We introduce Federated Learning for Optimizing Resource Allocation (FLORA), an extension to the CINCO de Bio (CdB)1platform for health analysis workflows. FLORA uses Federated Learning (FL) to optimize resource allocation for Service-Independent Building Blocks (SIBs) execution across multiple CdB deployments, predicting maximum memory usage while maintaining privacy. Preliminary results from a matrix multiplication experiment demonstrate the potential of machine learning models to predict peak memory usage of a SIB. We outline the FLORA architecture, discuss its implementation within CdB, and propose future work to validate and integrate the framework in real-world settings.

Train the trainer is a pedagogical model widely used across a range of disciplines and fields. Originating in non- governmental organisations, the model was developed in a bid to reduce costs associated with training while also increasing the capacity of staff to effectively disseminate knowledge within organisations. While its use is now widespread, there is little consensus in the literature regarding its efficacy. This paper describes a train-the-trainer programme that was designed to enhance early-career researchers’ ability to deliver training based on their research. The programme was delivered to a pilot group who then delivered training to external stakeholders on two occasions. The train-the-trainer programme was then evaluated from the perspectives of the trained early-career researchers along with the participants who subsequently took part in workshops delivered by this cohort. Results indicate that the programme was largely successful in improving the early-career researchers’ confidence with respect to training delivery, while also creating a positive learning experience for the participants. The paper concludes with a discussion around the future plans for the development of the train-the-trainer programme based on the results from this pilot implementation.

Critical skills, such as teamwork, project collaboration, and concept presentation, remain underdeveloped without structured university learning environments. These skills are essential for success in real-world projects and require a dedicated academic focus. The flipped classroom teaching method offers a solution by presenting students with specific challenges and asking them to solve the problem. We implemented a customized flipped teaching method to teach data structures and algorithms in the Immersive Software Engineering program at the University of Limerick, fostering active learning and practical application of concepts. The results show that students can learn more effectively and in a shorter time compared to traditional methods.

This research investigates the use of diverse visual knowledge communication tools in the multidisciplinary training produced in the BC4ECO project. During this project, teaching and learning content was developed to enable postgraduate learners to utilise blockchain and Distributed Ledger Technology (DLT) to solve complex, real-world problems related to environmental sustainability. We examine how visual modelling techniques enhance comprehension across disciplines and facilitate interdisciplinary and transdisciplinary collaboration, particularly for learners who may not have prior programming or computer science knowledge. Findings suggest that using these tools leads to enhanced collaboration between computer scientists and non-computer scientists and aids in the facilitation of joint problem solving between seemingly disparate disciplines. Additionally, the study highlights how the use of tools for established software engineering modelling, like Visual Paradigm for UML, bridges the gap between theoretical knowledge and practical implementation, strengthening problem solving skills and improving software development education.

In a world of constant disruption, effective digital transformation requires strategic alignment and a holistic approach. However, most initiatives fail due to fragmented execution and narrow, technology-first approaches. This paper introduces ADAPT (Alignment-Driven Adaptation Process & Tool), an advanced visual knowledge management tool designed to facilitate systemic, purpose-driven digital transformation. ADAPT integrates systems thinking, strategic clarity, and organizational agility to enable leaders to align digital efforts with long-term value creation and adaptive capacity. As a flexible meta-approach, ADAPT derives customized adaptation processes to address unique organizational challenges. ADAPT allows to integrate diverse methods into coherent strategies to derive opportunity-driven, shared purposes and implementation plans, effectively orchestrating involved stakeholders. ADAPT is based on ten years of interdisciplinary research and practical insights. However, given the need for contextual validation, this paper invites further real-world testing and iterative refinement to optimize its practical impact and enhance its instantiation’s effectiveness for digital transformation.

Evidence shows that practice-based learning is beneficial to students’ understanding of threshold concepts in all disciplines. Teaching activities that draw on research data provide students with real-world examples of how they might apply this new knowledge, and this reinforces their understanding. While research data from projects in disciplines such as computer science or economics is widely published, it is only recently that humanities scholars, in particular historians, have started considering publishing their research data in digital format. Using a case study of a 5-year funded collaborative project between historians and computer scientists, this paper discusses how the research data was created and applied in a classroom context, providing students with a ’real-world’ experience of working as a historian. It shows how the project data developed from a basic transcription of historical records into a fully enriched open dataset that can be used by teachers from a range of disciplines including history, historical geography, demography, computer science and medicine/medical humanities. It concludes that lessons planned around such open research data comprise a valuable educational resource to teachers and students.

According to data from the US Bureau of Labor Statistics, the number of job postings for software engineers has steadily increased over the past few years and is expected to grow by 22% from 2019 to 2029. This paper presents the pedagogical experience within the new Immersive Software Engineering (ISE) program concerning mathematical foundations and data analytics topics. These topics were designed to cover essential mathematical concepts such as calculus, linear algebra, probability, and statistics and their integration within data analytic tools and techniques such as time-series forecasting, data cleaning, data visualization, and introduction to pattern recognition. In addition, hands-on projects and real-world applications were incorporated throughout the course to provide students with practical experience in these areas. We reflect on the first delivery of the ISE course, which provided students with a new innovative blended learning environment, and how it will be further developed towards Open Educational Resources (OER) components and refined to respond to the rapidly evolving needs of the software engineering industry.

