PEG is a replacement to CFG. It is more powerful and can be more precise. In this slide I give a short introduction to PEG, the concept behind a programming language. Finally I write a parser for our programming language simple.
Talk @ #fuzzconeurope2020
Paper: https://ieeexplore.ieee.org/document/9166552
(M. Böhme, C. Cadar, and A. Roychoudhury)
Disclaimer: Our perspective on the discussions. Mistakes are mine.
Hypervisors are becoming more and more widespread in embedded environments, from automotive to medical and avionics. Their use case is different from traditional server and desktop virtualization, and so are their requirements. This talk will explain why hypervisors are used in embedded, and the unique challenges posed by these environments to virtualization technologies.
Xen, a popular open source hypervisor, was born to virtualize x86 Linux systems for the data center. It is now the leading open source hypervisor for ARM embedded platforms. The presentation will show how the ARM port of Xen differs from its x86 counterpart. It will go through the fundamental design decisions that made Xen a good choice for ARM embedded virtualization. The talk will explain the implementation of key features such as device assignment and interrupt virtualization.
This document discusses debugging the ACPI subsystem in the Linux kernel. It provides an overview of the ACPI subsystem and components like ACPICA and the namespace. It describes how to enable ACPI debug logging via the acpi.debug_layer and acpi.debug_level kernel parameters. It also covers overriding ACPI definition blocks tables and tracing ACPI temperature as a debugging case study.
This document discusses four parallel searching algorithms: Alpha-Beta search, Jamboree search, Depth-First search, and PVS search. Alpha-Beta search prunes unpromising branches without missing better moves. Jamboree search parallelizes the testing of child nodes. Depth-First search recursively explores branches until reaching a dead end, then backtracks. PVS search splits the search tree across processors, backing up values in parallel at each level. However, load imbalance can occur if some branches are much larger than others.
Kernel Recipes 2015: Linux Kernel IO subsystem - How it works and how can I s...Anne Nicolas
Understanding how Linux kernel IO subsystem works is a key to analysis of a wide variety of issues occurring when running a Linux system. This talk is aimed at helping Linux users understand what is going on and how to get more insight into what is happening.
First we present an overview of Linux kernel block layer including different IO schedulers. We also talk about a new block multiqueue implementation that gets used for more and more devices.
After surveying the basic architecture we will be prepared to talk about tools to peek into it. We start with lightweight monitoring like iostat and continue with more heavy blktrace and variety of tools that are based on it. We demonstrate use of the tools on analysis of real world issues.
Jan Kara, SUSE
The features released between Java 11 and Java 17 have brought a greater opportunity for developers to improve application development productivity as well and code expressiveness and readability. In this deep-dive session, you will discover all the recent Project Amber features added to the Java language such as Records (including Records serialization), Pattern Matching for `instanceof`, switch expression, sealed classes, and hidden classes. The main goal of the Amber Project is to bring Pattern Matching to the Java platform, which will impact both the language and the JDK APsI. You will discover record patterns, array patterns, as well as deconstruction patterns, through constructors, factory methods, and deconstructors.
You can find the code shown here: https://github.com/JosePaumard/devoxx-uk-2021
Kotlin is a concise, safe, and statically typed programming language that compiles to JVM bytecode and JavaScript. It focuses on interoperability with Java and solves many Java pitfalls. Kotlin removes verbosity like semicolons and replaces "extends" and "implement" with a colon. Functions are defined with the "fun" keyword and return types follow. Properties are treated like fields. Kotlin avoids null references through null safety features like the safe call operator and non-null assertion operator. When expressions replace switch statements. Extension functions can extend existing classes without subclassing.
Chapter 4 discusses greedy algorithms and their application to several optimization problems. It covers the general greedy method, including the subset and ordering paradigms. Specific problems covered include the knapsack problem, job sequencing with deadlines, and minimum cost spanning trees. Algorithms provided to solve these problems greedily include Prim's and Kruskal's algorithms for minimum cost spanning trees. The chapter also discusses the optimality of greedy approaches for several problems through proofs.
The document discusses NP-complete problems and polynomial-time reductions between them. It summarizes several permutation and subset problems that are known to be NP-complete, including Hamiltonian path/cycle, vertex cover, and 3-SAT. It then describes polynomial-time algorithms for solving some of these problems exactly using a "decision box" that can determine in polynomial time whether an instance has a solution. For example, it presents an O(n) algorithm for finding a minimum vertex cover using a decision box to iteratively test subset sizes.
Troubleshooting Linux Kernel Modules And Device DriversSatpal Parmar
The document discusses various techniques for debugging Linux kernel modules and device drivers, including:
1) Using printk statements to output debug messages from kernel space.
2) Watching system calls with strace to debug interactions between user and kernel space.
3) Adding /proc file system entries and write functions to dynamically modify driver values at runtime.
4) Enabling source-level debugging with tools like kgdb to debug at the level of C source code.
