In this deck I describe twenty best practices for using external DSLs to develop software (also know as Model-Driven Development). The best practices are based on my personal experience, but they are also rated based on feedback I received from a number of colleagues to express the level of confidence experts have in the particular best practice.
The slides cover three main aspects: language definition, model processing as well as process and organizational issues. Examples include the importance of notations, viewpoints and partitioning, the role of constraints, model transformations and testing as well as some thoughts on documentation, reviews and project roles.
Putting twenty best practices into 5.000 words of course results in each best practice being quite brief. However, it also means each is highly condensed and to the point. I believe the slides remind developers of most of the critical aspects of using DSLs, and it can serve as a checklist when starting an MD* project.
Architecture DSLs are a useful tool to capture the cornerstones of platform or product line architectures. In addition, interesting analyses can be performed on the models, and much of the infrastructure and configuration code can be generated. On the flip side, these DSLs themselves must be architected consciously: while many architectural abstractions are specific to any given platform or product line, many other aspects are generic and hence can be reused for several architecture DSLs. In this talk I trace how my thinking on architecture modeling has changed over time, and how this is reflected in the architecture DSLs I have built (or helped to build), and how evolving tools have made these changes possible.
From Programming to Modeling And Back AgainMarkus Voelter
Is programming = modeling? Are there differences, conceptual and tool-wise? Should there be differences? What if we programmed the way we model? Or vice versa? In this slidedeck I explore this question and introduce interesting developments in the space of projectional editing and modern parser technology. This leads to the concept of modular programming languages and a new way of looking at programming. I will demonstrate the idea with tools that are available today, for example TMF Xtext, JetBrains MPS and Intentional’s Domain Workbench.
Fusing Modeling and Programming into Language-Oriented ProgrammingMarkus Voelter
Modeling in general is of course different from programming (think: climate models). However, when we consider the role of models in the context of “model-driven”, i.e., when they are used to automati- cally construct software, it is much less clear that modeling is different from programming. In this paper, I argue that the two are conceptually indistinguishable, even though in practice they traditionally emphasize different aspects of the (conceptually indistinguishable) common approach. The paper discusses and illustrates language-oriented programming, the approach to {modeling| programming} we have successfully used over the last 7 years to build a range of innovative systems in domains such as insurance, healthcare, tax, engineering and consumer electronics. It relies on domain-specific languages, modular language extension, mixed notations, and in particular, the Jetbrains MPS language workbench.
Envisioning the Future of Language WorkbenchesMarkus Voelter
Over the last couple of years, I have used MPS successfully to build interesting (modeling and programming) languages in a wide variety of domains, targeting both business users and engineers. I’ve used MPS because it is currently the most powerful language workbench, lots of things are good about iz, in particular, its support for a multitude of notations and language modularity. But it is also obvious that MPS is not going to be viable for the medium to long term future; the most obvious reason for this statement is that it is not web/cloud-based. In this keynote, I will quickly recap why and how we have been successful with MPS, and point out how language workbenches could look like in the future; I will outline challenges, opportunities and research problems. I hope to spawn discussions for the remainder of the workshop.
I delivered this presentation at the Eclipse Modeling Days in NYC and Toronto, Ca: http://wiki.eclipse.org/Eclipse_Modeling_Day in November 2009.
The slides are based on the ones Jan Koehnlein presented at the Eclipse Summit Europe 09.
Architecture DSLs are a useful tool to capture the cornerstones of platform or product line architectures. In addition, interesting analyses can be performed on the models, and much of the infrastructure and configuration code can be generated. On the flip side, these DSLs themselves must be architected consciously: while many architectural abstractions are specific to any given platform or product line, many other aspects are generic and hence can be reused for several architecture DSLs. In this talk I trace how my thinking on architecture modeling has changed over time, and how this is reflected in the architecture DSLs I have built (or helped to build), and how evolving tools have made these changes possible.
