Convention-Based Syntactic Descriptions
•
0 likes•321 views
The document introduces a convention-based syntax notation designed for both humans and parser generators. Key aspects include using conventions to simplify EBNF notation, defining rules without delimiters, inferring token sets from rules, and representing abstract syntax trees with variables. The approach was motivated by limitations of existing formalisms. Examples are provided for microsyntax, macrosyntax, and representing abstract syntax trees. Future work discussed expanding the approach to support additional language features.
Report
Share
Report
Share
![Outline ,[object Object]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
Recommended
Lecture 13 intermediate code generation 2.pptx
This document discusses code generation for control flow statements and boolean expressions in programming languages. It introduces type conversions, abstract syntax trees, control flow, and generating three-address code for booleans. A key technique discussed is backpatching, which allows saving instruction labels as indices and later inserting target addresses to avoid an extra pass for setting jump targets. An example shows applying backpatching to an annotated parse tree for a boolean expression.
Syntax analyzer
The document discusses syntax analysis in compilers. It defines syntax as the arrangement of words and phrases to create meaningful sentences. The syntax analyzer or parser checks the stream of tokens for grammatical correctness according to the language's grammar. It determines if the input is well-formed syntactically. The parser ensures sentences in a program abide by the syntax of the language and detects any errors. The document also provides examples of English and programming language syntax and defines key concepts related to context-free grammars.
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.
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.
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.
Lexical
The document discusses lexical analysis, which is the first stage of syntax analysis for programming languages. It covers terminology, using finite automata and regular expressions to describe tokens, and how lexical analyzers work. Lexical analyzers extract lexemes from source code and return tokens to the parser. They are often implemented using finite state machines generated from regular grammar descriptions of the lexical patterns in a language.
The JavaScript Programming Language
The document provides an overview of the JavaScript programming language, including its history, key concepts, values, operators, statements, and objects. It discusses JavaScript's misunderstood nature due to its name, design errors in early implementations, and use in browsers. Some key points made include: JavaScript is a functional language; it uses prototypal inheritance instead of classes; all values are objects except for primitive values; and functions are first-class objects that can be assigned and passed around.
The Java Script Programming Language
The document provides an overview of the JavaScript programming language, including its history, key concepts, values, operators, statements, functions, and objects. It discusses JavaScript's origins, misunderstandings, dynamic and loosely typed nature, use of prototypes for inheritance rather than classes, and treatment of arrays and objects.
Recommended
Lecture 13 intermediate code generation 2.pptx
This document discusses code generation for control flow statements and boolean expressions in programming languages. It introduces type conversions, abstract syntax trees, control flow, and generating three-address code for booleans. A key technique discussed is backpatching, which allows saving instruction labels as indices and later inserting target addresses to avoid an extra pass for setting jump targets. An example shows applying backpatching to an annotated parse tree for a boolean expression.
Syntax analyzer
The document discusses syntax analysis in compilers. It defines syntax as the arrangement of words and phrases to create meaningful sentences. The syntax analyzer or parser checks the stream of tokens for grammatical correctness according to the language's grammar. It determines if the input is well-formed syntactically. The parser ensures sentences in a program abide by the syntax of the language and detects any errors. The document also provides examples of English and programming language syntax and defines key concepts related to context-free grammars.
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.
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.
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.
Lexical
The document discusses lexical analysis, which is the first stage of syntax analysis for programming languages. It covers terminology, using finite automata and regular expressions to describe tokens, and how lexical analyzers work. Lexical analyzers extract lexemes from source code and return tokens to the parser. They are often implemented using finite state machines generated from regular grammar descriptions of the lexical patterns in a language.
The JavaScript Programming Language
The document provides an overview of the JavaScript programming language, including its history, key concepts, values, operators, statements, and objects. It discusses JavaScript's misunderstood nature due to its name, design errors in early implementations, and use in browsers. Some key points made include: JavaScript is a functional language; it uses prototypal inheritance instead of classes; all values are objects except for primitive values; and functions are first-class objects that can be assigned and passed around.
The Java Script Programming Language
The document provides an overview of the JavaScript programming language, including its history, key concepts, values, operators, statements, functions, and objects. It discusses JavaScript's origins, misunderstandings, dynamic and loosely typed nature, use of prototypes for inheritance rather than classes, and treatment of arrays and objects.