Effective communication is crucial when working on complex or wicked problems in interdisciplinary, international teams. Developing a shared understanding of critical concepts and aligning knowledge, focus, and resources can be problematic when stakeholders speak different languages, span several disciplines and work within different national or industry-based norms. Using visual tools to represent critical concepts and their relations, and map out our strategic goals has greatly helped combat such issues. This paper recounts the use and impact of adopting visual tools within the transnational and interdisciplinary collaborative environment in the BC4ECO project's international consortium. The Miro Board and the canvas approach greatly helped represent, visualise, and thus concretise the structure and contents of our collaboration, which takes place within a 3 years ERASMUS+ framework that builds and delivers Summer School, MOOCS as well as teacher and multiplier events about harnessing the potential of Distributed Ledger Technologies (DLTs) for environmental sustainability. As the materials and MOOCS are expected to become Open Education Resources and have a wide impact, it is particularly crucial to get the contents as well as the pedagogy right, in spite of the team's differences in almost any dimension of background and culture.

In the pharmaceutical industry, problems like counterfeit drugs, including vaccines, and their supply chain management problems like transparency, immutability, and traceability exist. In the case of vaccines, it becomes more difficult to standardize and detect fake vaccines because the public has less awareness and knowledge about vaccines. Moreover, the increase in online pharmacies gives more opportunities for counterfeiting vaccines to enter the authentic supply chain management system. We present transparent, immutable and secure vaccine supply chain (TISVSchain), a framework based on blockchain to handle the issues of counterfeited vaccines and vaccine supply chain problems like transparency, immutability, and traceability. Our proposed framework can run both on the private and public blockchain. We have implemented the framework on public blockchain by using remix ide and the smart contracts designed by solidity language run on very low gas cost. We also carried out several experiments by changing the number of nodes and their block time to evaluate the performance of our framework in terms of transaction per second (TPS), gas cost, and propagation delay. Our proposed framework improves the security by using offline unique account addresses in blockchain-based frameworks and improves the overall efficiency of the framework by keeping the gas cost low, finding a way to decrease the number of lost blocks to keep low propagation delay, and keeping high TPS value. TISVSchain shows us promising results to improve vaccine supply chain management’s overall performance, security, and efficiency.

Census returns are a critical source of information for governments globally. They underpin a wide spectrum of public planning including health, housing, work and education. Historically, census forms have captured names, places, dates, age, occupation, family structure, and religion. In more recent times, sexual orientation and ethnicity, queries that can be intrusive to vulnerable communities, have been added to the criteria, and for such reasons data security is of paramount importance. Most governments restrict access to individual census returns, presenting the data in aggregate report format. The Irish government is particularly strict, enforcing a statutory closure period of 100 years. An exception was made for the Irish 1911 census which were digitised and released for free online consultation in 2009 [1]. They are an excellent source for genealogists and historians alike but exist as separate digital siloes. This project uses an eXtreme Model-Driven Development (XMDD) environment to create linkages between both datasets. It will discuss the development process of the CensusIrl application and the process used in developing the matching algorithm used. We will discuss the census records and the data cleansing process used in creating the initial proof of concept application. We detail the different approaches to the development life-cycle of the application and describe the different utilises used in the sanitation of data points in the records and the match-making process.

Death and Burial Data: Ireland 1864–1922 (DBDIrl), is a digital humanities project, which uses historical civil registration of death as its primary dataset. The overarching aim of this project is to provide enriched and clean historical Irish data for analysis, in a eXtreme Model-Driven Development (XMDD) fashion. This paper discusses how e-learning environments were used to enrich these partially indexed data in an online, hybrid and blended learning group instruction format over four years. It describes how the DBDIrl data entry application, called Historian Dime App (HDA), evolved over a number of iterations to create a more user friendly interface, in an interdisciplinary collaboration of historians and computer scientists enabled by the XMDD approach. It discusses how the development process of HDA benefitted successive cohorts of history students engaged in a curricular Practice-based learning (PBL) project that follows a transcribathon model as defined by the Folger Library11https://folgerpedia.folger.edu/Transcribathon, We adapted the model for postgraduate teaching and learning in the humanities and took a reflexive approach to student/user feedback to evolve the HDA over four versions. It resulted in enhanced features, higher rates of user satisfaction, and a more responsive data curation and storage mechanism. This effort achieved our original aim of obtaining clean and accurate outputs from the students' project work.

Abstract The increasing complexity delivered by the heterogeneity of the cyber-physical systems is being addressed and decoded by edge technologies, IoT development, robotics, digital twin engineering, and AI. Nevertheless, tackling the orchestration of these complex ecosystems has become a challenging problem. Specially the inherent entanglement of the different emerging technologies makes it hard to maintain and scale such ecosystems. In this context, the usage of model-driven engineering as a more abstract form of glue-code, replacing the boilerplate fashion, has improved the software development lifecycle, democratising the access to and use of the aforementioned technologies. In this paper, we present a practical use case in the context of Smart Manufacturing, where we use several platforms as providers of a high-level abstraction layer, as well as security measures, allowing a more efficient system construction and interoperability.

Abstract In the Internet of Things (IoT) era, devices and systems generate enormous amounts of real-time data, and demand real-time analytics in an uninterrupted manner. The typical solution, a cloud-centred architecture providing an analytics service, cannot guarantee real-time responsiveness because of unpredictable workloads and network congestion. Recently, edge computing has been proposed as a solution to reduce latency in critical systems. For computation processing and analytics on edge, the challenges include handling the heterogeneity of devices and data, and achieving processing on the edge in order to reduce the amount of data transmitted over the network. In this paper, we show how low-code, model-driven approaches benefit a Digital Platform for Edge analytics. The first solution uses EdgeX, an IIoT framework for supporting heterogeneous architectures with the eKuiper rule-based engine. The engine schedules fully automatically tasks that retrieve data from the Edge, as the infrastructure near the data is generated, allowing us to create a continuous flow of information. The second solution uses FiWARE, an IIoT framework used in industry, using IoT agents to accomplish a pipeline for edge analytics. In our architecture, based on the DIME LC/NC Integrated Modelling Environment, both integrations of EdgeX/eKuyper and FiWARE happen by adding an External Native DSL to this Digital Platform. The DSL comprises a family of reusable Service-Independent Building blocks (SIBs), which are the essential modelling entities and (service) execution capabilities in the architecture’s modelling layer. They provide users with capabilities to connect, control and organise devices and components, and develop custom workflows in a simple drag and drop manner.