From Programming to Modeling And Back AgainMarkus Voelter
Is programming = modeling? Are there differences, conceptual and tool-wise? Should there be differences? What if we programmed the way we model? Or vice versa? In this slidedeck I explore this question and introduce interesting developments in the space of projectional editing and modern parser technology. This leads to the concept of modular programming languages and a new way of looking at programming. I will demonstrate the idea with tools that are available today, for example TMF Xtext, JetBrains MPS and Intentional’s Domain Workbench.
Fusing Modeling and Programming into Language-Oriented ProgrammingMarkus Voelter
Modeling in general is of course different from programming (think: climate models). However, when we consider the role of models in the context of “model-driven”, i.e., when they are used to automati- cally construct software, it is much less clear that modeling is different from programming. In this paper, I argue that the two are conceptually indistinguishable, even though in practice they traditionally emphasize different aspects of the (conceptually indistinguishable) common approach. The paper discusses and illustrates language-oriented programming, the approach to {modeling| programming} we have successfully used over the last 7 years to build a range of innovative systems in domains such as insurance, healthcare, tax, engineering and consumer electronics. It relies on domain-specific languages, modular language extension, mixed notations, and in particular, the Jetbrains MPS language workbench.
Envisioning the Future of Language WorkbenchesMarkus Voelter
Over the last couple of years, I have used MPS successfully to build interesting (modeling and programming) languages in a wide variety of domains, targeting both business users and engineers. I’ve used MPS because it is currently the most powerful language workbench, lots of things are good about iz, in particular, its support for a multitude of notations and language modularity. But it is also obvious that MPS is not going to be viable for the medium to long term future; the most obvious reason for this statement is that it is not web/cloud-based. In this keynote, I will quickly recap why and how we have been successful with MPS, and point out how language workbenches could look like in the future; I will outline challenges, opportunities and research problems. I hope to spawn discussions for the remainder of the workshop.
I delivered this presentation at the Eclipse Modeling Days in NYC and Toronto, Ca: http://wiki.eclipse.org/Eclipse_Modeling_Day in November 2009.
The slides are based on the ones Jan Koehnlein presented at the Eclipse Summit Europe 09.
Better problem solving through scripting: How to think through your #eprdctn ...BookNet Canada
This is a resource part of Kris Coppieters' Tech Forum presentation: https://youtu.be/3OW96zE6N2I
Do you find yourself repeating the same task over and over? Or feeling certain there is a way to automate a task but it's just outside of your skill set? Kris Coppieters from Rorohiko has built a career solving just those kinds of problems. Whether it's scripting a solution from within InDesign, or using AppleScript to finish off some markup, Kris can show you how to bring high-level thinking to quick and dirty tasks.
techforum.booknetcanada.ca
#TechForum #ebookcraft
XIth Statistics Chapter 2,Collection of Data . NGPA College www.ngpaeducation.com. C-7/188, Sector-7, Nr Rohini east metro Stn. Delhi-110085. For purchasing video classes Please Call 9599222549, 9810139214, 9810398903, 01127043600
Better problem solving through scripting: How to think through your #eprdctn ...BookNet Canada
This is a resource part of Kris Coppieters' Tech Forum presentation: https://youtu.be/3OW96zE6N2I
Do you find yourself repeating the same task over and over? Or feeling certain there is a way to automate a task but it's just outside of your skill set? Kris Coppieters from Rorohiko has built a career solving just those kinds of problems. Whether it's scripting a solution from within InDesign, or using AppleScript to finish off some markup, Kris can show you how to bring high-level thinking to quick and dirty tasks.
techforum.booknetcanada.ca
#TechForum #ebookcraft
XIth Statistics Chapter 2,Collection of Data . NGPA College www.ngpaeducation.com. C-7/188, Sector-7, Nr Rohini east metro Stn. Delhi-110085. For purchasing video classes Please Call 9599222549, 9810139214, 9810398903, 01127043600
XI English Chapter 1, Portrait of a Lady. NGPA College www.ngpaeducation.com. C-7/188, Sector-7, Nr Rohini east metro Stn. Delhi-110085. For purchasing video classes Please Call 9599222549, 9810139214, 9810398903, 01127043600
In 2001 Euroavia Toulouse organized a symposium on ground effect. We invited most of the Russian and German actors, and some experts from Holland, UK or France for a week of science around the subject of ekranoplans / flying boats. This was dedicated to students. A book was issued... and now that all copies have been sold for a while I am sharing this on LinkedIn for everyone.
