A Brief Survey on Product Derivation Methods in Software Product Line

Product Derivation represents one of the main challenges that a Software Product Line (SPL) faces. Deriving individual products from shared software assets is a time-consuming and an expensive activity. Until now, only few works addressed, in a limited context, a partial evaluation of a reduced number of proposed derivation approaches. The main objective of such studies was the comparison of a proposed approach regarding two or three approaches. The purpose of the study reported in this paper is to set up a framework oriented to evaluate and compare existing SPL derivation approaches. The proposed framework uses a number of criteria which help understanding the capabilities and highlight the strength and the weakness of each SPL derivation approach

An Agile Process Model for Product Derivation in Software Product Line Engineering

Software Product Lines (SPL) and Agile practices have emerged as new paradigms for developing software. Both approaches share common goals; such as improving productivity, reducing time to market, decreasing development costs and increasing customer satisfaction. These common goals provide the motivation for this research. We believe that integrating Agile practices into SPL can bring a balance between agility and formalism. However, there has been little research on such integration. We have been researching the potential of integrating Agile approaches in one of the key SPL process areas, product derivation. In this paper we present an outline of our Agile process model for product derivation that was developed through industry based case study research

Capturing variability in Model Based Systems Engineering

International audienceAutomotive model-based systems engineering needs to be dapted to the industry specific needs, in particular by implementing appropriate means of representing and operating with variability. We rely on existing modeling techniques as an opportunity to provide a description of variability adapted to a systems en- gineering model. However, we also need to take into account requirements related to backwards compatibility with current practices, given the industry experience in mass customization. We propose to adopt the product line paradigm in model-based systems engineering by extending the orthogonal variability model, and adapting it to our specific needs. This brings us to an expression closer to a description of constraints, related to both orthogonal variability, and to SysML system models. We introduce our approach through a discussion on the different aspects that need to be covered for expressing variability in systems engineering. We explore these aspects by observing an automotive case study, and relate them to a list of contextual requirements for variability management

Formal Modelling of Feature Configuration Workflows

In software product line engineering, the configuration process can be a long and complex undertaking that in-volves many participants. When configuration is supported by feature diagrams, two challenges are to modularise the feature diagram into related chunks, and to schedule them as part of the configuration process. Existing work has only focused on the first of these challenges and, for the rest, assumes that feature diagram modules are configured se-quentially. This paper addresses the second challenge. It suggests using YAWL, a state-of-the-art workflow language, to represent the configuration workflow while feature dia-grams model the available configuration options.The prin-cipal contribution of the paper is a new combined formal-ism: feature configuration workflows. A formal semantics is provided so as to pave the way for unambiguous tool speci-fication and safer reasoning about of the configuration pro-cess. The work is motivated and illustrated through a con-figuration scenario taken from the space industry

Evolution, testing and configuration of variability intensive systems

Tesis descargada desde ResearchGateOne of the key characteristics of software is its ability to be adapted and configured to different scenarios. Recently, software variability has been studied as a first-class concept in different domains ranging from software product lines to pervasive systems. Variability is the ability of a software product to vary depending on different circumstances. Variability intensive systems are those software products where variability management is a core engineering activity. The varying parts of those systems are commonly modeled by us- ing different variability model flavors, being feature modeling one of the most common ones. Feature models were first introduced by Kang et al. back in 1990 and are a compact representation of a set of configurations in a variability intensive system. The large number of configurations that a feature model can encode makes the manual analysis of feature models an error prone and costly task. Then, computer-aided mechanisms appeared as a solution to extract useful information from feature models. This process of extracting information from feature models is known as ¿Automated Analysis of Feature models¿ that has been one of the main areas of research in the last years where more than thirty analysis operations have been proposed.Premio Extraordinario de Doctorado U

European Capacity for Monitoring and Assimilating Space-based Climate Change Observations - Status and Prospects

This report, which is based on the findings of a workshop at Ispra in March 2009, provides the scientific background to a forthcoming Commission response to the Space and Competitiveness councils requests that the commission assess the needs for full access to standardised climate change data, the means to provide these data and together with ESA, EUMETSAT and the scientific community define how GMES services can contribute effectively to providing these data. The report therefore focuses primarily, but not exclusively, on space-based Climate data sources. Standardised climate data are needed for climate monitoring, prediction and research, while climate information informs the policy cycle at four key points - Policy definition; Management and scenario building; Reporting requirements; Alarm functions. The workshop identified the 44 Essential Climate Variables defined by GCOS as the minimum set of standardised climate data that the commission should be considering and a gap analysis for the provision of these observations was undertaken. In addition European capacity is analysed according to maturity, differentiating between sustained operational capacity (Envelope Missions/EUMETSAT), non-operationally funded repetitive capacity and additional infrastructure needs in order to fill the gaps are identified. Finally the report discusses co-ordination and governance issues and how to overcome them. The key findings and recommendations are contained in an executive summary.JRC.DDG.H.2-Climate chang

An in-depth case study of a modular service delivery system in a logistics context

Purpose: The objective of this work is to empirically investigate the design of a service delivery system that supports the provision of modular service logistics offerings. Methodology: An in-depth single case study relying on interview data and extensive documentary evidence is carried out in the B2B logistics sector. Three main analytical techniques are used to make sense of the qualitative data: thematic analysis, process mapping and the application of modular operators. Findings: A modular service delivery system comprises three types of processes that collectively deliver modular offerings. First, the platform consists of core processes that enable the collection, transport, and delivery of physical items for all offerings (modular and non-modular). Second, dedicated modular processes are mandatory and exclusive to individual modular offerings. Third, optional modular processes are shared across several modular offerings. Moreover, interfaces regulate physical (e.g., parcels or parts) and information (e.g., booking data) inputs provided by the customer in order to control the interdependencies within these different process types. Practical implications: The identification of three process types and their interdependencies provides detailed insights into how managers can design modular logistics services that benefit from economies of scale and meet increasingly variable customer requirements. The importance of well-designed interfaces among the customer, the service offering, and the service delivery system is highlighted. Originality/value: This study exends previous modularity studies in service logistics. It applies modular operators to determine the presence of modularity in the service delivery system and to establish the role of different process types in enabling modularity in the service delivery system