This paper discusses the collaboration of higher education computer scientists, data scientists and historians to design and adapt a set of resources and digital assets that can be used by students and local communities to transcribe historical data. We show that an agile software design and development approach to co-creating such tools has great pedagogical merit both for the end users and the creators of the tools themselves. We note that effective interdisciplinary collaboration requires pooling resources and mutual respect for domain expertise. As part of the project took place during the SARs-Cov-2 pandemic, we also pivoted to a completely online environment. This means that we have a proven model for classroom, online and blended formats alike that we intend to use in the future also for "citizen scientist" events. In this way, the Open Education Resources can be used in a more accessible and inclusive way.

Automation systems involve a range of cyber-physical system components such as sensors, actuators, control equipment, machines, robots, AGVs, etc. Seamless interoperability among these entities is a significant challenge. A well-designed Industrial Internet of Things (IIoT) platform at the network edge can offer several services by acting as a transformation engine between these field devices and various enterprise applications. We consider the EdgeX Foundry platform as such an IIoT middleware, discuss how EdgeX can provide ready-to-use integration of IoT devices, and show how we connect it with a low-code XMDD coordination layer that interfaces with EdgeX microservices through a Native DSL mechanism. We consider this technology landscape from the point of view of a building automation system example that supports high reconfigurability and security. We show how to produce all the essential elements of a complex Web based application to control the considered building systems. We demonstrate various features of the application's data and process models, how DSLs play a role at various levels, and how to add security capabilities that go beyond the cross-layer concerns and mechanisms offered by EdgeX. To this end, we introduce a declarative policy layer to be implemented using the open source ADD-Lib in form of an additional DSL for Attribute Based Encryption, with the aim of further enriching the capabilities around the EdgeX platform.

Abstract In many industries, traditional automation systems (operating technology) such as PLCs are being replaced with modern, networked ICT-based systems as part of a drive towards the Industrial Internet of Things (IIoT). The intention behind this is to use more cost-effective, open platforms that also integrate better with an organisation’s information technology (IT) systems. In order to deal with heterogeneity in these systems, middleware platforms such as EdgeX Foundry, IoTivity, FI-WARE for Internet of Things (IoT) systems are under development that provide integration and try to overcome interoperability issues between devices of different standards. In this paper, we consider the EdgeX Foundry IIoT middleware platform as a transformation engine between field devices and enterprise applications. We also consider security as a critical element in this and discuss how to prevent or mitigate the possibility of several security risks. Here we address secure data access control by introducing a declarative policy layer implementable using Ciphertext-Policy Attribute-Based Encryption (CP-ABE). Finally, we tackle the interoperability challenge at the application layer by connecting EdgeX with DIME, a model-driven/low-code application development platform that provides methods and techniques for systematic integration based on layered Domain-Specific Languages (DSL). Here, EdgeX services are accessed through a Native DSL, and the application logic is designed in the DIME Language DSL, lifting middleware development/configuration to a DSL abstraction level. Through the use of DSLs, this approach covers the integration space domain by domain, technology by technology, and is thus highly generalizable and reusable. We validate our approach with an example IIoT use case in smart manufacturing.

Abstract With the heterogeneity of the industry 4.0 world, and more generally of the Cyberphysical Systems realm, the quest towards a platform approach to solve the interoperability problem is front and centre to any system and system-of-systems project. Traditional approaches cover individual aspects, like data exchange formats and published interfaces. They may adhere to some standard, however they hardly cover the production of the integration layer, which is implemented as bespoke glue code that is hard to produce and even harder to maintain. Therefore, the traditional integration approach often leads to poor code quality, further increasing the time and cost and reducing the agility, and a high reliance on the individual development skills. We are instead tackling the interoperability challenge by building a model driven/low-code Digital Thread platform that 1) systematizes the integration methodology, 2) provides methods and techniques for the individual integrations based on a layered Domain Specific Languages (DSL) approach, 3) through the DSLs it covers the integration space domain by domain, technology by technology, and is thus highly generalizable and reusable, 4) showcases a first collection of examples from the domains of robotics, IoT, data analytics, AI/ML and web applications, 5) brings cohesiveness to the aforementioned heterogeneous platform, and 6) is easier to understand and maintain, even by not specialized programmers. We showcase the power, versatility and the potential of the Digital Thread platform on four interoperability case studies: the generic extension to REST services, to robotics through the UR family of robots, to the integration of various external databases (for data integration) and to the provision of data analytics capabilities in R.

The project Death and Burial Data: Ireland 1864-1922 (DBDIrl) examines the relationship between historical death registration data and burial data to explore the history of power in Ireland from 1864 to 1922. Its core Big Data arises from historical records from a variety of heterogeneous sources, some aspects are pre-digitized and machine readable. A huge data set (over 4 million records in each source) and its slow manual enrichment (ca 7,000 records processed so far) pose issues of quality, scalability, and creates the need for a quality assurance technology that is accessible to non-programmers. An important goal for the researcher community is to produce a reusable, high-level quality assurance tool for the ingested data that is domain specific (historic data), highly portable across data sources, thus independent of storage technology.This paper outlines the step-wise design of the finer granular digital format, aimed for storage and digital archiving, and the design and test of two generations of the techniques, used in the first two data ingestion and cleaning phases.The first small scale phase was exploratory, based on metadata enrichment transcription to Excel, and conducted in parallel with the design of the final digital format and the discovery of all the domain-specific rules and constraints for the syntax and semantic validity of individual entries. Excel embedded quality checks or database-specific techniques are not adequate due to the technology independence requirement. This first phase produced a Java parser with an embedded data cleaning and evaluation classifier, continuously improved and refined as insights grew. The next, larger scale phase uses a bespoke Historian Web Application that embeds the Java validator from the parser, as well as a new Boolean classifier for valid and complete data assurance built using a Model-Driven Development technique that we also describe. This solution enforces property constraints directly at data capture time, removing the need for additional parsing and cleaning stages. The new classifier is built in an easy to use graphical technology, and the ADD-Lib tool it uses is a modern low-code development environment that auto-generates code in a large number of programming languages. It thus meets the technology independence requirement and historians are now able to produce new classifiers themselves without being able to program. We aim to infuse the project with computational and archival thinking in order to produce a robust data set that is FAIR compliant (Free Accessible Inter-operable and Re-useable).