De nos jours, de plus en plus d’entreprises adoptent Docker. Mais comment faire avec des dizaines, des centaines voire des milliers de conteneurs à gérer ? Google s’est posé ces questions et de ses forges une réponse est sortie : le projet Kubernetes. Venez marcher dans les pas du géant en découvrant Kubernetes dans son intimité. Vous apprendrez à déployer une application, la scaler, la mettre à jour en rolling update et l'isoler des environnements.
Avec Java 8, publier en 2014, Java a fait une révolution puisque aucune autre version n’aura apporté autant de nouveautés et d’avancées fonctionnelles permet une écriture du code grandement facilitée et des performances nettement améliorées.
Nginx uses an event-driven architecture with a master process that manages worker processes. It handles requests non-blockingly and efficiently using techniques like memory pooling, buffer chaining, and an event-driven model. Key parts of the architecture include phases and handlers for HTTP requests, virtual servers, locations, and filters. Nginx also supports mail proxying and module development.
The document provides an overview of functional programming in Java. It discusses functional programming concepts like higher-order functions and avoiding side effects. It gives examples of functional-style code in Java for filtering lists and transforming objects. It also discusses how functional programming can be used to implement customizable business logic by passing functions as parameters and looking up functions through a dependency injection container.
This document discusses PEG.js, a JavaScript parser generator. It begins with an agenda that includes understanding PEG.js, how to use it, and making a domain-specific language (DSL) and parser. The document then covers how parsers are generally made, what PEG.js is, trying out some simple PEG grammars, and making a DSL for conditional logic. Key points include that PEG.js uses Parsing Expression Grammar to easily generate parsers without needing a separate lexer, how to write grammars and generate parsers with PEG.js, and an example of developing a DSL and parser for conditional logic configuration files.
Столпы функционального программирования для адептов ООП, Николай МозговойSigma Software
This document provides an overview of functional programming concepts for object-oriented programmers. It discusses the fundamentals of FP including immutability, purity, first-class and higher-order functions, closures, and recursion. It provides examples of these concepts in languages like Lisp, F#, C#, and JavaScript. The document also compares OO and FP concepts and discusses derived FP concepts like partial application, lazy evaluation, and pattern matching.
Golang basics for Java developers - Part 1Robert Stern
This document provides an overview of Golang basics for Java developers. It covers Golang's history, features, syntax, data types, flow control, functions and interfaces, concurrency, and differences from Java. Key points include Golang being a compiled, statically typed language created at Google in 2007, its use of packages and imports, basic types like strings and integers, slices for dynamic arrays, maps for key-value pairs, functions with receivers, errors instead of exceptions, and goroutines for concurrency with channels.
These are the slides for the seminar to have a basic overview on the GO Language, By Alessandro Sanino.
They were used on a Lesson in University of Turin (Computer Science Department) 11-06-2018
This document provides an introduction to the C programming language. It discusses key concepts like functions, variables, data types, memory, scopes, expressions, operators, control flow with if/else statements and loops. It also explains how passing arguments by value means functions cannot directly modify their parameters, but passing addresses allows modifying variables in the calling scope. Overall it serves as a helpful primer on basic C syntax and programming concepts for newcomers to the language.
Python is a versatile, object-oriented programming language that can be used for web development, data analysis, and more. It has a simple syntax and is easy to read and learn. Key features include being interpreted, dynamically typed, supporting functional and object-oriented programming. Common data types include numbers, strings, lists, dictionaries, tuples, and files. Functions and classes can be defined to organize and reuse code. Regular expressions provide powerful string manipulation. Python has a large standard library and is used widely in areas like GUIs, web scripting, AI, and scientific computing.
This document summarizes Julien Pauli's presentation on performance considerations with PHP 7. The key points are:
1) PHP 7 introduced a new compiler based on an AST that performs optimizations like resolving static expressions and function calls at compile time.
2) PHP 7 also introduced optimizations for references, hashtables, strings and encapsed strings. References are copied less, hashtables use less memory, strings are interned and encapsed strings build strings more efficiently.
3) Future versions of PHP will continue optimizing the compiler and intoduce a JIT compiler for further performance improvements. PHP 8 will be released when these optimizations are ready.
The document discusses functional programming and pattern matching. It provides examples of using pattern matching in functional programming to:
1. Match on algebraic data types like lists to traverse and operate on data in a recursive manner. Pattern matching allows adding new operations easily by adding new patterns.
2. Use pattern matching in variable declarations to destructure data like tuples and case class objects.
3. Perform pattern matching on function parameters to selectively apply different logic based on the patterns, like filtering even numbers from a list. Everything can be treated as values and expressions in functional programming.
This document provides an overview of building a simple one-pass compiler to generate bytecode for the Java Virtual Machine (JVM). It discusses defining a programming language syntax, developing a parser, implementing syntax-directed translation to generate intermediate code targeting the JVM, and generating Java bytecode. The structure of the compiler includes a lexical analyzer, syntax-directed translator, and code generator to produce JVM bytecode from a grammar and language definition.