Enjoy.
Stéphan AUBIN
EAGES Proceedings - G. Gazuit & Y. GoupilStephan Aubin
In 2001 Euroavia Toulouse organized a symposium on ground effect. We invited most of the Russian and German actors, and some experts from Holland, UK or France for a week of science around the subject of ekranoplans / flying boats. This was dedicated to students. A book was issued... and now that all copies have been sold for a while I am sharing this on LinkedIn for everyone.
Enjoy.
Stéphan AUBIN
Secure Software Distribution in an Adversarial WorldDiogo Mónica
Secure software distribution is a hard problem. The thousands of different software update systems in use today, most of which are vulnerable to a myriad of attacks that leave the end users potentially vulnerable to compromise, are a testament to this fact.
With the explosion in popularity of package managers and distributors such as RubyGems, PyPI and npm, more and more of our applications are dependent on small, reusable, modules, developed by thousands of different developers, and distributed by infrastructures outside of our control. Given that distributed systems are only as secure as their weakest link, it only takes compromising one of these modules to be able to compromise the entire infrastructure.
It is time for software developers and publishers to start operating under an attack model that considers the distribution infrastructure itself as being actively malicious, and to start following best practices concerning role responsibility separation, offline storage of signing keys, and routine rotation of signing keys.
Are you responsible for developing satellite on-board software? Are you the Dutch government and you have to efficiently implement the public benefits law? Are you a healthcare startup, developing companion apps that help patients through a treatment? Are you an insurance company struggling to create new, and evolve existing products quickly to keep up with the market? These are all examples of organisations who have built their own domain-specific programming language to streamline the development of applications that have a non-trivial algorithmic core. All have built their languages with Jetbrains MPS, an open source language development tool optimized for ecosystems of collaborating languages with mixed graphical, textual, tabular and mathematical notations. This talk has four parts. I start by motivating the need for DSLs based on real-world examples, including the ones above. I will then present a few high-level design practices that guide our language development work. Third, I will develop a simple language extension to give you a feel for how MPS works. And finally, I will point you to things you can read to get you started with your own language development practice.
KernelF is a functional language built on top of MPS. It is designed to be highly extensible and embeddable in order to support its use at the core of domain-specific languages, realising an approach we sometimes call Funclerative Programming. 'Funclerative' is of course a mash-up of 'functional' and 'declarative' and refers to the idea of using functional programming in the small, and declarative language constructs for the larger-scale, often domain-specific, structures in a program. We have used KernelF in a wide range of languages including health and medicine, insurance contract definition, security analysis, salary calculations, smart contracts and language-definition. In this keynote, I illustrate the evolution of KernelF over the last two years. I discuss requirements on the language, and how those drove design decisions. I showcase a couple of the DSLs we built on top of KernelF to explain how MPS was used to enable the necessary language modularity. I demonstrate how we have integrated the Z3 solver to verify some aspects of programs. I present the architecture we have used to use KernelF-based DSLs in safety-critical environments. I close the keynote with an outlook on how KernelF might evolve in the future, and point out a few challenges for which we don't yet have good solutions.
Cherryleaf’s Ellis Pratt will be speaking at Lavacon’s first European conference. This will be held on 5-8 June, at the Trinity College Conference Centre, Dublin. Ellis’ presentation will be on the 7th June 2016
Explanation of what DSLs are with slight shift towards MPS.
Slides from my talk at Deutsche Bank.
There is nothing particulary new in these slides, there are mostly based on Martin Fowler talks and book (http://www.martinfowler.com/dslwip/).
External or internal domain-specific languages (DSLs) or (fluent)
APIs? Whoever you are – a developer or a user of a DSL –
you usually have to choose side; you should not! What about
metamorphic DSLs that change their shape according to your
needs? Our 4-years journey of providing the "right" support
(in the domain of feature modeling), led us to develop an external
DSL, different shapes of an internal API, and maintain
all these languages. A key insight is that there is no one-size-fits-
all solution or no clear superiority of a solution compared
to another. On the contrary, we found that it does make sense
to continue the maintenance of an external and internal DSL.