Adaptive online learning can facilitate students' support by responding immediately to the user's interactions. Good feedback to students helps closing the gap between actual and desired performance. In this paper we analyze how to introduce online adaptive formative learning in Computer Science, a discipline with well documented challenges that are hard to tackle with traditional classroom methods. Specifically, we developed illustrative learning items teaching Model-Driven Design and implemented them in an online system that implements a model for automatic formative assessment developed by University of Torino. The model takes advantage of an automatic assessment system initially designed for STEM disciplines, then adopted for teaching languages and other disciplines too. The key features of the adaptive model supported by the online system are algorithmic questions, availability, contextualization, immediate feedback, interactive feedback, and open answers. These features are portable across subject domains, so the system can be adapted to include new subjects. We chose MDD because it is a topic of Computer Science education connected with Computational Thinking, software design, and formal methods, which are three of the core areas in need of enhanced support.

National Research and Education Networks (NRENs) are dedicated networks that provide a backbone for the collaboration and data exchange between academic organizations. However, the lack of a domain-specific bridging application, lack of interoperability and data integration are serious challenges in educational technologies, hampering collaboration and resource sharing even within existing agreements. NRENs are cost-effective backbones of large scale networks aimed to deliver convergence and promote educational opportunities beyond individual institutions. In this paper we prototype an inter-organization bridging application based on an abstract NREN architecture based on a broker pattern. The ability to communicate is also an essential precondition for the easy adoption of Open Education Resources. The motivating case study is the Afghanistan Research and Educational Network (AfgREN). To enhance ease of adoption, adaptation, and evolution, the prototype is designed following an eXtreme Model-Driven Development (XMDD) paradigm, using a low-code development environment for modelling data, processes, user interfaces in an agile rapid prototyping fashion. We generalize the results to the (federated) collaboration of regional and global NRENs, to enable the delivery of easy collaboration, data integration, high accessibility, and resource sharing across educational organizations on a national and cross-national level.

National Research and Education Networks (NRENs) are developed to provide access and collaboration between educational organizations. Single-Sign-On (SSO) applications such as eduGAIN are used in the pan European research and education network (GÉANT) and Shibboleth is used in the Internet2 NRENs in the United States. However, the lack of data integration between many eLearning systems is still a challenge in the NREN domain. We address systematic data integration between large-scale eLearning systems by designing and prototyping an eLearning broker. The NREN eLearning architecture considers the strategies and policies of collaboration parties. We apply the eXtreme Model-Driven Development (XMDD) paradigm, using the DIME low-code development environment for data modeling, process modeling, interface modeling and prototyping. The motivating case study is the Afghanistan Research and Educational Network (AfgREN).

Advances in sensing, communications and data analytics have made it possible to construct virtual replicas of Cyber-Physical Systems (CPSs). Such replicas, known as digital twins, can in principle inform decision making during operation and evolution of the systems they model. This short paper introduces the ISoLA 2020/21 series of papers on the technology and practice of engineering digital twins for CPSs. The focus is on the relationship between model-based design, machine learning, digital twins and CPSs.

Aspiring software developers, like the novice students in Computer Science courses, need to acquire a thorough understanding of fundamental computational concepts like sequential execution, conditional branching, loops, modularisation, hierarchy and reuse. This understanding and "computational thinking" is deepened when they encounter the concepts in different contexts and environments, as opposed to only in one traditional programming language. In this paper, we describe how we used the Cinco Adventure Game Tool, a tool that allows students to model simple browser games in an intuitive graphical framework, to train basic computational concepts in a creative and engaging, learning-by-doing fashion. On purpose, we steered away from traditional programming languages, in order to separate the use of the concepts and constructs from the hurdle of a programming language syntax and development environment. The experiences with a large group of first-term Computer Science students in two successive years were very positive: The students had no problems in understanding and using the concepts, used the tool proficiently and enjoyed designing and modelling the games. Working together on a game project in small groups, they showed sustained engagement, developed a high level of confidence, and created quite complex games containing various fundamental computational constructs.

Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.

Context: Several research works emphasise that the concept of simplicity is, in itself, by far not a simple concept, mainly because there are many perspectives on the perception of simplicity. Purpose: To understand how the agile team interpret their experiences in agile software projects considering the simplicity issues in agile software development. Method: Semi-structured interviews were carried out with project managers and software engineers within a software development company. The data was analysed using grounded theory techniques. Results: A set of categories (lightweight process, knowledge acquisition, personal communication, time-consuming, and product with value) that affect the simplicity in agile software development were extracted. Relationships among categories were used to construct propositions that explain the simplicity phenomena. Finally, implications for practices and recommendations are also addressed. Conclusion: The results show that a better understanding of the implications of simplicity on agile software development may contribute to the projects' successes.