This document summarizes new syntactic features introduced in recent versions of C#, including C# 6.0, 7.0, and 7.1. It provides examples of properties with auto-properties and initializers, lambda expressions used in properties and methods, inline variables, null expressions with null-coalescing and null-conditional operators, throw expressions, local functions, value tuples, and pattern matching. It also briefly mentions features planned for future versions like C# 7.2, 8, and beyond such as read-only references, nullable reference types, and default interface methods.
Conférence des Geeks Anonymes sur " le langage Go ", par Thomas Hayen le 23 septembre 2020.
Cette conférence est disponible en vidéo sur Youtube : https://youtu.be/AlGGneVGTJk
What can be done with Java, but should better be done with Erlang (@pavlobaron)Pavlo Baron
Erlang excels at building distributed, fault-tolerant, concurrent applications due to its lightweight process model and built-in support for distribution. However, Java is more full-featured and is generally a better choice for applications that require more traditional object-oriented capabilities or need to interface with existing Java libraries and frameworks. Both languages have their appropriate uses depending on the requirements of the specific application being developed.
Kotlin is a concise, safe, and statically typed programming language that compiles to JVM bytecode and JavaScript. It focuses on interoperability with Java and solves many Java pitfalls. Kotlin removes verbosity like semicolons and replaces "extends" and "implement" with a colon. Functions are defined with the "fun" keyword and return types follow. Properties are treated like fields. Kotlin avoids null references through null safety features like the safe call operator and non-null assertion operator. When expressions replace switch statements. Extension functions can extend existing classes without subclassing.
Chapter 4 discusses greedy algorithms and their application to several optimization problems. It covers the general greedy method, including the subset and ordering paradigms. Specific problems covered include the knapsack problem, job sequencing with deadlines, and minimum cost spanning trees. Algorithms provided to solve these problems greedily include Prim's and Kruskal's algorithms for minimum cost spanning trees. The chapter also discusses the optimality of greedy approaches for several problems through proofs.
The document discusses NP-complete problems and polynomial-time reductions between them. It summarizes several permutation and subset problems that are known to be NP-complete, including Hamiltonian path/cycle, vertex cover, and 3-SAT. It then describes polynomial-time algorithms for solving some of these problems exactly using a "decision box" that can determine in polynomial time whether an instance has a solution. For example, it presents an O(n) algorithm for finding a minimum vertex cover using a decision box to iteratively test subset sizes.
Troubleshooting Linux Kernel Modules And Device DriversSatpal Parmar
The document discusses various techniques for debugging Linux kernel modules and device drivers, including:
1) Using printk statements to output debug messages from kernel space.
2) Watching system calls with strace to debug interactions between user and kernel space.
3) Adding /proc file system entries and write functions to dynamically modify driver values at runtime.
4) Enabling source-level debugging with tools like kgdb to debug at the level of C source code.
De nos jours, de plus en plus d’entreprises adoptent Docker. Mais comment faire avec des dizaines, des centaines voire des milliers de conteneurs à gérer ? Google s’est posé ces questions et de ses forges une réponse est sortie : le projet Kubernetes. Venez marcher dans les pas du géant en découvrant Kubernetes dans son intimité. Vous apprendrez à déployer une application, la scaler, la mettre à jour en rolling update et l'isoler des environnements.
Avec Java 8, publier en 2014, Java a fait une révolution puisque aucune autre version n’aura apporté autant de nouveautés et d’avancées fonctionnelles permet une écriture du code grandement facilitée et des performances nettement améliorées.
Nginx uses an event-driven architecture with a master process that manages worker processes. It handles requests non-blockingly and efficiently using techniques like memory pooling, buffer chaining, and an event-driven model. Key parts of the architecture include phases and handlers for HTTP requests, virtual servers, locations, and filters. Nginx also supports mail proxying and module development.
The document provides an overview of functional programming in Java. It discusses functional programming concepts like higher-order functions and avoiding side effects. It gives examples of functional-style code in Java for filtering lists and transforming objects. It also discusses how functional programming can be used to implement customizable business logic by passing functions as parameters and looking up functions through a dependency injection container.
This document discusses PEG.js, a JavaScript parser generator. It begins with an agenda that includes understanding PEG.js, how to use it, and making a domain-specific language (DSL) and parser. The document then covers how parsers are generally made, what PEG.js is, trying out some simple PEG grammars, and making a DSL for conditional logic. Key points include that PEG.js uses Parsing Expression Grammar to easily generate parsers without needing a separate lexer, how to write grammars and generate parsers with PEG.js, and an example of developing a DSL and parser for conditional logic configuration files.
Столпы функционального программирования для адептов ООП, Николай МозговойSigma Software
This document provides an overview of functional programming concepts for object-oriented programmers. It discusses the fundamentals of FP including immutability, purity, first-class and higher-order functions, closures, and recursion. It provides examples of these concepts in languages like Lisp, F#, C#, and JavaScript. The document also compares OO and FP concepts and discusses derived FP concepts like partial application, lazy evaluation, and pattern matching.
