Engineering Enterprise Software Systems with Interactive UML Models and Aspect-Oriented Middleware

Large scale enterprise software systems are inherently complex and hard to maintain. To deal with this complexity, current mainstream software engineering practices aim at raising the level of abstraction to visual models described in OMG’s UML modeling language. Current UML tools, however, produce static design diagrams for documentation which quickly become out-of-sync with the software, and thus obsolete. To address this issue, current model-driven software development approaches aim at software automation using generators that translate models into code. However, these solutions don’t have a good answer for dealing with legacy source code and the evolution of existing enterprise software systems. This research investigates an alternative solution by making the process of modeling more interactive with a simulator and integrating simulation with the live software system. Such an approach supports model-driven development at a higher-level of abstraction with models without sacrificing the need to drop into a lower-level with code. Additionally, simulation also supports better evolution since the impact of a change to a particular area of existing software can be better understood using simulated “what-if” scenarios. This project proposes such a solution by developing a web-based UML simulator for modeling use cases and sequence diagrams and integrating the simulator with existing applications using aspect-oriented middleware technology

Identifying Crisis-Critical Intellectual Property Challenges during the Covid-19 Pandemic: A scenario analysis and conceptual extrapolation of innovation ecosystem dynamics using a visual mapping approach

The Covid-19 pandemic exposed firms, organisations and their respective supply chains which are directly involved in the manufacturing of products that are critical to alleviating the effects of the health crisis, collectively referred to as the Crisis-Critical Sector,to unprecedented challenges. Firms from other sectors, such as automotive, luxury and home appliances, have rushed into the Crisis-Critical Sector in order to support the effort to upscale incumbent manufacturing capacities, thereby introducing Intellectual Property (IP)related dynamics and challenges. We apply an innovation ecosystem perspective on the Crisis-Critical Sector and adopt a novel visual mapping approach to identify IP associated challenges and IP specific dynamic developments during and potentially beyond the crisis.In this paper, we add methodologically by devising and testing a visual approach to capturing IP related dynamics in evolving innovation ecosystems and contribute to literature on IP management in the open innovation context by proposing paraground IP as a novel IP type.Finally, we also deduce managerial implications for IP management practitioners at both incumbent firms and new entrants for navigating innovation ecosystems subject to crisis-induced dynamic shifts

Supporting the grow-and-prune model for evolving software product lines

207 p.Software Product Lines (SPLs) aim at supporting the development of a whole family of software products through a systematic reuse of shared assets. To this end, SPL development is separated into two interrelated processes: (1) domain engineering (DE), where the scope and variability of the system is defined and reusable core-assets are developed; and (2) application engineering (AE), where products are derived by selecting core assets and resolving variability. Evolution in SPLs is considered to be more challenging than in traditional systems, as both core-assets and products need to co-evolve. The so-called grow-and-prune model has proven great flexibility to incrementally evolve an SPL by letting the products grow, and later prune the product functionalities deemed useful by refactoring and merging them back to the reusable SPL core-asset base. This Thesis aims at supporting the grow-and-prune model as for initiating and enacting the pruning. Initiating the pruning requires SPL engineers to conduct customization analysis, i.e. analyzing how products have changed the core-assets. Customization analysis aims at identifying interesting product customizations to be ported to the core-asset base. However, existing tools do not fulfill engineers needs to conduct this practice. To address this issue, this Thesis elaborates on the SPL engineers' needs when conducting customization analysis, and proposes a data-warehouse approach to help SPL engineers on the analysis. Once the interesting customizations have been identified, the pruning needs to be enacted. This means that product code needs to be ported to the core-asset realm, while products are upgraded with newer functionalities and bug-fixes available in newer core-asset releases. Herein, synchronizing both parties through sync paths is required. However, the state of-the-art tools are not tailored to SPL sync paths, and this hinders synchronizing core-assets and products. To address this issue, this Thesis proposes to leverage existing Version Control Systems (i.e. git/Github) to provide sync operations as first-class construct

Systemic Design for the innovation of home appliances The meaningfulness of data in designing sustainable systems