Context: Several research works emphasise that the concept of simplicity is, in itself, by far not a simple concept, mainly because there are many perspectives on the perception of simplicity. Purpose: To understand how project managers and software engineers interpret their experiences in agile software projects considering the simplicity issues in agile software development. Method: Semi-structured interviews were carried out with practitioners within a software development company. The data was analysed using grounded theory techniques. Results: A set of categories (lightweight process, knowledge acquisition, personal communication, time-consuming, and product with value) that affect the simplicity in agile software development were extracted. Finally, the categories and propositions with higher explanatory power were used to create a provisional theory about simplicity in agile software projects. Conclusion: The results show that a better understanding of the implications of simplicity on agile software development may contribute to the projects' successes.

Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.

Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.

We discuss how global types, aka multiparty session types, provide a complementary perspective on workflow models within the jABC modeling framework. On a reference example from the Semantic Web Services Challenge we show how the service orchestrations of jABC workflow applications can be expressed as service choreographies based on global types. Roles, identified with sets of logically related Service-Independent Building Blocks (SIBs), bridge between the two ways of looking at the behavior of systems. We compare the degree of declarativity and robustness in the face of changes of the reference example modeled with the jABC framework with as a global types specification.

Process modeling can play a central role in problem-based software development education with regard to qualifying students for the design and implementation of software applications for their specific needs without putting the focus on the technical part of coding. eXtreme Model Driven Design (XMDD) is a paradigm that focuses on the What (solving problems), rather than on the How (the technical skills of writing code). In this way it renders application design and implementation less daunting, thus accessible and more appealing to people that are either less technically skilled, or simply not interested at all in learning usual programming. In this paper we report on our experiences with the use of the jABC process modeling framework for teaching service-based software development in an XMDD fashion to students of different fields and on different levels of education.

Cyber-Physical systems become increasingly interconnected. Mastering the governance of such systems, in particular in the era of the Internet of Things and Industry 4.0, where CPS are part of large (infra)-strcutures that span across boundaries of responsibility and of control, is becoming a challenge per se. We examine the requirements posed by such an evolution of the CPS and discuss some risks and opportunities.

In this paper, we sketch how treating product lines as systems of possibly heterogeneous constraints allows one to elegantly and consistently manage product lines in terms of a product line of product lines. In fact, as will also be illustrated along our example scenarios, this leads to a framework for a consistent division of labour in an "easy for the many difficult for the few" fashion which supports correctness by construction. Central for this approach are our powerful model-based synthesis and code generation technologies, which turn systems of constraints into executable models or target code.

SUMMARY In this article, we present our experience with over a decade of strict simplicity orientation in the development and evolution of plug‐ins. The point of our approach is to enable our graphical modeling framework jABC to capture plug‐in development in a domain‐specific setting. The typically quite tedious and technical plug‐in development is shifted this way from a programming task to the modeling level, where it can be mastered also by application experts without programming expertise. We show how the classical plug‐in development profits from a systematic domain‐specific API design and how the level of abstraction achieved this way can be further enhanced by defining adequate building blocks for high‐level plug‐in modeling. As the resulting plug‐in models can be compiled and deployed automatically, our approach decomposes plug‐in development into three phases where only the realization phase requires plug‐in‐specific effort. By using our modeling framework jABC, this effort boils down to graphical, tool‐supported process modeling. Furthermore, we support the automatic completion of process sketches for executability. All this will be illustrated along the most recent plug‐in‐based evolution of the jABC framework, which witnessed quite some bootstrapping effects. Copyright © 2013 John Wiley & Sons, Ltd.

The adoption of services on the architectural side has been rather prompt, sometimes turning a pre-existing offer of component-like software into a coarse or fine granular offer of services, in a quick SOA adaptation, and more recently along the lines proposed by the Service Component Architecture (SCA). On the contrary, service-oriented computing (the operational side of the SO-* paradigm) is not as easily producible from preexisting systems that were not conceived for this kind of deep-black box provision. The behavioural side of service engineering is still lagging behind the maturity of the mere architectural perspective because it is intrinsically more difficult to convert post factum. The realm of consistency and compliance is the home turf of formal methods; but which formal methods are adequate to support seamlessly this very large scale and heterogeneous transition to the era of services en masse? Delegation and hiding are the primary commandments of thinking in services; but what is truly required is automatic, efficient, powerful machine-readable support in a world that systematically shields internal details, and this for all the questions that concern eg. service selection and composition from a behavioural point of view. How it is built is not important, how it functions and how to use the service are here in the center of the attention.

Leading goal for the EU-project ITSy is to explore the power of simplicity for achieving robustness, flexibility and trust. A number of scenarios have been investigated in this direction, comprising looking at different notions of complexity, in particular distinguishing the actual complexity, the objective notion of complexity associated with a task as such, from the felt complexity, the subjective notion of complexity associated with the difficulty for some person satisfy his personal task. Division of labor is the typical way of decomposing the actual complexity in manageable or small piece of felt complexity. Or in other words, standing on the shoulder of giants we may reach impressive goals. A completely different way to achieve simplicity is to change the rules of the game. A good example here is the change from object tracking via image recognition to RFID-based object tracking. Whereas the former is intrinsically difficult, the latter, much simpler solution much better serves the purpose. In this session we consider three scenarios which propose such a change of perspective.

Traditional syntax-oriented variability modeling specifies the set of possible system variants by explicitly describing how variability is expressed by linguistic means and it concentrates on the set of features that may or may not be present in a product. In contrast, constraint-based variability modeling defines variability in a top-down way by restricting the set of possible compositions of reusable artifacts in terms of properties and by including in this declarative description also some behavioral knowledge the experts may have about the product. Concretely, we propose here to integrate constraint-based solution space variability modeling with feature-oriented problem space variability modeling. This new approach paves the way to significantly simplify feature-oriented software development of product lines: Each feature is described by a set of constraints capturing what the feature contributes to a product variant and expects from it, and, for a given feature selection, the set of associated feature constraints allows synthesizing the set of product variants satisfying the constraints automatically. We illustrate and evaluate the proposed approach on the concrete example of a family of workflows from the bioinformatics domain.

