8,823 research outputs found
Modeling Software Process Configurations for Enterprise Adaptability
Abstract. Modern enterprises are expected to continuously evolve and adapt to uncertain environmental conditions and evolving customer trends. Adaptability in software processes enable enterprises to respond to changing situations by selecting software process configurations that help best meet enterprise-level business goals. Conventional methods of modeling and designing software processes are limited in their ability to visualize these software process configurations, reason about them and select an appropriate configuration which meet functional and non-functional requirements while considering enterprise-level perspectives. As part of our PhD project, we propose a requirements-based software process adaptability framework that considers software process adaptability, first at a process-centric and then at an agent-centric level. Key constructs for this framework are discussed and illustrated by using the DevOps approach as an example
Development of an Extended Product Lifecycle Management through Service Oriented Architecture.
Organised by: Cranfield UniversityThe aim of this work is to define new business opportunities through the concept of Extended Product
Lifecycle Management (ExtPLM), analysing its potential implementation within a Service Oriented
Architecture. ExtPLM merges the concepts of Extended Product, Avatar and PLM. It aims at allowing a
closer interaction between enterprises and their customers, who are integrated in all phases of the life cycle,
creating new technical functionalities and services, improving both the practical (e.g. improving usage,
improving safety, allowing predictive maintenance) and the emotional side (e.g. extreme customization) of
the product.Mori Seiki – The Machine Tool Company; BAE Systems; S4T – Support Service Solutions: Strategy and Transitio
A framework for Model-Driven Engineering of resilient software-controlled systems
AbstractEmergent paradigms of Industry 4.0 and Industrial Internet of Things expect cyber-physical systems to reliably provide services overcoming disruptions in operative conditions and adapting to changes in architectural and functional requirements. In this paper, we describe a hardware/software framework supporting operation and maintenance of software-controlled systems enhancing resilience by promoting a Model-Driven Engineering (MDE) process to automatically derive structural configurations and failure models from reliability artifacts. Specifically, a reflective architecture developed around digital twins enables representation and control of system Configuration Items properly derived from SysML Block Definition Diagrams, providing support for variation. Besides, a plurality of distributed analytic agents for qualitative evaluation over executable failure models empowers the system with runtime self-assessment and dynamic adaptation capabilities. We describe the framework architecture outlining roles and responsibilities in a System of Systems perspective, providing salient design traits about digital twins and data analytic agents for failure propagation modeling and analysis. We discuss a prototype implementation following the MDE approach, highlighting self-recovery and self-adaptation properties on a real cyber-physical system for vehicle access control to Limited Traffic Zones
A Framework for Evaluating Model-Driven Self-adaptive Software Systems
In the last few years, Model Driven Development (MDD), Component-based
Software Development (CBSD), and context-oriented software have become
interesting alternatives for the design and construction of self-adaptive
software systems. In general, the ultimate goal of these technologies is to be
able to reduce development costs and effort, while improving the modularity,
flexibility, adaptability, and reliability of software systems. An analysis of
these technologies shows them all to include the principle of the separation of
concerns, and their further integration is a key factor to obtaining
high-quality and self-adaptable software systems. Each technology identifies
different concerns and deals with them separately in order to specify the
design of the self-adaptive applications, and, at the same time, support
software with adaptability and context-awareness. This research studies the
development methodologies that employ the principles of model-driven
development in building self-adaptive software systems. To this aim, this
article proposes an evaluation framework for analysing and evaluating the
features of model-driven approaches and their ability to support software with
self-adaptability and dependability in highly dynamic contextual environment.
Such evaluation framework can facilitate the software developers on selecting a
development methodology that suits their software requirements and reduces the
development effort of building self-adaptive software systems. This study
highlights the major drawbacks of the propped model-driven approaches in the
related works, and emphasise on considering the volatile aspects of
self-adaptive software in the analysis, design and implementation phases of the
development methodologies. In addition, we argue that the development
methodologies should leave the selection of modelling languages and modelling
tools to the software developers.Comment: model-driven architecture, COP, AOP, component composition,
self-adaptive application, context oriented software developmen
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