Golang basics for Java developers - Part 1Robert Stern
This document provides an overview of Golang basics for Java developers. It covers Golang's history, features, syntax, data types, flow control, functions and interfaces, concurrency, and differences from Java. Key points include Golang being a compiled, statically typed language created at Google in 2007, its use of packages and imports, basic types like strings and integers, slices for dynamic arrays, maps for key-value pairs, functions with receivers, errors instead of exceptions, and goroutines for concurrency with channels.
These are the slides for the seminar to have a basic overview on the GO Language, By Alessandro Sanino.
They were used on a Lesson in University of Turin (Computer Science Department) 11-06-2018
This document provides an introduction to the C programming language. It discusses key concepts like functions, variables, data types, memory, scopes, expressions, operators, control flow with if/else statements and loops. It also explains how passing arguments by value means functions cannot directly modify their parameters, but passing addresses allows modifying variables in the calling scope. Overall it serves as a helpful primer on basic C syntax and programming concepts for newcomers to the language.
Python is a versatile, object-oriented programming language that can be used for web development, data analysis, and more. It has a simple syntax and is easy to read and learn. Key features include being interpreted, dynamically typed, supporting functional and object-oriented programming. Common data types include numbers, strings, lists, dictionaries, tuples, and files. Functions and classes can be defined to organize and reuse code. Regular expressions provide powerful string manipulation. Python has a large standard library and is used widely in areas like GUIs, web scripting, AI, and scientific computing.
This document summarizes Julien Pauli's presentation on performance considerations with PHP 7. The key points are:
1) PHP 7 introduced a new compiler based on an AST that performs optimizations like resolving static expressions and function calls at compile time.
2) PHP 7 also introduced optimizations for references, hashtables, strings and encapsed strings. References are copied less, hashtables use less memory, strings are interned and encapsed strings build strings more efficiently.
3) Future versions of PHP will continue optimizing the compiler and intoduce a JIT compiler for further performance improvements. PHP 8 will be released when these optimizations are ready.
The document discusses functional programming and pattern matching. It provides examples of using pattern matching in functional programming to:
1. Match on algebraic data types like lists to traverse and operate on data in a recursive manner. Pattern matching allows adding new operations easily by adding new patterns.
2. Use pattern matching in variable declarations to destructure data like tuples and case class objects.
3. Perform pattern matching on function parameters to selectively apply different logic based on the patterns, like filtering even numbers from a list. Everything can be treated as values and expressions in functional programming.
This document provides an overview of building a simple one-pass compiler to generate bytecode for the Java Virtual Machine (JVM). It discusses defining a programming language syntax, developing a parser, implementing syntax-directed translation to generate intermediate code targeting the JVM, and generating Java bytecode. The structure of the compiler includes a lexical analyzer, syntax-directed translator, and code generator to produce JVM bytecode from a grammar and language definition.
This document summarizes new syntactic features introduced in recent versions of C#, including C# 6.0, 7.0, and 7.1. It provides examples of properties with auto-properties and initializers, lambda expressions used in properties and methods, inline variables, null expressions with null-coalescing and null-conditional operators, throw expressions, local functions, value tuples, and pattern matching. It also briefly mentions features planned for future versions like C# 7.2, 8, and beyond such as read-only references, nullable reference types, and default interface methods.
Conférence des Geeks Anonymes sur " le langage Go ", par Thomas Hayen le 23 septembre 2020.
Cette conférence est disponible en vidéo sur Youtube : https://youtu.be/AlGGneVGTJk
What can be done with Java, but should better be done with Erlang (@pavlobaron)Pavlo Baron
Erlang excels at building distributed, fault-tolerant, concurrent applications due to its lightweight process model and built-in support for distribution. However, Java is more full-featured and is generally a better choice for applications that require more traditional object-oriented capabilities or need to interface with existing Java libraries and frameworks. Both languages have their appropriate uses depending on the requirements of the specific application being developed.
Python - Getting to the Essence - Points.com - Dave Parkpointstechgeeks
This document provides an introduction to Python and compares sorting lists in Java and Python. It demonstrates how to sort a list of tuples by different elements in Python using key functions with the built-in sorted() function. It also covers Python concepts like lists, dictionaries, list comprehensions, objects, built-in functions, and more.
Groovy is a dynamic language for the Java Virtual Machine that simplifies programming through features like closures, properties, and built-in support for lists, maps, ranges, and regular expressions. The latest version 1.5 adds support for Java 5 features like annotations and generics to leverage frameworks that use them. Groovy can be integrated into applications through mechanisms like JSR-223, Spring, and Groovy's own GroovyClassLoader to externalize business rules, provide extension points, and customize applications.
This document provides an overview of the Ruby programming language for Perl programmers. Ruby is an interpreted, object-oriented scripting language that is very similar to Perl but also introduces significant differences. Both languages are suitable for tasks like text processing and system administration scripts. Ruby places a stronger emphasis on object-oriented principles and is more dynamic than Perl.