Abstract Automatic code generation is an essential cornerstone of today’s model-driven approaches to software engineering. Thus a key requirement for the success of this technique is the reliability and correctness of code generators. This article describes how we employ standard model checking-based verification to check that code generator models developed within our code generation framework Genesys conform to (temporal) properties. Genesys is a graphical framework for the high-level construction of code generators on the basis of an extensible library of well-defined building blocks along the lines of the Extreme Model-Driven Development paradigm. We will illustrate our verification approach by examining complex constraints for code generators, which even span entire model hierarchies. We also show how this leads to a knowledge base of rules for code generators, which we constantly extend by e.g. combining constraints to bigger constraints, or by deriving common patterns from structurally similar constraints. In our experience, the development of code generators with Genesys boils down to re-instantiating patterns or slightly modifying the graphical process model, activities which are strongly supported by verification facilities presented in this article.

The importance of verification for software products is being increasingly appreciated in industry, although still not as much as necessary to become a standard development approach for industrial-scale high-quality software.In 2005, a global initiative was started by eminent researchers in both industry and academia, with the aim of establishing and disseminating a culture of software verification from the first principles by means of theories, tools and experiments.This special issue contains a selection of contributions originally presented at the 2008 Workshop on Tools at VSTTE 2008, the conference on Verified Software: Theories, Tools and Experiments in Toronto.The VSTTE series of conferences and workshops focuses on the challenge of verifying software systems.Within VSTTE, the scope of the Tools workshop includes implementations and enabling techniques for program verifiers, which are important ingredients for the dissemination of principles and techniques among industrial practitioners.This special issue complements a sister special issue of the Journal on Software Tools For Technology Transfer (STTT) [STT10].The FAC papers address the foundational aspects of tool-based verification, whereas the STTT selection focuses on practical aspects.The general public perceives the quality of software products as a major issue.In fact, the cost of software construction is dominated by the process of debugging it and validating that the software meets the desired requirements.Due to the prohibitive cost of manual inspection, it is widely believed that computers themselves need to be part of the solution.To this end, Tony Hoare's Grand Challenge for computing research proposes the Verifying Compiler, that is, computer-implemented algorithms that validate the correctness of a given program [Hoa03].In the Manifesto of the Grand Challenge, presented at VSTTE 2005 [MW08, Coo07], the first in the series of VSTTE conferences and workshops, Tony Hoare and Jay Misra directly recognise and appraise the importance of tools as vehicles for the transmission of knowledge to practitioners.In the second paragraph of the introduction, they write: "This paper argues that the time is ripe to embark on an international Grand Challenge project to construct a program verifier that would use logical proof to give an automatic check of the correctness of programs submitted to it.Prototypes for the program verifier will be based on a sound and complete theory of programming; they will be supported by a range of program construction and analysis tools; and the entire toolset will be evaluated and evolve by experimental application to a large and widely representative sample of useful computer programs.The project will provide the scientific basis of a solution for many of the problems of programming error that afflict all builders and users of software today."The paper also suggested that the achievement of this vision should be accelerated by a major international research initiative, modelled on a Grand Challenge, with specific measurable goals.The suggested measure was one million lines of verified code, together with its specifications, designs, assertions, and other artifacts.

In this paper, we present the ConnectIT tool, which uses a graphical flow graph-based representation to express strategies for playing the connect-four game. The tool allows to transfer complex knowledge about theconnect-four game itself, simple algorithmic concepts, and modern high-level component-based modeling techniques from theoretical grounds into an inspiring and practical learning experience. For proving the feasibilityof this approach, we applied the tool in a project with pupils, who had no experience in computer sciences at all. We demonstrate that solely based on intuition and knowledge about the connect-four game, the pupils wereable to build really competitive strategies.

Modern telecommunications networks and classical roles of operators are subject to fundamental change. In the age of Web expansion, many network operators are currently seeking for new ways to create and provide applications on top of converging networks. Enabling user generated services as well as the smooth integration of communications services into mash-ups and other 3rd party services is a key capability for the Service Creation Environments. In this paper we describe our approach to enabling eXtreme Model Driven Design of Parlay X-based communications services, which is a standardized collection of Web services that expose Next Generation Networks (NGN) core services to 3rd parties. We explain how to integrate Parlay X services in a service creation environment adequate for easy, user-level mash-up design as a human-computer interaction during service design and creation phase. We illustrate the integration into end-to-end multiplatform service orchestrations by means of an Assisted Living scenario that has been exhibited at the German CeBIT 2009 fair to show how human beings may interact with automated processes through real-time communication channels.

Bio-jETI is a framework for model-based, graphical development and execution of bioinformatics analysis processes. With the GeneSys code generation framework we can automatically compile the workflow models into native, stand-alone program code. We show via a phylogenetic analysis workflow designed by the DNA Data Bank of Japan (DDBJ) how we generate 6 variants of Java code from the corresponding process model realized in Bio-jETI. Performance measurements show that 1) the overall workflow execution time is dominated by the remote services it uses, and thus 2)all 6 variants are almost as fast as the handwritten Java of DDBJ. This way, we obtain efficient native code essentially without program- ming. Thus, we demonstrate in this paper that model- based workflow development in Bio-jETI offers several advantages over manual implementation – including higher agility, greater transparency and better maintainability – without compromising the runtime performance.