Based on our experience and on an analysis of the DSL engineering
field, the vision that we foresee for the future of
software languages is their ability to be self-adaptable to the
most appropriate shape (including the corresponding integrated
development environment) according to a particular
usage or task. We call metamorphic DSL such a language,
able to change from one shape to another shape.
The talk has been presented at SPLASH conference in Portland (USA), Onward! Essays track.
Paper is here: https://hal.archives-ouvertes.fr/hal-01061576/fr
A rough sketch of a presentation I'm working on; still needs work, but the basic concepts are all there.
Note: this is based on my own experience of writing a language service; if you think I've gotten something wrong, please let me know (comment, or create an issue in the repository) - I'm always happy to learn :)
https://github.com/tintoy/how-does-intellisense-work
Developing software often requires using a number of tools and languages. In embedded software, for example, it is common to use C and its IDE, Matlab/Simulink, a number of custom XML files, a requirements management tool such as DOORS and possibly a UML tool and a variant management tool. The integration of such a zoo of tools is often a major source of (accidental) complexity in development projects.
Contrast that with the "good old days" when everything was text files and command line executables running on the unix shell. This approach had two important properties: the infrastructure was extremely generic (unix shell, pipes, text editors) and the actual contents were easily extensible and composable (new text file formats/languages and new command line tools); a productive environment for a given project or domain could easily be built from the generic infrastructure plus a few custom extensions.
In this talk I want to propose that creating (domain-specific) development environments based on language workbenches results in many of the same advantages that we all valued in the unix shell-world. A language workbench is an extremely generic infrastructure that is easily extensible with new languages. It is easy to create domain-specific development tools that can address different aspects of the system with suitable abstractions, but are nonetheless very well integrated in terms of semantics and tooling.
Spark NLP: State of the Art Natural Language Processing at ScaleDatabricks
Natural language processing is a key component in many data science systems that must understand or reason about text. Common use cases include question answering, summarization, sentiment analysis, natural language BI, language modeling, and disambiguation. Building such systems usually requires combining three types of software libraries: NLP annotation frameworks, machine learning frameworks, and deep learning frameworks. This talk introduces the NLP library for Apache Spark. Spark NLP natively extends the Spark ML pipeline API’s which enabling zero-copy, distributed, combined NLP & ML pipelines, which leverage all of Spark’s built-in optimizations. Benchmarks and design best practices for building NLP, ML and DL pipelines on Spark will be shared.
Smart Contracts sind in aller Munde. Auf Basis von Blockchains soll die Ausführung von Verträgen zwischen mehreren Parteien (die sich nicht zwangsläufig vertrauen müssen) automatisiert werden. Blockchains stellen sicher, dass die im Vertrag definierten Regeln auch zwangsläufig eingehalten werden. Allerdings ist es mit existierenden Sprachen (wie bspw. Solidity) nicht so einfach, Veträge so zu implementieren, dass alle beteiligten Parteien (insbesondere auch nicht-Programmierer) verstehen welche Regeln denn nun in dem Vertrag definiert sind. Solidity ist letztendlich eine General-Purpose Programmiersprache, die typischen Muster für Mehr-Parteien-Verträge werden nicht direkt unterstützt. In diesem Vortrag zeige ich anhand konkreter Code-Beispiele, wie man kollaborative Verträge so beschreiben kann, dass das Verhalten leichter verständlich und leichter auf Korrektheit prüfbar ist. Dabei kommen unter anderem Zustandsmaschinen, deklarative Entscheidungsstrategien und Mechanismen zur Vermeidung spieltheoretischer Angriffe zum Einsatz. Die Implementierung beruht auf KernelF, einer funktionalen Sprache die wir über die letzten Jahre entwickelt haben um als Basis für domänenspezifische Sprachen zum Einsatz zu kommen. Da die Sprache mittels Jetbrains MPS entwickelt ist, lässt sie sich modular erweitern. Die Abstraktionen für Smart Contracts sind ein Beispiel für solcheErweiterungen. Der Talk dient damit auch als Illustration der Mächtigkeit funktionaler Sprachen sowie für Sprachbau mittels MPS.
