> FT’ { ( , id } { + , $ , ) }
T’ -> *FT’|ε { * , ε } { + , $ , ) }
F -> (E)|id { ( , id } { *, + , $ , ) }
Non
Terminal
INPUT SYMBOLS
id + * ( ) $
E E -> TE’ E -> TE’
E’ E’-> +TE’ E’ -> ε E’ -> ε
T T -> FT’ T -> FT’
T’ T’ -> ε T’ -> *FT’ T’ -> ε T’ -> ε
F F -> id F -> (E)
54. Continue…
54
TABLE: PARSING TABLE
Non
Terminal
INPUT SYMBOLS
id + * ( ) $
E E -> TE’ E -> TE’
E’ E’-> +TE’ E’ -> ε E’ -> ε
T T -> FT’ T -> FT’
T’ T’ -> ε T’ -> *FT’ T’ -> ε T’ -> ε
F F -> id F -> (E)
This grammar is LL(1).
So, the parse tree can be derived from the stack
implementation of the given parsing table.
55. There are grammars which may requite LL(1) parsing.
For e.g. Look at next grammar…..
55
Continue…
56. Continue…
GRAMMAR:
S iEtSS’ | a
S’ eS |ε
E b
SYMBOL FIRST FOLLOW
S a , i $ , e
S’ e , ε $ , e
E b t
TABLE: FIRST & FOLLOW
56
57. TABLE:
PARSING TABLE
TABLE:
FAST & FOLLOW
57
SYMBOL FIRST FOLLOW
S iEtSS’ | a
a , i $ , e
S’ eS |ε
e, ε $ , e
E b
b t
Non
Terminal
INPUT SYMBOLS
a b e i t $
S
S’
E
58. TABLE:
PARSING TABLE
TABLE:
FAST & FOLLOW
58
SYMBOL FIRST FOLLOW
S iEtSS’ | a
a , i $ , e
S’ eS |ε
e, ε $ , e
E b
b t
Non
Terminal
INPUT SYMBOLS
a b e i t $
S Sa
S’
E
59. TABLE:
PARSING TABLE
TABLE:
FAST & FOLLOW
59
SYMBOL FIRST FOLLOW
S iEtSS’ | a
a , i $ , e
S’ eS |ε
e, ε $ , e
E b
b t
Non
Terminal
INPUT SYMBOLS
a b e i t $
S Sa
SiEtSS
’
S’
E
60. TABLE:
PARSING TABLE
TABLE:
FAST & FOLLOW
60
SYMBOL FIRST FOLLOW
S iEtSS’ | a
a , i $ , e
S’ eS |ε
e, ε $ , e
E b
b t
Non
Terminal
INPUT SYMBOLS
a b e i t $
S Sa
SiEtSS
’
S’ S’ eS
E
61. TABLE:
PARSING TABLE
TABLE:
FAST & FOLLOW
61
SYMBOL FIRST FOLLOW
S iEtSS’ | a
a , i $ , e
S’ eS |ε
e, ε $ , e
E b
b t
Non
Terminal
INPUT SYMBOLS
a b e i t $
S Sa
SiEtSS
’
S’
S’ eS
S’ε
S’ε
E
62. TABLE:
PARSING TABLE
TABLE:
FAST & FOLLOW
62
SYMBOL FIRST FOLLOW
S iEtSS’ | a
a , i $ , e
S’ eS |ε
e, ε $ , e
E b
b t
Non
Terminal
INPUT SYMBOLS
a b e i t $
S Sa
SiEtSS
’
S’
S’ eS
S’ε
S’ε
E E b
63. TABLE:
PARSING TABLE
TABLE:
FAST & FOLLOW
63
AMBIGUITY
SYMBOL FIRST FOLLOW
S iEtSS’ | a
a , i $ , e
S’ eS |ε
e, ε $ , e
E b
b t
Non
Terminal
INPUT SYMBOLS
a b e i t $
S Sa
SiEtSS
’
S’
S’ eS
S’ε
S’ε
E E b
64. Continue…
The grammar is ambiguous and it is evident by the fact that
we have two entries corresponding to M[S’,e] containing
S’ ε and S’ eS.
Note that the ambiguity will be solved if we use LL(2) parser, i.e.
Always see for the two input symbols.
LL(1) grammars have distinct properties.
- No ambiguous grammar or left recursive grammar
can be LL(1).
Thus , the given grammar is not LL(1).
64
66. STACK Implementation
The predictive parser uses an explicit stack to keep track of pending
non-terminals. It can thus be implemented without recursion.