In the area of re-engineering or re-purposing of existing software, model driven methodologies are hard to adopt because of lack of the central asset: models for the existing source code. Large companies and organizations that maintain a large code basis over long periods of time have recognized this issue, and are looking for ways to turn that code basis into models understandable under a business purposes point of view. In this paper, we introduce a technique that address this issue for C/C++ code. It delivers code-models, a representation of source code close to control flow graphs, by means of tool-supported analysis and transformations from legacy source code. Code models extend usual control flow graphs with rich information on both nodes and edges. They are immediately analyzable and verifiable in the jABC MDD framework, thus adequate for a model driven design, development, and evolution process.

Service orientation leads to a completely new understanding and a much more end-user oriented tailoring of software design. We advocate a new software development paradigm: eXtreme Model-Driven Design (XMDD), designed to continuously involve the customer/application expert throughout the whole system's life cycle, including development and software maintenance. As maintenance is predominantly an adaption to new user requirements or to other global conditions, empowering the application expert would change the scene: Customer/application experts could rapidly adapt the system to their changing requirements. Source code becomes "only" a by-product and the development focuses on the model level. This paper presents a new development paradigm which realizes these ideas.

BACKGROUND: The development of bioinformatics databases, algorithms, and tools throughout the last years has lead to a highly distributed world of bioinformatics services. Without adequate management and development support, in silico researchers are hardly able to exploit the potential of building complex, specialized analysis processes from these services. The Semantic Web aims at thoroughly equipping individual data and services with machine-processable meta-information, while workflow systems support the construction of service compositions. However, even in this combination, in silico researchers currently would have to deal manually with the service interfaces, the adequacy of the semantic annotations, type incompatibilities, and the consistency of service compositions. RESULTS: In this paper, we demonstrate by means of two examples how Semantic Web technology together with an adequate domain modelling frees in silico researchers from dealing with interfaces, types, and inconsistencies. In Bio-jETI, bioinformatics services can be graphically combined to complex services without worrying about details of their interfaces or about type mismatches of the composition. These issues are taken care of at the semantic level by Bio-jETI's model checking and synthesis features. Whenever possible, they automatically resolve type mismatches in the considered service setting. Otherwise, they graphically indicate impossible/incorrect service combinations. In the latter case, the workflow developer may either modify his service composition using semantically similar services, or ask for help in developing the missing mediator that correctly bridges the detected type gap. Newly developed mediators should then be adequately annotated semantically, and added to the service library for later reuse in similar situations. CONCLUSION: We show the power of semantic annotations in an adequately modelled and semantically enabled domain setting. Using model checking and synthesis methods, users may orchestrate complex processes from a wealth of heterogeneous services without worrying about interfaces and (type) consistency. The success of this method strongly depends on a careful semantic annotation of the provided services and on its consequent exploitation for analysis, validation, and synthesis. We are convinced that these annotations will become standard, as they will become preconditions for the success and widespread use of (preferred) services in the Semantic Web.

The Semantic Web Services Challenge addresses since 2006 the issue of finding adequate domain modelling formalisms that help taming the complexity of service orchestration and service discovery. In this paper we examine the concrete settings, the dimensions of complexity that appear in the Challenge, and reflect on the essence of the observations so far.

Recent experience and feedback from panels indicates that what the audience likes best is the chance to ask questions, particularly regarding things that might solve problems on their development projects or in their research studies. This panel has been held at every ISSRE since 1997, and has been highly popular. Originally the panel was chaired by John Musa, but Mike Hinchey took over that role last year. The panel has no presentations, only questions. The questions can be on anything, ranging from theory to details of application. The panelists have been selected to make available wide and extensive experience in the field.

BACKGROUND: PCR primer design is an everyday, but not trivial task requiring state-of-the-art software. We describe the popular tool GeneFisher and explain its recent restructuring using workflow techniques. We apply a service-oriented approach to model and implement GeneFisher-P, a process-based version of the GeneFisher web application, as a part of the Bio-jETI platform for service modeling and execution. We show how to introduce a flexible process layer to meet the growing demand for improved user-friendliness and flexibility. RESULTS: Within Bio-jETI, we model the process using the jABC framework, a mature model-driven, service-oriented process definition platform. We encapsulate remote legacy tools and integrate web services using jETI, an extension of the jABC for seamless integration of remote resources as basic services, ready to be used in the process. Some of the basic services used by GeneFisher are in fact already provided as individual web services at BiBiServ and can be directly accessed. Others are legacy programs, and are made available to Bio-jETI via the jETI technology. The full power of service-based process orientation is required when more bioinformatics tools, available as web services or via jETI, lead to easy extensions or variations of the basic process. This concerns for instance variations of data retrieval or alignment tools as provided by the European Bioinformatics Institute (EBI). CONCLUSIONS: The resulting service- and process-oriented GeneFisher-P demonstrates how basic services from heterogeneous sources can be easily orchestrated in the Bio-jETI platform and lead to a flexible family of specialized processes tailored to specific tasks.

BACKGROUND: With Bio-jETI, we introduce a service platform for interdisciplinary work on biological application domains and illustrate its use in a concrete application concerning statistical data processing in R and xcms for an LC/MS analysis of FAAH gene knockout. METHODS: Bio-jETI uses the jABC environment for service-oriented modeling and design as a graphical process modeling tool and the jETI service integration technology for remote tool execution. CONCLUSIONS: As a service definition and provisioning platform, Bio-jETI has the potential to become a core technology in interdisciplinary service orchestration and technology transfer. Domain experts, like biologists not trained in computer science, directly define complex service orchestrations as process models and use efficient and complex bioinformatics tools in a simple and intuitive way.