Javascript
The JavaScript Programming Language document provides an overview of the JavaScript programming language, including its history, key concepts, values, operators, statements, and objects. It notes that JavaScript is a multi-paradigm scripting language that is misunderstood as only for web development. The document outlines JavaScript's core data types, objects, functions, and prototypal inheritance model.
Syntax analysis
The document discusses syntax analysis and parsing. It defines a syntax analyzer as creating the syntactic structure of a source program in the form of a parse tree. A syntax analyzer, also called a parser, checks if a program satisfies the rules of a context-free grammar and produces the parse tree if it does, or error messages otherwise. It describes top-down and bottom-up parsing methods and how parsers use grammars to analyze syntax.
Data types in c++
A very clear explanation of Data Types in C++ with an example using small programs. Memory allocation of data types also covered.
Glimpses of C++0x
This is Work-In-Progress. Developing a series of lectures on C++0x. This will augment my presentations on C++ and Design Pattern. First trial run was done at Interra, Noida in 2009
LVEE 2014: Text parsing with Python and PLY
This document summarizes text parsing with Python and PLY. It discusses formal languages and grammars, lexers and tokens, parser generators like PLY Lex and PLY YACC. Key points include: formal grammars use production rules to define a language's structure; lexers break text into tokens using regular expressions; parser generators like PLY automate creating parsers from context-free grammars; shift-reduce conflicts can occur if grammar rules have overlapping tokens at the start.
Automata Theory
This document contains questions and answers related to finite automata theory. It begins with definitions of finite automata and their uses in text processing, compiler design, and hardware design. It then provides the formal definition of a deterministic finite automaton (DFA) and explains how a DFA processes strings using the transition function. Examples of DFAs are given for specific languages. Extended transition functions are described, along with examples of using them to represent languages. Specific languages are also given with their corresponding DFA diagrams and formal definitions.
Language for specifying lexical Analyzer
The document discusses the role and process of lexical analysis using LEX. LEX is a tool that generates a lexical analyzer from regular expression rules. A LEX source program consists of auxiliary definitions for tokens and translation rules that match regular expressions to actions. The lexical analyzer created by LEX reads input one character at a time and finds the longest matching prefix, executes the corresponding action, and places the token in a buffer.
Lecture 02 lexical analysis
The document discusses lexical analysis and how it relates to parsing in compilers. It introduces basic terminology like tokens, patterns, lexemes, and attributes. It describes how a lexical analyzer works by scanning input, identifying tokens, and sending tokens to a parser. Regular expressions are used to specify patterns for token recognition. Finite automata like nondeterministic and deterministic finite automata are constructed from regular expressions to recognize tokens.
Lexicalanalyzer
- Lexical analyzer reads source program character by character to produce tokens. It returns tokens to the parser one by one as requested.
- A token represents a set of strings defined by a pattern and has a type and attribute to uniquely identify a lexeme. Regular expressions are used to specify patterns for tokens.
- A finite automaton can be used as a lexical analyzer to recognize tokens. Non-deterministic finite automata (NFA) and deterministic finite automata (DFA) are commonly used, with DFA being more efficient for implementation. Regular expressions for tokens are first converted to NFA and then to DFA.
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.
Unit 1 question and answer
The document discusses the role of CLR (Common Language Runtime) in .NET framework. It explains that CLR converts programs to native code, handles exceptions, provides type safety, memory management, security, improved performance and is language and platform independent. It also discusses garbage collection and language features supported by CLR. The main components of CLR are CTS (Common Type System), JIT (Just-In-Time) compiler and CLS (Common Language Specification). CTS defines value and reference types while JIT compiles CIL to machine code. CLS provides language interoperability.
Compiler Construction | Lecture 3 | Syntactic Editor Services
The document discusses syntactic editor services for programming languages. It covers formatting specifications that define how abstract syntax trees are mapped to text using templates. It also discusses syntactic completion, which proposes valid completions in an editor by using the syntax definition. The lecture focuses on defining lexical and syntactic syntax for Tiger using SDF, and generating editor services like formatting and coloring from the syntax definitions.