The document provides an overview of the Ruby programming language for Perl programmers. Some key points:
- Ruby is an object-oriented scripting language that is interpreted, not compiled. It draws influences from Perl, Smalltalk, Lisp, and C.
- Ruby supports functional, aspect-oriented, and design-by-contract programming paradigms. It is well-suited for practices like extreme programming.
- Core concepts include classes, modules, blocks/iterators, exceptions, regular expressions and strings. Common data structures include arrays, hashes, ranges and more.
- Examples demonstrate basic syntax like variables, loops, conditions, classes and modules. Ruby emphasizes flexibility, dynamism and "
This document provides an overview of the Ruby programming language for Perl programmers. Ruby is a dynamic, reflective, object-oriented scripting language that is similar to Perl in many ways but also differs in its stronger object-oriented focus. The document discusses Ruby's syntax, core classes, object model, modules, blocks and iterators, and other features.
This document provides an overview of the Ruby programming language for Perl programmers. Ruby is an interpreted, object-oriented scripting language that is very similar to Perl in many ways, such as its syntax for regular expressions and special variables, but differs in its stronger emphasis on object-oriented principles and more dynamic features. The document discusses Ruby's history and influences, basic syntax, core programming concepts like classes and modules, and ways that Ruby code can be easily extended.
In this slide, I introduce how I implement RSA256 algorithm with verilog and verify with verilator.
The project use C++ to build the C-model and SystemC model.
To help build the model, we create a C++ class vint to simulate the behavior of Verilog. It supports normal Verilog operation with more strict rules.
The systemC model can be directly translated into Verilog, so the intention of Verilog design is quite clear and concise.
To simplify the simulation, we limit our module to be one input port and one output port. The port uses the valid/ready protocol to control the data flow, which can be modeled as sc_fifo in systemC.
With these abstraction, we can easily implement unit test for all of our modules, and make sure they act as what we want.
----
Please access the source code at:
https://github.com/yodalee/rsa256
The slide introduce some of the Rust concept that are necessary to write a kernel. Including wrapping an CSRs operation, locking mutable static variable, memory allocator, and pointer in Rust.
Please visit the project github to see the source code of the rrxv6 projects:
https://github.com/yodalee/rrxv6
In this slide, I introduced how Gameboy works and how to build a Gameboy emulator using Rust programming language. Also, I introduce how to migrate the Rust emulator to Webassembly, so that we can run the emulator using browser.
Video of presentation of this slide:
https://www.youtube.com/watch?v=LqcEg3IVziQ
Make A Shoot ‘Em Up Game with Amethyst FrameworkYodalee
A brief introduction to Rust, Amethyst game framework, and rust/WebAssembly. Focus on the ECS concept in amethyst framework and how to build a simple game by it.
You can build an old-fashioned Nixie tube clock by yourself. In this slide I introduce all the challenges and how I overcome them. I also publish all my design on website easyEDA and Github, you can use the design freely if you want to build your own one.
This document provides an outline and introduction for the Nand2Tetris course, which teaches students to build a computer from basic logic gates up through an entire computer architecture. The outline covers building combinational logic circuits in part 1 and developing a virtual machine and compiler in part 2. Key concepts discussed include NAND gates, Boolean logic, ALU design, CPU implementation, assembly language, stack-based virtual machines, and high-level language compilers. Diagrams illustrate the course progression from basic gates to an entire computer system.
A brief introduction to OpenTelemetry, with a practical example of auto-instrumenting a Java web application with the Grafana stack (Loki, Grafana, Tempo, and Mimir).
From Chaos to Clarity - Designing (AI-Ready) APIs with APIOps CyclesMarjukka Niinioja
Teams delivering API are challenges with:
- Connecting APIs to business strategy
- Measuring API success (audit & lifecycle metrics)
- Partner/Ecosystem onboarding
- Consistent documentation, security, and publishing
🧠 The big takeaway?
Many teams can build APIs. But few connect them to value, visibility, and long-term improvement.
That’s why the APIOps Cycles method helps teams:
📍 Start where the pain is (one “metro station” at a time)
📈 Scale success across strategy, platform, and operations
🛠 Use collaborative canvases to get buy-in and visibility
Want to try it and learn more?
- Follow APIOps Cycles in LinkedIn
- Visit the www.apiopscycles.com site
- Subscribe to email list
-
Integrating Survey123 and R&H Data Using FMESafe Software
West Virginia Department of Transportation (WVDOT) actively engages in several field data collection initiatives using Collector and Survey 123. A critical component for effective asset management and enhanced analytical capabilities is the integration of Geographic Information System (GIS) data with Linear Referencing System (LRS) data. Currently, RouteID and Measures are not captured in Survey 123. However, we can bridge this gap through FME Flow automation. When a survey is submitted through Survey 123 for ArcGIS Portal (10.8.1), it triggers FME Flow automation. This process uses a customized workbench that interacts with a modified version of Esri's Geometry to Measure API. The result is a JSON response that includes RouteID and Measures, which are then applied to the feature service record.
