Supporting 'design for reuse' with modular design

Engineering design reuse refers to the utilization of any knowledge gained from the design activity to support future design. As such, engineering design reuse approaches are concerned with the support, exploration, and enhancement of design knowledge prior, during, and after a design activity. Modular design is a product structuring principle whereby products are developed with distinct modules for rapid product development, efficient upgrades, and possible reuse (of the physical modules). The benefits of modular design center on a greater capacity for structuring component parts to better manage the relation between market requirements and the designed product. This study explores the capabilities of modular design principles to provide improved support for the engineering design reuse concept. The correlations between modular design and 'reuse' are highlighted, with the aim of identifying its potential to aid the little-supported process of design for reuse. In fulfilment of this objective the authors not only identify the requirements of design for reuse, but also propose how modular design principles can be extended to support design for reuse

On Experimentation in Software-Intensive Systems

Context: Delivering software that has value to customers is a primary concern of every software company. Prevalent in web-facing companies, controlled experiments are used to validate and deliver value in incremental deployments. At the same that web-facing companies are aiming to automate and reduce the cost of each experiment iteration, embedded systems companies are starting to adopt experimentation practices and leverage their activities on the automation developments made in the online domain. Objective: This thesis has two main objectives. The first objective is to analyze how software companies can run and optimize their systems through automated experiments. This objective is investigated from the perspectives of the software architecture, the algorithms for the experiment execution and the experimentation process. The second objective is to analyze how non web-facing companies can adopt experimentation as part of their development process to validate and deliver value to their customers continuously. This objective is investigated from the perspectives of the software development process and focuses on the experimentation aspects that are distinct from web-facing companies. Method: To achieve these objectives, we conducted research in close collaboration with industry and used a combination of different empirical research methods: case studies, literature reviews, simulations, and empirical evaluations. Results: This thesis provides six main results. First, it proposes an architecture framework for automated experimentation that can be used with different types of experimental designs in both embedded systems and web-facing systems. Second, it proposes a new experimentation process to capture the details of a trustworthy experimentation process that can be used as the basis for an automated experimentation process. Third, it identifies the restrictions and pitfalls of different multi-armed bandit algorithms for automating experiments in industry. This thesis also proposes a set of guidelines to help practitioners select a technique that minimizes the occurrence of these pitfalls. Fourth, it proposes statistical models to analyze optimization algorithms that can be used in automated experimentation. Fifth, it identifies the key challenges faced by embedded systems companies when adopting controlled experimentation, and we propose a set of strategies to address these challenges. Sixth, it identifies experimentation techniques and proposes a new continuous experimentation model for mission-critical and business-to-business. Conclusion: The results presented in this thesis indicate that the trustworthiness in the experimentation process and the selection of algorithms still need to be addressed before automated experimentation can be used at scale in industry. The embedded systems industry faces challenges in adopting experimentation as part of its development process. In part, this is due to the low number of users and devices that can be used in experiments and the diversity of the required experimental designs for each new situation. This limitation increases both the complexity of the experimentation process and the number of techniques used to address this constraint

A service network perspective to evaluate service matching in early design

Purpose – Service matching is defined in this paper as the process of combining a new service with one or more existing services. A recurring problem for service designer is to match new services with existing ones. This process may be seen as the fundamental action for the development of a service network. The purpose of this paper is to evaluate the consequences that may follow from service matching. Design/methodology/approach – Through an analogy with living organisms in natural ecosystems, the service relationship deployment (SRD) allows the investigation of the possible relationships between matched services. Findings – This paper presents a new method, named SRD, developed to support the process of service matching in the early design phases of a new service. The description of the method is supported by some practical examples. Originality/value – The focus of the scientific community on the problem of matching new services with existing ones, is very limited. This paper proposes a new methodology to address this issue

MROS: Runtime Adaptation For Robot Control Architectures

Known attempts to build autonomous robots rely on complex control architectures, often implemented with the Robot Operating System platform (ROS). Runtime adaptation is needed in these systems, to cope with component failures and with contingencies arising from dynamic environments-otherwise, these affect the reliability and quality of the mission execution. Existing proposals on how to build self-adaptive systems in robotics usually require a major re-design of the control architecture and rely on complex tools unfamiliar to the robotics community. Moreover, they are hard to reuse across applications. This paper presents MROS: a model-based framework for run-time adaptation of robot control architectures based on ROS. MROS uses a combination of domain-specific languages to model architectural variants and captures mission quality concerns, and an ontology-based implementation of the MAPE-K and meta-control visions for run-time adaptation. The experiment results obtained applying MROS in two realistic ROS-based robotic demonstrators show the benefits of our approach in terms of the quality of the mission execution, and MROS' extensibility and re-usability across robotic applications

A systematic approach for simulation-based dimensioning of production systems during the concept phase of factory planning