Andy On Closures
Closures allow blocks of code to access variables from the enclosing scope even after the scope has closed. This allows closures to maintain state even when passed around or returned from functions. Closures originated in Lisp and are supported in many modern languages like Python, Ruby, and C#, providing benefits like elegant iteration, filtering, and caching of results. While objects can also be used to inject strategy or share state, closures provide a more concise syntax and avoid wrapper classes in many cases.
Basics of C programming
Introduction to C language. Compiled from different sources available online. Thanks to the original authors.
System Programming Unit IV
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.
Syntax directed translation
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.
Lecture 3 RE NFA DFA
This document discusses lexical analysis in compilers. It begins with an outline of the topics to be covered, including lexical analysis, regular expressions, finite state automata, and the process of converting regular expressions to deterministic finite automata (DFAs). It then provides more details on each phase of a compiler and the role of lexical analysis. Key aspects of lexical analysis like tokenizing source code and classifying tokens are explained. The document also covers implementation of regular expressions using non-deterministic finite automata (NFAs) and their conversion to equivalent DFAs using techniques like epsilon-closure and transition tables.
Syntax-Directed Translation into Three Address Code
The document discusses syntax-directed translation of code into three-address code. It defines semantic rules for generating three-address code for expressions, boolean expressions, and control flow statements. Temporary variables are generated for subexpressions and intermediate values. The semantic rules specify generating three-address code statements using temporary variables. Backpatching is also discussed as a technique to replace symbolic names in goto statements with actual addresses after code generation.
Chapter 6 Intermediate Code Generation
This document summarizes key topics in intermediate code generation including:
- Variants of syntax trees like DAGs to represent common subexpressions.
- Three-address code where each instruction has at most three operands.
- Type checking declarations and expressions during translation.
- Generating three-address code for control flow statements using techniques like backpatching to resolve symbolic labels.
Introduction to Python Basics
Python is an open source, general-purpose programming language that is easy to use and learn. It supports object-oriented programming and has extensive libraries for tasks like working with arrays and matrices. Python code is written in plain text and uses whitespace indentation to denote code blocks rather than curly braces. It supports common data types like integers, floats, and strings. Functions are defined using the def keyword and can take arguments. Conditionals, loops, exceptions, and other control flow structures allow Python code to respond dynamically to different situations.
Processing XML with Java
The document discusses different XML parsers in Java including DOM, SAX, and StAX. DOM represents the XML document as an in-memory tree which allows flexible processing but uses more memory. SAX is event-driven and reads the XML sequentially using less memory. StAX is similar to SAX but simplified and "pull"-based where the developer manually navigates elements. The document also covers using JAXP for XML processing independence and the key classes involved in DOM and StAX parsing.
ITU - MDD - Textural Languages and Grammars
This presentation describes the use and design of textural domain specific language - DSL. It has two basic purposes:
Introduce you to some of the more important design criteria in language design
Introduce you to BNF
This presentation is developed for MDD 2010 course at ITU, Denmark.
More Related Content
What's hot
Javascript
The JavaScript Programming Language document provides an overview of the JavaScript programming language, including its history, key concepts, values, operators, statements, and objects. It notes that JavaScript is a multi-paradigm scripting language that is misunderstood as only for web development. The document outlines JavaScript's core data types, objects, functions, and prototypal inheritance model.
Syntax analysis
The document discusses syntax analysis and parsing. It defines a syntax analyzer as creating the syntactic structure of a source program in the form of a parse tree. A syntax analyzer, also called a parser, checks if a program satisfies the rules of a context-free grammar and produces the parse tree if it does, or error messages otherwise. It describes top-down and bottom-up parsing methods and how parsers use grammars to analyze syntax.
Data types in c++
A very clear explanation of Data Types in C++ with an example using small programs. Memory allocation of data types also covered.
Glimpses of C++0x
This is Work-In-Progress. Developing a series of lectures on C++0x. This will augment my presentations on C++ and Design Pattern. First trial run was done at Interra, Noida in 2009
LVEE 2014: Text parsing with Python and PLY
This document summarizes text parsing with Python and PLY. It discusses formal languages and grammars, lexers and tokens, parser generators like PLY Lex and PLY YACC. Key points include: formal grammars use production rules to define a language's structure; lexers break text into tokens using regular expressions; parser generators like PLY automate creating parsers from context-free grammars; shift-reduce conflicts can occur if grammar rules have overlapping tokens at the start.