Using language workbenches and domain-specific languages for safety-critical ...Markus Voelter
Language workbenches support the efficient creation, integration, and use of domain-specific languages. Typically, they execute models by code generation to programming language code. This can lead to increased productivity and higher quality. However, in safety-/mission-critical environments, generated code may not be considered trustworthy, because of the lack of trust in the generation mechanisms. This makes it harder to justify the use of language workbenches in such an environment. In this paper, we demonstrate an approach to use such tools in critical environments. We argue that models created with domain-specific languages are easier to validate and that the additional risk resulting from the transformation to code can be mitigated by a suitably designed transformation and verification architecture. We validate the approach with an industrial case study from the healthcare domain. We also discuss the degree to which the approach is appropriate for critical software in space, automotive, and robotics systems.
In this talk I will present a number of issues that we run against in our work of building DSLs for and with customers, mostly on top of MPS. This is not an MPS wishlist, but rather the attempt at identifying general areas where tool support or even the conceptual approach are not yet as mature as for the basics of language engineering: syntax, type systems, generators and basic IDE support. An ideal outcome of this session would be the formation of groups of people who will work on some of these issues in the future. These issues include the construction of debuggers for various language paradigms, realtime incremental transformations of models, interactive guidance for end users (clippy for DSLs :-)), a practically-usable formalism for defining semantics from which interpreters and generators can be derived, as well as the more diffuse requirement for more “liveness” in DSLs of non-trivial complexity and model sizes.
Depending on the purpose of a language, its design will be completely different: the syntax may be textual, graphical, tabular, or a mix of those. It may be highly expressive, allowing users to define their own abstractions, or restricted, simplifying the language for non-programmer end users. The degree of formality may be different, depending on the domain for which the language is built and the assurances one must be able to make about the correctness of programs. Depending on performance requirements, a simple AST interpreter may be good enough for executing programs, or one may need an optimizing generator. I this talk, I revisit a number of languages we have built over the last five years. For each of them, I discuss the core design decisions as well as the drivers in the domain that led to those decisions. The talk includes languages for embedded software, insurance product definition, security analysis, health algorithms, engine control and system engineering. All of the languages discussed have been designed with and for industrial customers and have been implemented on the basis of the open source Jetbrains MPS language workbench.
Kürzlich ist es mal wieder passiert: jemand hat vertwittert, welche Thesen und Probleme im Rahmen eines akademischen Workshop zum Thema 'Model-Driven' diskutiert wurden. Darunter Perlen wie: Passen Agil + Modellierung zusammen? Alle Modellierungswerkzeuge sind schlecht! Modellieren kann man auch mit Papier und Bleistift. Gibt es Wege aus der Modellierungskrise? Modellierungssprachen müssen nicht grafisch sein. Codegenerierung ist nicht der einzige Zweck von Modellen. Diese Diskussionen machen mich wahnsinnig. Denn die (industrielle) Model-Driven Community hat alle diese Fragen schon beanwortet (Ja, Nein, Nein, Keine Krise!, Echt?, Genau!) Die obigen Behauptungen oben kommen in aller Regel aus uninformierten (nicht nur akademischen) Kreisen, die in ihrem Verständnis von Sprachen, Modellen und Werkzeugen irgendwann vor 10 oder 15 Jahren stehengeblieben sind. In diesem Vortrag hoffe ich, mit diesen Vorurteilen aufzuräumen. End of Rant! Aber ernsthaft. Was wir heute in diesem Umfeld tun ist nicht mit UML Tools + Konsorten zu vergleichen. Auf Basis der Vorurteile oben diskutiere ich ein modernes Verständnis von Modellen und Modellierungssprachen, illustriere anhand von Jetbrains MPS aktuelle Werkzeuge und illustriere den Nutzen des ganzen anhand konkreter Beispiele aus unserer industriellen Praxis. Der eine oder andere berechtigte kritische Punkt kommt dabei auch zur Sprache.