Due to increasing globalization, market penetration, and technological progress, more products are becoming highly standardized and interchangeable. This has led to fierce price competition, forcing companies to compete for declining margins. To remain competitive in the long term, it is essential to consider both changeability and profitability during the early planning phases. The article proposes an approach for simulation studies using discrete-event simulation during the concept phase of factory planning. This approach aims to systematically dimension production resources while considering alternative scaling options, such as a higher degree of automation. By doing so, the approach facilitates the demand-oriented deployment of resources during the ramp-up phase, which helps to control and reduce manufacturing costs. The simulation experiments yield scaling paths that indicate the timing and quantity of resources required to meet changing demands. These paths form the basis for subsequent factory planning steps. For instance, the layout can incorporate the necessary space for a future automation solution that will be profitable, enabling faster adaptation to demand changes and securing competitive advantages. This is demonstrated in a use case where the approach was applied to the factory planning of a new production system for a sensor product family

Software Product Line Reengineering: A Case Study on the Geographic Domain

The growing adoption of software product lines (SPL) represents perhaps a paradigm shift in software development aiming at improving cost, quality, time to market, and developer productivity. While the underlying concepts are straightforward enough building a family of related products or systems by planned and careful reuse of a base of generalized software development assets the problems can be in the details, as successful product line practice involves domain understanding, technology selection, and so forth. Today, there is an important increment on reporting experiences and lessons about SPL development by capturing aspects that have been gathered during daily practice. Following this line, in this paper we start from our experiences of developing a software product line on the Marine Ecology domain highlighting our reasons for reengineering a previous SPL. Then, we explain step-bystep reengineering activities in terms of motivation, solutions, and lessons learned, which summarize strengths and limitations of the applied practices. Differently from other cases, here we take advantage of using domain standards as well as open source implementations within the geographic domain.Facultad de Informátic

Modeling and Selection of Software Service Variants

Providers and consumers have to deal with variants, meaning alternative instances of a service?s design, implementation, deployment, or operation, when developing or delivering software services. This work presents service feature modeling to deal with associated challenges, comprising a language to represent software service variants and a set of methods for modeling and subsequent variant selection. This work?s evaluation includes a POC implementation and two real-life use cases

Software Product Line Reengineering: A Case Study on the Geographic Domain

The growing adoption of software product lines (SPL) represents perhaps a paradigm shift in software development aiming at improving cost, quality, time to market, and developer productivity. While the underlying concepts are straightforward enough building a family of related products or systems by planned and careful reuse of a base of generalized software development assets the problems can be in the details, as successful product line practice involves domain understanding, technology selection, and so forth. Today, there is an important increment on reporting experiences and lessons about SPL development by capturing aspects that have been gathered during daily practice. Following this line, in this paper we start from our experiences of developing a software product line on the Marine Ecology domain highlighting our reasons for reengineering a previous SPL. Then, we explain step-bystep reengineering activities in terms of motivation, solutions, and lessons learned, which summarize strengths and limitations of the applied practices. Differently from other cases, here we take advantage of using domain standards as well as open source implementations within the geographic domain.Facultad de Informátic

Towards Identifying and closing Gaps in Assurance of autonomous Road vehicleS - a collection of Technical Notes Part 1

This report provides an introduction and overview of the Technical Topic Notes (TTNs) produced in the Towards Identifying and closing Gaps in Assurance of autonomous Road vehicleS (Tigars) project. These notes aim to support the development and evaluation of autonomous vehicles. Part 1 addresses: Assurance-overview and issues, Resilience and Safety Requirements, Open Systems Perspective and Formal Verification and Static Analysis of ML Systems. Part 2: Simulation and Dynamic Testing, Defence in Depth and Diversity, Security-Informed Safety Analysis, Standards and Guidelines

Model-based fleet deployment in the IoT–edge–cloud continuum

With the increasing computing and networking capabilities, IoT devices and edge gateways have become part of a larger IoT–edge–cloud computing continuum, where processing and storage tasks are distributed across the whole network hierarchy, not concentrated only in the cloud. At the same time, this also introduced continuous delivery practices to the development of software components for network-connected gateways and sensing/actuating nodes. These devices are placed on end users’ premises and are characterized by continuously changing cyber-physical contexts, forcing software developers to maintain multiple application versions and frequently redeploy them on a distributed fleet of devices with respect to their current contexts. Doing this correctly and efficiently goes beyond manual capabilities and requires an intelligent and reliable automated solution. This paper describes a model-based approach to automatically assigning multiple software deployment plans to hundreds of edge gateways and connected IoT devices implemented in collaboration with a smart healthcare application provider. From a platform-specific model of an existing edge computing platform, we extract a platform-independent model that describes a list of target devices and a pool of available deployment plans. Next, we use constraint solving to automatically assign deployment plans to devices at once with respect to their specific contexts. The result is transformed back into the platform-specific model and includes a suitable deployment plan for each device, which is then consumed by our engine to deploy software components not only on edge gateways but also on their downstream IoT devices with constrained resources and connectivity. We validate the approach with a fleet deployment prototype integrated into a DevOps toolchain used by the partner application provider. Initial experiments demonstrate the viability of the approach and its usefulness in supporting DevOps for edge and IoT software development.publishedVersio