Automata Theory
This document contains questions and answers related to finite automata theory. It begins with definitions of finite automata and their uses in text processing, compiler design, and hardware design. It then provides the formal definition of a deterministic finite automaton (DFA) and explains how a DFA processes strings using the transition function. Examples of DFAs are given for specific languages. Extended transition functions are described, along with examples of using them to represent languages. Specific languages are also given with their corresponding DFA diagrams and formal definitions.
Language for specifying lexical Analyzer
The document discusses the role and process of lexical analysis using LEX. LEX is a tool that generates a lexical analyzer from regular expression rules. A LEX source program consists of auxiliary definitions for tokens and translation rules that match regular expressions to actions. The lexical analyzer created by LEX reads input one character at a time and finds the longest matching prefix, executes the corresponding action, and places the token in a buffer.
Lecture 02 lexical analysis
The document discusses lexical analysis and how it relates to parsing in compilers. It introduces basic terminology like tokens, patterns, lexemes, and attributes. It describes how a lexical analyzer works by scanning input, identifying tokens, and sending tokens to a parser. Regular expressions are used to specify patterns for token recognition. Finite automata like nondeterministic and deterministic finite automata are constructed from regular expressions to recognize tokens.
Lexicalanalyzer
- Lexical analyzer reads source program character by character to produce tokens. It returns tokens to the parser one by one as requested.
- A token represents a set of strings defined by a pattern and has a type and attribute to uniquely identify a lexeme. Regular expressions are used to specify patterns for tokens.
- A finite automaton can be used as a lexical analyzer to recognize tokens. Non-deterministic finite automata (NFA) and deterministic finite automata (DFA) are commonly used, with DFA being more efficient for implementation. Regular expressions for tokens are first converted to NFA and then to DFA.
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.
Unit 1 question and answer
The document discusses the role of CLR (Common Language Runtime) in .NET framework. It explains that CLR converts programs to native code, handles exceptions, provides type safety, memory management, security, improved performance and is language and platform independent. It also discusses garbage collection and language features supported by CLR. The main components of CLR are CTS (Common Type System), JIT (Just-In-Time) compiler and CLS (Common Language Specification). CTS defines value and reference types while JIT compiles CIL to machine code. CLS provides language interoperability.
Compiler Construction | Lecture 3 | Syntactic Editor Services
The document discusses syntactic editor services for programming languages. It covers formatting specifications that define how abstract syntax trees are mapped to text using templates. It also discusses syntactic completion, which proposes valid completions in an editor by using the syntax definition. The lecture focuses on defining lexical and syntactic syntax for Tiger using SDF, and generating editor services like formatting and coloring from the syntax definitions.
Andy On Closures
Closures allow blocks of code to access variables from the enclosing scope even after the scope has closed. This allows closures to maintain state even when passed around or returned from functions. Closures originated in Lisp and are supported in many modern languages like Python, Ruby, and C#, providing benefits like elegant iteration, filtering, and caching of results. While objects can also be used to inject strategy or share state, closures provide a more concise syntax and avoid wrapper classes in many cases.
Basics of C programming
Introduction to C language. Compiled from different sources available online. Thanks to the original authors.
System Programming Unit IV
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.
Syntax directed translation
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.
Lecture 3 RE NFA DFA
This document discusses lexical analysis in compilers. It begins with an outline of the topics to be covered, including lexical analysis, regular expressions, finite state automata, and the process of converting regular expressions to deterministic finite automata (DFAs). It then provides more details on each phase of a compiler and the role of lexical analysis. Key aspects of lexical analysis like tokenizing source code and classifying tokens are explained. The document also covers implementation of regular expressions using non-deterministic finite automata (NFAs) and their conversion to equivalent DFAs using techniques like epsilon-closure and transition tables.
Syntax-Directed Translation into Three Address Code
The document discusses syntax-directed translation of code into three-address code. It defines semantic rules for generating three-address code for expressions, boolean expressions, and control flow statements. Temporary variables are generated for subexpressions and intermediate values. The semantic rules specify generating three-address code statements using temporary variables. Backpatching is also discussed as a technique to replace symbolic names in goto statements with actual addresses after code generation.
Chapter 6 Intermediate Code Generation
This document summarizes key topics in intermediate code generation including:
- Variants of syntax trees like DAGs to represent common subexpressions.