The future of DSLs - functions and formal methodsMarkus Voelter
I have used domain-specific languages to empower non-programmers in healthcare, finance, aerospace, automotive and public administration for years. My approach relies on growing the DSL from a functional programming core, combining the flexibility and power of an algorithmic language with domain-specific constructs that range from temporal data types, state machines and data models to polymorphic dispatch between versions of calculation rules. I rely on the open source MPS workbench to define the languages and their IDE. I am looking to incremental model transformations to desugar domain-specific constructs back to a minimal core language in realtime. That core language will have an interpreter for in-IDE execution and a compiler for deployment. The language will be integrated with formal methods to verify properties of programs, enabling advanced analyses for DSL users. In this talk, I will demo some existing DSLs, provide an illustration of how they are built, and demo prototypes of the future approach while discussing their integration with formal methods.
Over the last five years we have built mbeddr, a collection of integrated languages and language extensions built with the Jetbrains MPS language workbench. mbeddr consists of 81 languages, incl. IDE support, 34 of them C extensions. The mbeddr languages use a wide variety of notations – textual, tabular, symbolic and graphical – and the C extensions are modular; new extensions can be added without changing the existing implementation of C. mbeddr’s development has spanned roughly 15 person years so far, and the tool is used in practice and continues to be developed. This makes mbeddr a case study in language engineering of non-trivial size and complexity. In this keynote, I look back at mbeddr’s development to identify what worked well and what are still challenges in language engineering with a modern language workbench. I will address five areas: language modularity, notational freedom and projectional editing, mechanisms for managing complexity, performance and scalability issues and the consequences for the development process. I will close by highlighting a set of issues which need further research and engineering.
Generic Tools - Specific Languages (PhD Defense Slides)Markus Voelter
Generic Tools, Specific Languages (GTSL) is an approach for developing tools and applications in a way that supports easier and more meaningful adaptation to specific domains. To achieve this goal, GTSL generalizes programming language IDEs to domains traditionally not addressed by languages and IDEs. At its core, GTSL represents applications as documents/programs/models expressed with suitable languages. Application functionality is provided through an IDE that is aware of the languages and their semantics. The IDE provides editing support, and also directly integrates domain-specific analyses and execution services. Applications and their languages can be adapted to increasingly specific domains using language engineering; this includes developing incremental extensions to existing languages or creating additional, tightly integrated languages. Language workbenches act as the foundation on which such applications are built.
Traditionally, DSLs have been targeted at "specialized programmers" or at least at people with a strong technical background such as engineers, mathematicians or scientists. However, DSLs can also be very useful for people who work in fields that are less technical, and more on the business side of the universe.
In this session we discuss our experiences in building DSLs for business people, i.e. non-IT people who know their respective domain well. These people are not necessarily experienced in structured (or even formal) representation of their expert knowledge, and might not even be experts in computer usage.
Over the last few years, Markus, Jos & Bernd have gained some valuable experience into the kinds of domains, people, languages, and notations that make this approach feasible. It turns out that the requirements for DSLs and the tools used can be quite different for business users. The goal of this session is to present this experience and start a discussion about how to move the field forward.
The experiences are taken from Bernd's and Markus's work with Intentional and Achmea Insurance, Jos's work for an insurance company in Porto, and Markus's and Bernd's work on the requirements language in mbeddr.
Software development is a very dynamic discipline, it can be very hype-driven at times. Technologies change all the time. For years, the pattern movement has successfully aimed at capturing the essence of what’s going on in the software development field in order to make sure wheels are not invented over and over again. Some patterns are very specialized, some are quite fundamental (such as the GoF patterns).
However, what are really the fundamentals of software development? Quicksort? Scheme? UML? What would you like all your developers in the team to really understand, what would you like to be the guiding principles of a curriculum of software engineering?
In this pattern language, I try to capture these principles. I will illustrate them with quite different, but usually contemporary and relevant technology examples. Some of the principles are implemented in languages, others in technologies, some in processes.