Top 5 Task Management Software to Boost Productivity in 2025Orangescrum
In this blog, you’ll find a curated list of five powerful task management tools to watch in 2025. Each one is designed to help teams stay organized, improve collaboration, and consistently hit deadlines. We’ve included real-world use cases, key features, and data-driven insights to help you choose what fits your team best.
GDG Douglas - Google AI Agents: Your Next Intern?felipeceotto
Presentation done at the GDG Douglas event for June 2025.
A first look at Google's new Agent Development Kit.
Agent Development Kit is a new open-source framework from Google designed to simplify the full stack end-to-end development of agents and multi-agent systems.
Key AI Technologies Used by Indian Artificial Intelligence CompaniesMypcot Infotech
Indian tech firms are rapidly adopting advanced tools like machine learning, natural language processing, and computer vision to drive innovation. These key AI technologies enable smarter automation, data analysis, and decision-making. Leading developments are shaping the future of digital transformation among top artificial intelligence companies in India.
For more information please visit here https://www.mypcot.com/artificial-intelligence
Bonk coin airdrop_ Everything You Need to Know.pdfHerond Labs
The Bonk airdrop, one of the largest in Solana’s history, distributed 50% of its total supply to community members, significantly boosting its popularity and Solana’s network activity. Below is everything you need to know about the Bonk coin airdrop, including its history, eligibility, how to claim tokens, risks, and current status.
https://blog.herond.org/bonk-coin-airdrop/
Agentic Techniques in Retrieval-Augmented Generation with Azure AI SearchMaxim Salnikov
Discover how Agentic Retrieval in Azure AI Search takes Retrieval-Augmented Generation (RAG) to the next level by intelligently breaking down complex queries, leveraging full conversation history, and executing parallel searches through a new LLM-powered query planner. This session introduces a cutting-edge approach that delivers significantly more accurate, relevant, and grounded answers—unlocking new capabilities for building smarter, more responsive generative AI applications.
Traditional Retrieval-Augmented Generation (RAG) pipelines work well for simple queries—but when users ask complex, multi-part questions or refer to previous conversation history, they often fall short. That’s where Agentic Retrieval comes in: a game-changing advancement in Azure AI Search that brings LLM-powered reasoning directly into the retrieval layer.
This session unveils how agentic techniques elevate your RAG-based applications by introducing intelligent query planning, subquery decomposition, parallel execution, and result merging—all orchestrated by a new Knowledge Agent. You’ll learn how this approach significantly boosts relevance, groundedness, and answer quality, especially for sophisticated enterprise use cases.
Key takeaways:
- Understand the evolution from keyword and vector search to agentic query orchestration
- See how full conversation context improves retrieval accuracy
- Explore measurable improvements in answer relevance and completeness (up to 40% gains!)
- Get hands-on guidance on integrating Agentic Retrieval with Azure AI Foundry and SDKs
- Discover how to build scalable, AI-first applications powered by this new paradigm
Whether you're building intelligent copilots, enterprise Q&A bots, or AI-driven search solutions, this session will equip you with the tools and patterns to push beyond traditional RAG.
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➡ 🌍📱👉COPY & PASTE LINK👉👉👉 ➤ ➤➤ https://drfiles.net/
Wondershare PDFelement Professional is professional software that can edit PDF files. This digital tool can manipulate elements in PDF documents.
Revolutionize Your Insurance Workflow with Claims Management SoftwareInsurance Tech Services
Claims management software enhances efficiency, accuracy, and satisfaction by automating processes, reducing errors, and speeding up transparent claims handling—building trust and cutting costs. Explore More - https://www.damcogroup.com/insurance/claims-management-software
Integration Ignited Redefining Event-Driven Architecture at Wix - EventCentricNatan Silnitsky
At Wix, we revolutionized our platform by making integration events the backbone of our 4,000-microservice ecosystem. By abandoning traditional domain events for standardized Protobuf events through Kafka, we created a universal language powering our entire architecture.
We'll share how our "single-aggregate services" approach—where every CUD operation triggers semantic events—transformed scalability and extensibility, driving efficient event choreography, data lake ingestion, and search indexing.
We'll address our challenges: balancing consistency with modularity, managing event overhead, and solving consumer lag issues. Learn how event-based data prefetches dramatically improved performance while preserving the decoupling that makes our platform infinitely extensible.
Key Takeaways:
- How integration events enabled unprecedented scale and extensibility
- Practical strategies for event-based data prefetching that supercharge performance
- Solutions to common event-driven architecture challenges
- When to break conventional architectural rules for specific contexts
14 Years of Developing nCine - An Open Source 2D Game FrameworkAngelo Theodorou
A 14-year journey developing nCine, an open-source 2D game framework.