- Three-address code where each instruction has at most three operands.
- Type checking declarations and expressions during translation.
- Generating three-address code for control flow statements using techniques like backpatching to resolve symbolic labels.
Introduction to Python Basics
Python is an open source, general-purpose programming language that is easy to use and learn. It supports object-oriented programming and has extensive libraries for tasks like working with arrays and matrices. Python code is written in plain text and uses whitespace indentation to denote code blocks rather than curly braces. It supports common data types like integers, floats, and strings. Functions are defined using the def keyword and can take arguments. Conditionals, loops, exceptions, and other control flow structures allow Python code to respond dynamically to different situations.
What's hot (20)
Compiler Construction | Lecture 3 | Syntactic Editor Services
Compiler Construction | Lecture 3 | Syntactic Editor Services
Syntax-Directed Translation into Three Address Code
Syntax-Directed Translation into Three Address Code
Similar to Convention-Based Syntactic Descriptions
Processing XML with Java
The document discusses different XML parsers in Java including DOM, SAX, and StAX. DOM represents the XML document as an in-memory tree which allows flexible processing but uses more memory. SAX is event-driven and reads the XML sequentially using less memory. StAX is similar to SAX but simplified and "pull"-based where the developer manually navigates elements. The document also covers using JAXP for XML processing independence and the key classes involved in DOM and StAX parsing.
ITU - MDD - Textural Languages and Grammars
This presentation describes the use and design of textural domain specific language - DSL. It has two basic purposes:
Introduce you to some of the more important design criteria in language design
Introduce you to BNF
This presentation is developed for MDD 2010 course at ITU, Denmark.
7986-lect 7.pdf
This document discusses assembly language directives and mixed-mode programming. It provides examples of assembly directives like .byte, .word, .section that reserve data locations and section code. It also discusses using inline assembly in C/C++ programs and the rules for calling assembly routines from high-level languages.
Combinators, DSLs, HTML and F#
The document discusses combinator libraries and domain-specific languages (DSLs) in F#. It explains that combinator libraries allow defining DSLs that embed in a host language. It provides examples of using F# to define DSLs for expressions, HTML, and forms. The document also discusses how F# features like algebraic data types and quotations enable easily defining and compiling DSLs to other languages.
The Style of C++ 11
The document discusses the new features in C++11 including new language features such as rvalue references, decltype, lambdas, and auto; new library features such as smart pointers, regular expressions, and hash tables; and the status of support for C++11 in Visual Studio 2010 and 2012. It also discusses modern C++ style using features like lambdas, smart pointers, and move semantics.
Web technologies-course 07.pptx
This document contains a series of questions and answers about JavaScript and web development topics. It begins with definitions of key terms like URLs, HTTP and HTTPS protocols, IP addresses, front-end and back-end development, and HTML block and inline elements. It then discusses ways to include CSS in HTML pages and differences between IDs and classes. The document concludes with explanations of Sass/SCSS and Bootstrap frameworks.
Python scripting kick off
An introduction of Python language.
The presentation is intended to give a very basic overview of Python feature using an informal approach
Python Programming Basics for begginners
Python Basics. This presentation will give you a basic idea about python programming language. A good guide for the beginners to refer.
Coding standards for java
This document provides an introduction to coding standards for Java. It discusses why coding standards are important for consistency, readability, and maintainability. It outlines the key components of a Java source file and comments. It also covers naming conventions, formatting, and best practices for variables, methods, classes, and comments. Finally, it introduces static code analysis tools like PMD and AppPerfect that can analyze Java code and enforce coding standards and best practices.
Aspect-oriented programming in Perl
This document provides an overview of aspect-oriented programming (AOP) in Perl using the Aspect.pm module. It defines key AOP terminology like join points, pointcuts, advice, and aspects. It describes the features of Aspect.pm like creating pointcuts with strings, regexes, or code references to select subroutines, and writing before, after, and around advice. Examples show creating reusable aspects for logging, profiling, and enforcing design patterns.