Software Architecture is often either imprecise and hard to grasp or technology specific. What you really want is a succinct, precise, technology-independent and tool-processable description of an architecture. In this tutorial we illustrate how textual DSLs can be used to this end. The core idea is to actually develop an architecture language as you understand the architecture, formalizing the growing intuitive understanding into a formal language. This removes ambiguity from the discussion, requires answers to arising questions and results in a more consistent and (re-)usable architecture. The tutorial has three parts: we start with a role play where we showcase how an architecture DSL is developed as part of a discussion about a system's architecture. We actually build an example DSL in real time. In part two we look at some of the concepts, rationales and benefits of the approach, and briefly point to tools that can be used to build languages and associated tooling. The third part looks at how to use the approach for product lines: how to express variability in the architectural descriptions, and how to integrate the DSL with feature-modeling based variability management. The tutorial is for practitioners, by practitioners. It is guaranteed to contain only practice-oriented material.
Model-Driven Development in the context of Software Product LinesMarkus Voelter
Domain specific languages, together with code generation or interpreters (a.k.a. model-driven development), are becoming more and more important. Since there is a certain overhead involved in building languages and processors, this approach is especially useful in environments where a spe-cific set of languages and generators can be reused many times. Product lines are such an environment. Consequently, the use of domain specific languages (DSLs) for Software Product Line Engi-neering (SPLE) is becoming more relevant. However, exploiting DSLs in the context of product lines involves more than just defining and using languages. This tutorial explains the differences as well as commonalities between model-driven development (MDD) and SPLE and shows how the two approaches can be combined. In this tutorial we will first recap/introduce feature modeling and model-driven development. We then build a simple textual DSL and a code generator based on Eclipse openArchitectureWare (oAW). Based on this language we’ll discuss the kinds of variability expressible via DSLs versus those expressible via feature modeling, leading to a discussion about ways to combine the two. In the next demo slot we’ll do just that: we’ll annotate a model with feature dependencies. When generating code, the elements whose features are not selected will be removed, and hence no code will be generated. Finally we’ll discuss and demo the integration feature dependencies into code generators to con-figure the kind of code generated from the model.
This slideset covers trends in programming paradigms by illustrating concepts based on new, emerging languages in 2009/10.
see http://www.voelter.de/conferences/index.html for the full set of my presentations.
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
Welcome to the first live UiPath Community Day Dubai! Join us for this unique occasion to meet our local and global UiPath Community and leaders. You will get a full view of the MEA region's automation landscape and the AI Powered automation technology capabilities of UiPath. Also, hosted by our local partners Marc Ellis, you will enjoy a half-day packed with industry insights and automation peers networking.
📕 Curious on our agenda? Wait no more!
10:00 Welcome note - UiPath Community in Dubai
Lovely Sinha, UiPath Community Chapter Leader, UiPath MVPx3, Hyper-automation Consultant, First Abu Dhabi Bank
10:20 A UiPath cross-region MEA overview
Ashraf El Zarka, VP and Managing Director MEA, UiPath
10:35: Customer Success Journey
Deepthi Deepak, Head of Intelligent Automation CoE, First Abu Dhabi Bank
11:15 The UiPath approach to GenAI with our three principles: improve accuracy, supercharge productivity, and automate more
Boris Krumrey, Global VP, Automation Innovation, UiPath
12:15 To discover how Marc Ellis leverages tech-driven solutions in recruitment and managed services.
Brendan Lingam, Director of Sales and Business Development, Marc Ellis
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
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.
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.
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
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.
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/
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
23. Do you want users to build their own Limit Expressiveness abstractions with the language?
24. DSL is a compromise: … Domain Abstractions … Reuse, Modularization, … Limit Expressiveness … All Data for Generation … DSL Tool influences Viewpoints?
39. Text + Visualization … problem-specific … anwers specific questions … highlight specific aspects … several different Grapical vs. Textual visualizations
115. Teamwork Navigation Overviews Searching Quick-find Find-references Show usage Refactoring Debugging Code Completion Syntax Highlighting The Language is not ToolingMatters! enough!
