The document discusses traits in object-oriented programming. Traits are similar to mixins and allow the aggregation of methods and properties. The document explains how traits work in various programming languages like Perl, Ruby, Java and describes operations like trait summation, aliasing and exclusion. Trait systems allow flexible composition of behaviors while avoiding problems of multiple inheritance.
WebGL brings hardware accelerated 3D to your browser. The code may be complex, but the possibilities are amazing. Given as a lecture in the fh ooe in Hagenberg, Austria in December 2011.
WebGL brings hardware accelerated 3D to your browser. The code may be complex, but the possibilities are amazing. Given as a lecture in the fh ooe in Hagenberg, Austria in December 2011.
Introduction to ad-3.4, an automatic differentiation library in Haskellnebuta
Haskellの自動微分ライブラリ Ad-3.4 の紹介(の試み) If you don't see 21 slides in this presentation, try this one (re-uploaded): http://www.slideshare.net/nebuta/130329-ad-by-ekmett
Part presentation, part debate about the future of the language while touching base on the current state of the industry with respect to ES6/ES2015, and the possibilities of using it today in web applications and frameworks, the different options, and the things to keep in mind. Additionally, we will do a walk-through on the new features included in ES7/ES2016 draft, and those that are being discussed for ES8/ES2017.
Introduction to ad-3.4, an automatic differentiation library in Haskellnebuta
Haskellの自動微分ライブラリ Ad-3.4 の紹介(の試み) If you don't see 21 slides in this presentation, try this one (re-uploaded): http://www.slideshare.net/nebuta/130329-ad-by-ekmett
Part presentation, part debate about the future of the language while touching base on the current state of the industry with respect to ES6/ES2015, and the possibilities of using it today in web applications and frameworks, the different options, and the things to keep in mind. Additionally, we will do a walk-through on the new features included in ES7/ES2016 draft, and those that are being discussed for ES8/ES2017.
Introduction to Lisp. A survey of lisp's history, current incarnations and advanced features such as list comprehensions, macros and domain-specific-language [DSL] support.
Slides from a tutorial I gave at ETech 2006. Notes to accompany these slides can be found here: http://simonwillison.net/static/2006/js-reintroduction-notes.html
This case study gives an inside look at optimization of the MongoDB Perl driver, including custom benchmarking tools, step-by-step changes and results that will surprise and amaze. If you ever needed to optimize some Perl and wondered how people go about it, this talk is for you.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
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.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
9. Moose::Role Trait
(provided)
✤
(required)
✤
( OK)
✤
package TaxRole;
TaxRole
use Moose::Role;
requires 'price';
comsumption_tax price
our $TAX_RATE = 0.05;
tax_inclusive_price
sub consumption_tax{
return shift->price * $TAX_RATE;
}
sub tax_inclusive_price{
my $self = shift;
return $self->price + $self->consumption_tax;
}
no Moose::Role;
10. Moose::Role Trait
Trait
✤
required
✤
Goods
package Goods;
use Moose;
price
has price => (
isa => 'Int',
TaxRole
is => 'ro',
required => 1,
comsumption_tax price
);
tax_inclusive_price
with 'TaxRole';
no Moose;
11. Trait
sum : t1 + t2
✤
alias : t[a→b]
✤
exclusion : t - a
✤
12. Trait (1) - sum
package TraitsA;
required + provided = provided
✤
use Moose::Role;
required + required = required
✤
with 'TraitsB';
provided + provided = required ( )
✤
no Moose::Role;
TraitA TraitB TraitA
+= a ⇒
a c d b a
b d c c d
13. sum : ...
(m, ⊥: ,⟙: ) m1 ⊔ ⟙ = ⟙
→ ✤
✤
⟘⊔⟙=⟙
✤
⟘ ⊔⟘=⟘
✤
⟙⊔⟙=⟙
✤
m1 ⊔ ⟘ = m1
✤
provided: ⊥ ⟙
✤
m1 ⊔ m1 = m1
✤
m1 ⊔ m2 = ⟙ required: - provided
✤ ✤
TraitA TraitB TraitA
+= a = m3, c = m4 ⇒
a = m1, b = m2 b = m2, c = m4
c = ⟘, d = ⟘ d=⟘ a = ⟙, d = ⟘
14. Trait (2) - alias
package AnotherTraits;
use Moose::Role;
→
✤
with 'TraitsA' => {
alias => {a => 'e'},
};
no Moose::Role;
TraitA TraitA
[e → a] ⇒
a c a c
b d b d
e
15. Trait (3) - exclusion
package AnotherTraits;
use Moose::Role;
−
✤
with 'TraitsA' => {
excludes => ['a'],
};
no Moose::Role;
TraitA TraitA
-= a ⇒
a c b c
b d d
16. Trait :
package TraitsA;
use Moose::Role;
TraitA
with 'TraitsB' => {
a b
alias => {b => 'e'},
excludes => ['c'], c
}; d
e
no Moose::Role;
TraitA TraitB
a d += ( b a [e → b] - c )
b c
c d
17. Trait :
package TraitsA;
use Moose::Role;
TraitA
with 'TraitsB' => {
a b
alias => {b => 'e'},
excludes => ['c'], c
}; d
e
no Moose::Role;
TraitA TraitB
+= ( b = e
a d a [e → b] - c )
=
b c
c d
18. Trait
✤
package Trait; package Class;
use Moose::Role; use Moose;
sub class_vs_trait{ print __PACKAGE__, quot;nquot;; } extends 'SuperClass'; with 'Trait';
sub super_vs_trait{ print __PACKAGE__, quot;nquot;; } sub class_vs_trait{ print __PACKAGE__, quot;nquot;; }
no Moose::Role; no Moose;
package SuperClass; package main;
use Moose; my $c = Class->new;
sub super_vs_trait{ print __PACKAGE__, quot;nquot;; } $c->class_vs_trait;
no Moose; $c->super_vs_trait;
20. package TraitA;
use Moose::Role; package Class;
sub vs{ print __PACKAGE__, quot;nquot; } use Moose;
no Moose::Role; with 'TraitA', 'TraitB';
no Moose;
package TraitB;
use Moose::Role; package main;
sub vs{ print __PACKAGE__, quot;nquot; } Class->new->vs;
no Moose::Role;