DEFUN 2008 - Real World Haskell
This document provides an introduction and overview to the Haskell programming language. It discusses Haskell's core concepts like pure functions, immutable data, static typing, and lazy evaluation. It also covers common Haskell tools and libraries, how to write simple Haskell programs, and how to compile and run Haskell code. The document uses examples and interactive sessions to demonstrate Haskell syntax and show how various language features work.
python and perl
Python and Perl are both high-level programming languages. Python is an interpreted language with clear, readable syntax and intuitive object orientation. Perl is also an interpreted and dynamic language that supports both procedural and object-oriented programming and is best known for powerful text processing. Both languages have a long history and are widely used for web development, scientific computing, and other tasks.
Syntax analysis
The document discusses the syntax of programming languages, including terminology, syntactic elements, and formal methods for describing syntax such as grammars, parse trees, and syntax diagrams. Grammars provide formal definitions of programming language syntax through sets of rules defining valid constructs. Context-free grammars like Backus-Naur Form (BNF) are commonly used.
Syntax analysis
The document discusses the syntax of programming languages, including terminology, syntactic elements, and formal methods for describing syntax such as grammars, parse trees, and syntax diagrams. Grammars provide formal definitions of programming language syntax through sets of rules defining valid constructs. Context-free grammars like Backus-Naur Form (BNF) are commonly used.
An Annotation Framework for Statically-Typed Syntax Trees
This document presents an annotation framework for statically typed syntax trees that allows generating parsers and abstract syntax trees from annotated context-free grammars. Key contributions include a grammar-independent annotation approach, a definition of statically typed AST specifications, and a prototype parser generator. The framework uses annotations to specify the types of values nodes produce, supporting scalar, string, node reference, and list values. An example grammar for a simple language is annotated to demonstrate the approach. The prototype implementation generates scanners, parsers producing the specified ASTs, AST node classes, and visitor code from annotated grammars.
Lec 04 intro assembly
The document provides an introduction to assembly language programming including:
- The basic elements of assembly language such as instructions, directives, constants, identifiers, and comments.
- A flat memory program template that includes TITLE, MODEL, STACK, DATA, CODE, and other directives.
- An example program that adds and subtracts integers and calls a procedure to display registers.
- An overview of the assemble-link-debug cycle used to develop assembly language programs.
Introduction to PHP
This document provides an introduction to PHP, including:
- What scripting languages and PHP are, and how PHP works as a server-side scripting language
- The history and origins of PHP
- How to set up a PHP development environment using XAMPP
- PHP programming fundamentals like syntax, operators, and control structures
- How to handle forms and files in PHP
- How to connect to and manipulate databases like MySQL from PHP
- Several tasks as examples of working with forms, files, and databases in PHP
Designing A Syntax Based Retrieval System03
The document proposes a syntax-based text retrieval system to support grammatical querying of tagged corpora for language learners and teachers. It describes building an index of part-of-speech tagged n-grams from a corpus, with a filter to select discriminative index terms. A regular expression query is rewritten and its positions in the index are used to find candidate matching text units efficiently. An evaluation compares the proposed index to a complete index in terms of size and query performance.
Generating parsers using Ragel and Lemon
The document discusses using Ragel and Lemon to generate parsers. It provides an overview of lexical analysis and syntax analysis in parsing. Ragel is introduced as a state machine generator that can be used to implement a lexer. A Ragel example tokenizes mathematical expressions. Lemon is a parser generator that outputs code to implement a parser based on a defined grammar. A Lemon example parses mathematical expressions. Finally, the document shows how to combine a Ragel lexer and Lemon parser to build a calculator application that can evaluate expressions.
Gude for C++11 in Apache Traffic Server
The document provides suggestions for using various new C++11 language features in ATS coding, focusing on features that are most useful. It discusses nullptr, auto, range-based for loops, delegating constructors, prohibiting/defaulting methods, member initialization, override, explicit conversion operators, std::unique_ptr, lambdas, std::function, constexpr, and provides code examples for many of these features. The overall aim is to take advantage of new language features to improve ATS code without overusing them in a way that makes the code harder to understand.
Similar to Convention-Based Syntactic Descriptions (20)
An Annotation Framework for Statically-Typed Syntax Trees
An Annotation Framework for Statically-Typed Syntax Trees
More from Ray Toal
Git workshop
This document provides an introduction to Git and covers:
- An overview of the basic Git commands that will be covered in the introductory workshop
- What Git is and how it differs from other version control systems
- Watching a video about Git branching
- Learning Git through hands-on examples of configuring Git, creating repositories and projects, making commits, branching and merging, resolving conflicts, and working with remotes and pushing changes to GitHub.