116. The Language is not ToolingMatters! enough! Thisis also trueforthe Meta Developers!
141. Language Structure is not enough. Checks firstand separate Youneedconstraints. Boolean expressionsthatvalidate the model beyondstructure.
142. Model G Checks firstand separate … complex Constraints Code
143. Model Checks firstand separate G G‘ … complex … duplication Constraints Constraints Code Code‘
144. separate phase Model firstclasscitizens muchbetter. Constraints Checks firstand separate G G‘ check asmany aspossible. makeittight. Code Code‘
145. different constraints atdifferenttimes orfor Checks firstand separate different partitions ofthe model partition-local: editor, on-save global: batch, on-request
146. check early. Model moresemantics. Constraints bettermessages. T Model‘ Checks firstand separate T Model‘ G Code
147. Model Constraints 1 constraints 1 ok T implies Model‘ constraints 2 ok Checks firstand separate Constraints 2 implies T constraints 3 ok Model‘ Constraints 3 G Code
174. whenandhow do you and validate process Viewpoint-Aware Processing eachviewpoint?
175. whenandhow do you and validate process Viewpoint-Aware Processing eachviewpoint? Roles? Process?
176. Generate in phases: type developer implementmanualcode Viewpoint-Aware Processing deployment integrator run on targetsystem behaviour runtime interpretstatemachine
228. Better Testing Generator Example Models Code Don‘t Forget Testing Based On Binary Test Cases (hand written) Tests
229. Better Testing Generator Example Models Code Don‘t Forget Testing Based On Models and Language serve as meaningful „spec“ for what to test Binary Test Cases (hand written) Tests
234. TestingMetware Reference Model … maintaned! Don‘t Forget Testing … bymetaware Reference Test Cases developers Reference Constraints
235. This tests only the generators Generator Model Code Don‘t Forget Testing Tests Generator Test Code
236. This tests not the model: self fulfilling! Generator Model Code Don‘t Forget Testing Tests Generator Test Code
237. Separate test models and generated test code Model Generator Code Don‘t Forget Testing based on tests Test Model (Test Language) Generator Test Code
238. Separate test models and generate Mocks Model Generator Code Mocks Don‘t Forget Testing based on tests Generator Test Model (Test Language) Generator Test Code
239. Auto-Derived Test Models work sometimes. Model Generator Code Don‘t Forget Testing automatically derived tests Test Model (Test Language) Generator Test Code
273. Language Designer … works w/ domain expert abstractions, notations Let‘em do whatthey‘regoodat … adds modularization, in- heritance, „abstract“, etc. … works w/ architect generators, interpreters … requires „metapeople“
274. App Developer … caresaboutappdomain … uses DSLs + metaware Let‘em do whatthey‘regoodat … isisolatedfrom technology, does not have to care (that much)
275. Flip side: Let‘em do whatthey‘regoodat Youactuallyneedpeople whoaregoodatthis!
297. How do youknow ifitworks foryoursituation? Forget Published Case Studies
298. How do youknow ifitworks foryoursituation? Forget Published Case Studies Do not judgeby published casestudies!
299. How do youknow ifitworks foryoursituation? Forget Published Case Studies Do not judgeby published casestudies! (yes, theyareworthreading but don‘tdecidebased on them)
300. Instead: Prototype! … meaningful Forget Published Case Studies … 4-8 personweeks … incremental … externalhelp?
307. Mixing Notations Language Modularity MetawareRefactoring Model/Code Refactoring Challenges Automatic Model Migration
308. Mixing Notations Language Modularity MetawareRefactoring Model/Code Refactoring Challenges Automatic Model Migration Model Debugging
309. Mixing Notations Language Modularity MetawareRefactoring Model/Code Refactoring Challenges Automatic Model Migration Model Debugging Interpretation -> Code Gen
310. Mixing Notations Language Modularity MetawareRefactoring Model/Code Refactoring Challenges Automatic Model Migration Model Debugging Interpretation -> Code Gen Cartridges