This talk covers its origins, the challenges of staying motivated over the long term, and the hurdles of open-sourcing a personal project while working in the game industry.
Along the way, it’s packed with juicy technical pills to whet the appetite of the most curious developers.
Have you upgraded your application from Qt 5 to Qt 6? If so, your QML modules might still be stuck in the old Qt 5 style—technically compatible, but far from optimal. Qt 6 introduces a modernized approach to QML modules that offers better integration with CMake, enhanced maintainability, and significant productivity gains.
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2. Outline
Who am I? Why I did this?
Introduction to PEG
Introduction to programming language
Write a parser in PEG
No demo QQ
2
3. About Me
葉闆, Yodalee <[email protected]>
Study EE in college, Microwave in graduate school,
now rookie engineer in Synopsys.
3
Github: yodalee Blogger: http://yodalee.blogspot.tw
4. Why Did I Do This
“Understanding Computation: From
Simple Machines to Impossible
Programs”
In the book, it implements a
programming language parser, regular
expression parser with Ruby Treetop,
which is a PEG parser.
I re-write all the code in Rust, so I did a
little research on PEG.
https://github.com/yodalee/computationbook
-rust
4
6. Parsing Expression Grammar, PEG
Bryan Ford, <Parsing Expression Grammars: A Recognition-
Based Syntactic Foundation>, 2004
A replacement to Chomsky language, by removing the
ambiguity in grammar.
The ambiguity is useful in modeling natural language, but not
in precise and unambiguous programming language.
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Language <- Subject Verb Noun
Subject <- He | Lisa …
Verb <- is | has | sees…
Noun <- student | a toy …
7. PEG Basic Rule
PEG in definition are very similar to CFG, composed
of rules.
Rule will either:
Match success: consume input.
Match fail: not consume input.
As predicate: only return success or fail, not consume input.
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8. PEG Basic Rule
Replace choice ‘|’ with
prioritized choice ‘/’.
Consider following:
CFG: A = “a” | “ab”
PEG: A = “a” / “ab”
PEG: A = a* a
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Operator
“” String Literal
[] Character Set
. Any Character
(e1 e2 ..) Grouping
e? e+ e* Optional Repetition
&e And predicate
!e Not predicate
e1 e2 Sequence
e1 / e2 Prioritized Choice
9. Some Example
NUMBER <- [1-9] [0-9]*
COMMENT <- “//” (!”n” .)* n
EXPRESSION <- TERM ([+-] TERM)*
TERM <- FACTOR ([*/] FACTOR)*
STAT_IF <-
“if” COND “then” STATEMENT “else” STATEMENT /
“if” COND “then” STATEMENT
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10. PEG is not CFG
PEG is equivalent to Top Down Programming Language
(TDPL)
Language anbncn is not context-free, however PEG can parse
it with And-predicate.
In CFG, A <- aAa | a match: odd number “a”
In PEG, A <- aAa / a match: 2n-1 “a”
It is an open problem that any CFG can be parsed by PEG
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A <- aAb / ε
B <- bBc / ε
S <- &(A !b) a* B
11. Using PEG
There are many library that supports PEG:
Rust: rust-peg, pest, nom-peg …
C++: PEGTL, Boost …
Ruby: kpeg, raabro, Treetop …
Python: pyPEG, parsimonious …
Haskell: Peggy …
…
So why Rust?
11
13. Simple Language
3 types of statements: assign, if else, while.
Support integer arithmetic.
Support pair, list, function with one argument.
Simple, but actually we can do some complex things, like
recursion, map.
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factorfun = function factor(x) {
if (x > 1) { x * factor ( x-1 ) } else { 1 }
}
result = factorfun(10); // 3628800
function last(l) {
if (isnothing(snd(l))) {
fst(l)
} else {
last(snd(l))
}
}
14. Abstract Syntax Tree
Use Rust enum to store a payload inside.
“Programming” like this:
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pub enum Node {
Number(i64),
Boolean(bool),
Add(Box<Node>, Box<Node>),
Subtract(Box<Node>, Box<Node>),
LT(Box<Node>, Box<Node>)
…
}
let n = Node::add(Node::number(3), Node::number(4))
Add
3 4
LT
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15. Abstract Syntax Tree
All the statement are Node:
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pub enum Node {
Variable ( String ),
Assign ( String, Box<Node>),
If ( Box<Node>, Box<Node>, Box<Node> ),
While ( Box<Node>, Box<Node> ),
…
}
16. Pair, List and Nothing
Node::pair(Node::number(3), Node::number(4))
List [3,4,5] = pair(3, pair(4, pair(5, nothing)))
Nothing special
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Pair
3 4
Pair
3 Pair
4 Pair
Nothing5
17. Environment and Machine
Environment stores a Hashmap<String, Box<Node>>, with
<add> and <get> interface.
A machine accepts an AST and an environment to evaluate
AST inside the machine.