This work addressed the domestic environment considering this context as a complex system characterised by significant impacts in terms of resource consumption. Within the theoretical framework of Systemic Design (SD), this thesis focused on home appliances, in order to understand how to reduce the impact directly attributable to them, while optimising and simplifying daily tasks for the user. A design methodology towards environmental sustainability has been structured, by focusing on the use of data for design purposes and on creating value for the user through meaningful products. It considers the user, the product and the environment as central topics, by giving them the same relevance and the literature review is structured accordingly, investigating needs and requirements, ethical issues, but also current products and future scenarios. During my experience at TU Delft, I spent six months in the Department of Internet of Things at the Faculty of Industrial Design Engineering. Together with computer scientists, we developed a prototype to collect some missing data, establishing the importance of grounding the decision-making on reliable information. IoT and data gathering open a variety of possibilities in monitoring, accessing more precise knowledge of products and households useful for design purposes, up to understand how to fill the gap perceived by the user between needs and solutions. It considered the potential benefits of using IoT indicators to collect missing information about both the product, its use and its operating environment to address critical aspects in the design stage, thus extending products’ lifetime. This thesis highlighted the importance of building multidisciplinary design teams to investigate different classes of requirements, and the need for flexible tools to cope with complex and evolving requirements, the co-evolution of problem and solutions and investigating open-ended questions. This approach leaves room for addressing every step of the traditional life-cycle in a more circular way, shifting the focus from the life-cycle centrality of the previous century to a more complex vision about the product

Self-organising agent communities for autonomic resource management

The autonomic computing paradigm addresses the operational challenges presented by increasingly complex software systems by proposing that they be composed of many autonomous components, each responsible for the run-time reconfiguration of its own dedicated hardware and software components. Consequently, regulation of the whole software system becomes an emergent property of local adaptation and learning carried out by these autonomous system elements. Designing appropriate local adaptation policies for the components of such systems remains a major challenge. This is particularly true where the system’s scale and dynamism compromise the efficiency of a central executive and/or prevent components from pooling information to achieve a shared, accurate evidence base for their negotiations and decisions.In this paper, we investigate how a self-regulatory system response may arise spontaneously from local interactions between autonomic system elements tasked with adaptively consuming/providing computational resources or services when the demand for such resources is continually changing. We demonstrate that system performance is not maximised when all system components are able to freely share information with one another. Rather, maximum efficiency is achieved when individual components have only limited knowledge of their peers. Under these conditions, the system self-organises into appropriate community structures. By maintaining information flow at the level of communities, the system is able to remain stable enough to efficiently satisfy service demand in resource-limited environments, and thus minimise any unnecessary reconfiguration whilst remaining sufficiently adaptive to be able to reconfigure when service demand changes

The state of adoption and the challenges of systematic variability management in industry

Handling large-scale software variability is still a challenge for many organizations. After decades of research on variability management concepts, many industrial organizations have introduced techniques known from research, but still lament that pure textbook approaches are not applicable or efficient. For instance, software product line engineering—an approach to systematically develop portfolios of products—is difficult to adopt given the high upfront investments; and even when adopted, organizations are challenged by evolving their complex product lines. Consequently, the research community now mainly focuses on re-engineering and evolution techniques for product lines; yet, understanding the current state of adoption and the industrial challenges for organizations is necessary to conceive effective techniques. In this multiple-case study, we analyze the current adoption of variability management techniques in twelve medium- to large-scale industrial cases in domains such as automotive, aerospace or railway systems. We identify the current state of variability management, emphasizing the techniques and concepts they adopted. We elicit the needs and challenges expressed for these cases, triangulated with results from a literature review. We believe our results help to understand the current state of adoption and shed light on gaps to address in industrial practice.This work is supported by Vinnova Sweden, Fond Unique Interminist´eriel (FUI) France, and the Swedish Research Council. Open access funding provided by University of Gothenbur

The Future of the Internet III

Presents survey results on technology experts' predictions on the Internet's social, political, and economic impact as of 2020, including its effects on integrity and tolerance, intellectual property law, and the division between personal and work lives