Note that productions output are tracing out a lefmost derivation
The grammar symbols on the stack make up left-sentential forms
66
67. LL(1) Stack
The input buffer contains the string to be parsed; $ is the end-
of-input marker
The stack contains a sequence of grammar symbols
Initially, the stack contains the start symbol of the grammar on
the top of $.
67
68. LL(1) Stack
The parser is controlled by a program that behaves as follows:
The program considers X, the symbol on top of the stack, and a, the
current input symbol.
These two symbols, X and a determine the action of the parser.
There are three possibilities.
68
69. LL(1) Stack
1. X a $,
the parser halts and annouces successful completion.
2. X a $
the parser pops x off the stack and advances input pointer to next
input symbol
3. If X is a nonterminal, the program consults entry M[x,a] of parsing
table M.
If the entry is a production M[x,a] = {x → uvw } then the
parser replaces x on top of the stack by wvu (with u on top).
As output, the parser just prints the production used:
x → uvw .
69
70. LL(1) Stack
Example:
Let’s parse the input
string
id+idid
Using the nonrecursive
LL(1) parser
70
Grammar:
E -> TE'
E'-> +TE'|ε
T -> FT'
T' -> *FT'|ε
F -> (E)|id
74. 74
id + id id
$
$
stack Parsing
Table M
T →
T
E'
F T'
Non
Terminal
INPUT SYMBOLS
id + * ( ) $
E E -> TE’ E -> TE’
E’ E' -> +TE’ E’ -> ε E’ -> ε
T T -> FT’ T -> FT’
T’ T’ -> ε T’ -> *FT’ T’ -> ε T’ -> ε
F F -> id F -> (E)
75. 75
T'
id + id id
$
$
stack Parsing
Table M
→
E'
F
F id
Non
Terminal
INPUT SYMBOLS
id + * ( ) $
E E -> TE’ E -> TE’
E’ E' -> +TE’ E’ -> ε E’ -> ε
T T -> FT’ T -> FT’
T’ T’ -> ε T’ -> *FT’ T’ -> ε T’ -> ε
F F -> id F -> (E)
76. 76
T'
id + id id
$
$
stack Parsing
Table M
E'
id
Non
Terminal
INPUT SYMBOLS
id + * ( ) $
E E -> TE’ E -> TE’
E’ E' -> +TE’ E’ -> ε E’ -> ε
T T -> FT’ T -> FT’
T’ T’ -> ε T’ -> *FT’ T’ -> ε T’ -> ε
F F -> id F -> (E)
77. 77
T'
+ id id
$
$
stack Parsing
Table M
→
E'
T'
id
Non
Terminal
INPUT SYMBOLS
id + * ( ) $
E E -> TE’ E -> TE’
E’ E' -> +TE’ E’ -> ε E’ -> ε
T T -> FT’ T -> FT’
T’ T’ -> ε T’ -> *FT’ T’ -> ε T’ -> ε
F F -> id F -> (E)
78. 78
+ id id
$
$
stack Parsing
Table M
→
E'
E' +
id
E'T
Non
Terminal
INPUT SYMBOLS
id + * ( ) $
E E -> TE’ E -> TE’
E’ E' -> +TE’ E’ -> ε E’ -> ε
T T -> FT’ T -> FT’
T’ T’ -> ε T’ -> *FT’ T’ -> ε T’ -> ε
F F -> id F -> (E)
79. 79
+ id id
$
$
stack Parsing
Table M
E'
+
id
T
Non
Terminal
INPUT SYMBOLS
id + * ( ) $
E E -> TE’ E -> TE’
E’ E' -> +TE’ E’ -> ε E’ -> ε
T T -> FT’ T -> FT’
T’ T’ -> ε T’ -> *FT’ T’ -> ε T’ -> ε
F F -> id F -> (E)
80. 80
MATCHED STACK INPUT ACTION
E$ id+id * id$
TE’$ id+id * id$ E->TE’
FT’E’$ id+id * id$ T->FT’
id T’E’$ id+id * id$ F->id
id T’E’$ +id * id$ Match id
id E’$ +id * id$ T’->Є
id +TE’$ +id * id$ E’-> +TE’
id+ TE’$ id * id$ Match +
id+ FT’E’$ id * id$ T-> FT’
id+ idT’E’$ id * id$ F-> id
id+id T’E’$ * id$ Match id
id+id * FT’E’$ * id$ T’-> *FT’
id+id * FT’E’$ id$ Match *
id+id * idT’E’$ id$ F-> id
id+id * id T’E’$ $ Match id
id+id * id E’$ $ T’-> Є
id+id * id $ $ E’-> Є