Learning and Modern Programming Languages
A brief look at learnability of a few modern programming languages, drawing a lot from Bret Victor's Learnable Programming.
Java best practices
This document provides an overview of best practices for writing Java code. It discusses topics like immutability, using libraries like Guava and Joda-Time, avoiding nulls, closing resources properly, using prepared statements to prevent SQL injection, and many other practices. The document emphasizes writing code that is readable, maintainable, efficient and avoids common pitfalls. It also provides resources for tools that can analyze code and help identify areas that don't follow best practices.
unittest in 5 minutes
This document discusses unit testing in Python. It provides an example of writing a test-driven function that interleaves two lists. The steps shown are:
1. Write test cases for the interleave function before writing the code. This tests various input/output cases.
2. Create a stub interleave function that returns None to make the tests fail as expected.
3. Write the interleave code using itertools.izip_longest to zip the lists together.
4. Rerun the tests to ensure they now pass with the implemented function.
Economics of Open Source Software
This document discusses the economics of open source software. It explains that open source software is not just about sharing or giving things away for free, but is actually closely tied to capitalism. Open source software development spreads costs and risks across many contributors. Companies that adopt open source can benefit from lower costs and more customized software that is improved through peer review. The open source model is economically viable and may be applicable to other fields beyond just software.
Modeling Patterns for JavaScript Browser-Based Games
This document proposes JavaScript patterns for modeling browser-based game objects and types without using frameworks. It describes challenges for browser games and recent advances in JavaScript. Patterns are presented for modules, types, and inheritance using prototypes instead of classes. A root game object type and projectile subtype are implemented as examples. The patterns were applied in an HTML5 game and several JavaScript game engines are surveyed.
More from Ray Toal (6)
Modeling Patterns for JavaScript Browser-Based Games
Modeling Patterns for JavaScript Browser-Based Games
Recently uploaded
UiPath Test Automation using UiPath Test Suite series, part 6
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
Taking AI to the Next Level in Manufacturing.pdf
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
5th LF Energy Power Grid Model Meet-up Slides
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
20240607 QFM018 Elixir Reading List May 2024
Everything I found interesting about the Elixir programming ecosystem in May 2024
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on integration of Salesforce with Bonterra Impact Management.
Interested in deploying an integration with Salesforce for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
20240609 QFM020 Irresponsible AI Reading List May 2024
Everything I found interesting about the irresponsible use of machine intelligence in May 2024
Webinar: Designing a schema for a Data Warehouse
Are you new to data warehouses (DWH)? Do you need to check whether your data warehouse follows the best practices for a good design? In both cases, this webinar is for you.
A data warehouse is a central relational database that contains all measurements about a business or an organisation. This data comes from a variety of heterogeneous data sources, which includes databases of any type that back the applications used by the company, data files exported by some applications, or APIs provided by internal or external services.
But designing a data warehouse correctly is a hard task, which requires gathering information about the business processes that need to be analysed in the first place. These processes must be translated into so-called star schemas, which means, denormalised databases where each table represents a dimension or facts.
We will discuss these topics:
- How to gather information about a business;
- Understanding dictionaries and how to identify business entities;
- Dimensions and facts;
- Setting a table granularity;
- Types of facts;
- Types of dimensions;
- Snowflakes and how to avoid them;
- Expanding existing dimensions and facts.
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
ここ3000字までしか入らないけどタイトルの方がたくさん文字入ると思います。
Artificial Intelligence for XMLDevelopment
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Recently uploaded (20)
UiPath Test Automation using UiPath Test Suite series, part 6
UiPath Test Automation using UiPath Test Suite series, part 6
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
20240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 2024
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
WeTestAthens: Postman's AI & Automation Techniques
WeTestAthens: Postman's AI & Automation Techniques
Convention-Based Syntactic Descriptions
- 1. Convention-Based Syntactic Descriptions Ray Toal Derek Smith Loyola Marymount University CSIE 2009, Los Angeles 2009-04-02
- 5. Approach
- 6. Conventions
- 7. Summary
- 8. Future Work
- 11. ... with some regex notation and custom extensions
- 14. Idea: Try to adapt convention over configuration to reduce markup requirements!