The FMICS-jETI platform is a collaborative, service- based demonstrator of tools and techniques for the analysis of industrial critical systems. It is the FMICS Working Group contribution to the Verified Software Initiative. In this paper, we extend the scope of the FMICS-jETI platform to address the integration of heterogeneous and legacy tools and technologies. We show how to integrate 1) CORBA, a language independent standard for the inter-operability of heterogeneous functionalities distributed over a network, 2) active model learning technologies, via the LearnLib, as a model extrapolation technique that uses testing to explore a black box system and CORBA as a communication mechanism, and 3) third party applications built on top of the LearnLib, in this case Smyle, a tool that synthesizes design models by learning from examples, that uses the LearnLib as learner core.

In this paper we present the FormulaBuilder, a flexible tool for graph-based modelling and generation of formulae. The FormulaBuilder allows easy and intuitive creation of formulae by using basic components called Formula Building Blocks (FBBs) and arranging them as graphs according to the syntactic structure of a formula. Such a graph can then be validated and used to generate the corresponding formula on the basis of a specific syntax which is chosen from a list of syntaxes supported by the FormulaBuilder.An important application of the FormulaBuilder is the formal specification of properties that describe the requirements of a system. Such property specifications are usually needed by verification tools like model checkers, that help software engineers to detect errors in a specified system. The FormulaBuilder allows users to model property specifications as formula graphs by using commonly-occurring specification patterns.

In today's business the availability of services is of central importance. To guarantee a higher availability of a service, like a Web-service, it can be installed on several machines, which are running in a hot-standby operation. In case of a fault one hot-standby service can take over the work of the faulty service. Novel to our approach is that this kind of redundancy can be applied to services, that normally do not support service availability concepts. The switching of one machine running in hot-standby mode to active can be done from an external system monitoring the service. MaTRICS is an architecture that allows the configuration of any service provided by a specific server. The specification is done by service logic graphs, which can be validated by model checking.

LC/MS is a successful analysis technique for the statistical analysis used in several branches of biology. It requires an intense screening and combination of the raw data, which is usually done with programs and libraries invoked by scripts in the domain-specific statistics language S or R. We show here how to model and implement this complex workflow in a service-oriented fashion, using the jABC service definition environment and jETI for remote service integration and execution.

One of the goals of FMICS, the ERCIM Working Group on Formal Methods for Industrial Critical Systems (FMICS) [8], is to transfer and promote the use formal methods technology in industry. The ongoing Verified Software Repository Grand Challenge [11] offers a great opportunity to reach this goal, resulting in a more robust and solid software industry in Europe. We demonstrate here the current status of the FMICS-jETIplatform1, a collaborative demonstrator based on the jETI technology2, that provides as repository a collection of verification tools stemming from the activities of the FMICS working group and facilities to orchestrate them in a remote and simple way. At the same time FMICS-jETI itself is a contribution to the VSR repository and thus to the Grand Challenge.

Model driven analysis and design are increasingly recognized as powerful methodologies for software development and evolution. Model driven approaches in particular can be also combined with formal methods, offering advantages for verification, analysis, and testing. In order to use model driven methods for re-designing existing software, however, one needs additional facilities to transform the existing source code into adequate models. We examine in this paper a large number of existing tools for the analysis and processing of C/C++ source code, and evaluate them with respect to their usefulness in the model driven development process of software re-design projects. Our goal is to identify tools suitable to convert C or C++ code into a code-level model. Preferably, we want to use existing compilers, adequate system tools or other research and commercial programs to automate the process of deriving code-level models of large software applications.

Summary form only given. Service-oriented design has long driven the development of the telecommunications infrastructure and applications, especially intelligent network services. Applying the same principles of domain specificity, virtualization, loose coupling, and seamless vertical integration to business processes has the potential to lead to a new generation of personalized, secure, and highly available Web services

Test-based model generation by classical automata learning is very expensive. It requires an impractically large number of queries to the system, each of which must be implemented as a system-level test case. Key towards the tractability of observation based model generation are powerful optimizations exploiting different kinds of expert knowledge in order to drastically reduce the number of required queries, and thus the testing effort. In this paper, we present a thorough experimental analysis of the second-order effects between such optimizations in order to maximize their combined impact

We propose a framework for top-down Web service interoperation based on an aggressive version of model-driven development (AMDD). The point here is to govern the construction and customization of complex Web applications at the model level in a framework that allows application experts to directly formulate their desires in an adequate way. Adequate means in this context that applications can be automatically validated, executed, tested, and deployed by the application experts, inside a framework that takes care also of second-order concerns. Our approach, which focuses on functionalities as the basic entities of the design space is tailored to make second order issues like interoperation, distribution, and compatibility simple for the many, difficult for the few: simple for the many, as the advocated approach hides most of the intricate second-order issues from the application designer, and difficult for the few, as these issues must be dealt with by means of complex compilation, synthesis or technology mappings. Our experience indicates that this approach has the potential to cover and thereby drastically simplify the bulk of modern Web application development and customization

Dependability of complex systems is a critical system-level issue, which is still insufficiently tackled today. We propose the adoption of an aggressive model-driven development paradigm (AMDD) to adequately capture globally scoped issues like interoperability and compatibility. AMDD moves most of the recurring problems of compatibility and consistency of a system's design, implementation and evolution from the coding and integration level to the modeling level. In particular it enables an economical treatment of cross-system issues. This approach has proven useful already for the design, realization and test of complex distributed applications. In this paper we discuss the potential and benefits of AMDD and present examples where it is already adopted

We study the extension of applicability of system-level testing techniques to the construction of a consistent model of (legacy) systems under test, which are seen as black boxes. We gather observations via an automated test environment and systematically extend available test suites according to learning procedures. Testing plays two roles here: (i) as an application domain and (ii) as the enabling technology for the adopted learning technique. The benefits include enhanced error detection and diagnosis, both during the testing phase and the online test of deployed systems at customer sites. 1