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pub struct Environment {
pub vars: HashMap<String, Box<Node>>
}
pub struct Machine {
pub environment: Environment,
expression: Box<Node>
}
18. Evaluate the AST
Add evaluate function to all AST node using trait.
The result will be a new Node.
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fn evaluate(&self, env: &mut Environment) -> Box<Node>;
match *self {
Node::Add(ref l, ref r) => {
Node::number(l.evaluate(env).value() +
r.evaluate(env).value()) }
…
}
19. Evaluate the AST
How to evaluate While Node ( condition, body )?
Evaluate condition => evaluate body and self if true.
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x = 3;
while (x < 9) { x = x * 2; }
Evaluate x = 3
Evaluate while (x < 9) x = x * 2
Evaluate x = x * 2
Evaluate while (x < 9) x = x * 2
Evaluate x = x * 2
Evaluate while (x < 9) x = x * 2
20. Function
Function is also a type of Node. Upon evaluation, function is
wrapped into Closure with environment at that time.
Call is evaluated the function with closure’s environment.
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Node::Func(String, String, Box<Node>)
Node::Closure(Environment, Box<Node>)
fn evaluate(&self, env: &mut Environment) -> Box<Node> {
Node::Fun(ref name, ref arg, ref body) => {
Node::closure(env.clone(), Box::new(self.clone()))
}
}
21. Call a Function
fn evaluate(&self, env: &mut Environment) -> Box<Node> {
Node::Call(ref closure, ref arg) => {
match *closure {
Node::Closure(ref env, ref fun) => {
if let Node::Fun(funname, argname, body) = *fun.clone() {
let mut newenv = env.clone();
newenv.add(&funname, closure.evaluate(env));
newenv.add(&argname, arg.evaluate(env));
body.evaluate(&mut newenv);
} } } } }
21
22. Free Variable
Evaluate the free variables in a function to prevent copy whole
environment
Node::Variable
Node::Assign
Node::Function
22
function addx(x) { function addy(y) { x + y }}
-> no free variables
function addy(x) { x + y }
-> free variable y
23. Call a Function
if let Node::Fun(funname, argname, body) = *fun.clone() {
let mut newenv = new Environment {};
for var in free_vars(fun) {
newenv.add(var, env.get(var));
}
newenv.add(&funname, closure.evaluate(env));
newenv.add(&argname, arg.evaluate(env));
body.evaluate(&mut newenv);
}
23
24. What is a Language?
We make some concepts abstract, like a virtual machine.
Design a language is to design the abstraction.
Function “evaluate” implement the concept, of course we can
implement it as anything. Like return 42 on every evaluation.
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Concept Simple, virtual
machine
Real Machine
Number 3 Node::number(3) 0b11 in memory
+ Node::add(l, r) add r1 r2
Choice Node::if branch command
25. What is a Language?
Abstraction will bring some precision issue, like floating point.
We have no way to express concept of <infinite>.
We can create a language on geometry as below, which
representation for line is best?
Consider every pros and cons the abstraction will bring.
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Concept In Programming Language
Point (x: u32, y: u32)
Line
(Point, Point)
(Point, Slope)
(Point, Point, type{vertical, horizontal, angled})
Intersection Calculate intersection
27. The Pest Package
Rust Pest
https://github.com/pest-parser/pest
My simple language parser grammar at:
https://github.com/yodalee/simplelang
Parsing Flow
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Grammar Parser
Source
Code
Pest Pair
Structure
Simple AST
28. The Pest Package
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use pest::Parser;
#[derive(Parser)]
#[grammar = "simple.pest"]
struct SimpleParser;
let pairs = SimpleParser::parse(
Rule::simple, “<source code>")
A pair represents the parse result
from a rule.
Pair.as_rule() => the rule
Pair.as_span() => get match span
Pair.as_str() => matched text
Pair.into_inner()=> Sub-rules
30. Climb the Expression
Expression can be written as single Rule:
Expr = { Factor ~ (op_binary ~ Factor)* }
Pest provides a template, just defines:
Function build factor => create Factor Node
Function infix rules => create Operator Node
Operator precedence =>
vector of operator precedence and left/right association
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31. Challenges
Error message with syntax error.
How to deal with optional? Like C for loop
A more systematic way to deal with large language, like C.
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compound_statement <- block_list
block_list <- block_list block | ε
block <- declaration_list | statement_list
declaration_list <- declaration_list declaration | ε
statement_list <- statment_list statement | ε
// Wrong PEG
compound_statement <- block*
block <- declaration* ~ statement*
// Correct PEG
compound_statement <- block*
block <- (declaration | statement)+
33. Conclusion
PEG is a new, much powerful grammar than CFG. Fast and
convenient to create a small language parser.
The most important concept in programming language?
Abstraction
Is there best abstraction? NO. It is engineering.
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34. Reference
<Parsing Expression Grammars: A Recognition-Based
Syntactic Foundation>, Bryan Ford
<Understanding Computation: From Simple Machines to
Impossible Programs>
<Programming Language Part B> on Coursera, University of
Washington
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