- 16. Microsyntax Example For a little C-like language: LETTER -> <L> DIGIT -> <Nd> CHAR -> [ˆ<Cc>" | 'apos; [ˆ<Cc>] ID -> LETTER (LETTER | DIGIT | '_')* KEYWORD -> 'var' | 'fun' | 'read' | 'write' | 'while' | 'do' | 'end' NUMLIT -> DIGIT+ ('.' DIGIT+)? ([Ee] [+-]? DIGIT+)? STRLIT -> '"' CHAR* '"' SKIP -> <Zs> | #09 | #0A | #0D | '//' [ˆ#0A#0D]* [#0A#0D]
- 18. Rules must be non-recursive, and RHS can only use symbols from previous rules
- 24. Category: <L>, <Nd>, <C>, <Zl>
- 25. String: 'while', ';'
- 26. One-of: [aeiou], [0-9A-Fa-f], [<L><Nd>_]
- 29. e 1 | e 2 or
- 30. e? optional
- 31. e* zero or more
- 32. e+ one or more
- 33. e^n exactly n e's
- 34. (…) grouping
- 35. Macrosyntax Example PROGRAM => BLOCK BLOCK => (DEC ';')* (STMT ';')+ DEC => 'var' ID ('=' EXP)? | 'fun' ID '(' IDLIST? ')' '=' EXP STMT => ID '=' EXP | 'read' IDLIST | 'write' EXPLIST | 'while' EXP 'do' BLOCK 'end' IDLIST => ID (',' ID)* EXPLIST => EXP (',' EXP)* EXP => TERM ([+-] TERM)* TERM => FACTOR ([*/] FACTOR)* FACTOR => NUMLIT | STRLIT | ID | CALL | '(' EXP ')' CALL => ID '(' EXPLIST? ')'
- 37. Means that SKIP* can appear before and after any token
- 38. Maximal munch assumed for tokenization
- 39. No delimiters needed between rules
- 40. First rule is the start symbol
- 42. Tokens can be introduced here, too!
- 43. Abstract Syntax var y; fun half(x) = x / 2; while x - (5 * x) do write half(10.4), x + 2; read x; end; (Program (Block (Var y) (Fun half x (/ (Ref x) (Numlit 2))) (While (- (Ref x) (* (Numlit 5) (Ref x))) (Block (Write (Call half (Numlit 10.4)) (+ (Ref x)(Numlit 2))) (Read x)))))
- 46. Last expression encountered is the “value”
- 47. Some rules don't even need AST expressions
- 48. Can have variables which are implicitly list valued, with special syntax for reassignment
- 49. Abstract Syntax PROGRAM => b:BLOCK {Program b} BLOCK => (d:DEC ';')* (s:STMT ';')+ {Block d s} DEC => 'var' i:ID ('=' e:EXP)? {Var i e} | 'fun' i:ID '(' p:IDLIST? ')' '=' e:EXP {Fun i p e} IDLIST => i:ID (',' i:ID)* The value of IDLIST is not an AST node; it's just a list since the last thing evaluated was stored in i Value of d is a list of values from each DEC Value of PROGRAM is an AST node with root 'Program; We're purposely using the same variable twice
- 50. Abstract Syntax EXP => t1:TERM (o=[+-] t2=TERM t1={o t1 t2})* TERM => f1:FACTOR (o=[*/] f2=FACTOR f1={o f1 f2})* FACTOR => n:NUMLIT {Numlit n} | s:STRLIT {Strlit s} | i:ID {Ref i} | c:CALL | '(' e:EXP ')' Each time we iterate through the ([*/] FACTOR)* syntax element, the vaues of the variables o and f1 are reassigned. Here o refers to the Variable because it Is lowercase It's okay that some of the alternatives produce AST nodes and some do not
- 53. SKIP is just another rule
- 55. => implies SKIP* separators
- 56. AST variables lowercase; nodes capitalized
- 57. Value of abstract syntax object is value of last object encountered in L-R parse
- 59. C, JSON, other specifications on web (http://xlg.cs.lmu.edu/ssd/)
- 62. Added custom features to EBNF
- 63. Defined conventions to simplify the notation
- 64. Provided examples of use
- 68. Ultimate convention: AST nodes automatically generated according to syntax category