The Experts below are selected from a list of 4665 Experts worldwide ranked by ideXlab platform

Brian Henderson-sellers - One of the best experts on this subject based on the ideXlab platform.

  • A method to build information Systems Engineering Process metamodels
    Journal of Systems and Software, 2009
    Co-Authors: Agnès Front, D.b Rieu, Brian Henderson-sellers
    Abstract:

    Several Process metamodels exist. Each of them presents a different viewpoint of the same information Systems Engineering Process. However, there are no existing correspondences between them. We propose a method to build unified, fitted and multi-viewpoint Process metamodels for information Systems Engineering. Our method is based on a Process domain metamodel that contains the main concepts of information Systems Engineering Process field. This Process domain metamodel helps selecting the needed metamodel concepts for a particular situational context. Our method is also based on patterns to refine the Process metamodel. The Process metamodel can then be instantiated according to the organisation's needs. The resulting method is represented as a pattern system.

  • A method to build information Systems Engineering Process metamodels
    Journal of Systems and Software, 2009
    Co-Authors: Charlotte Hug, D.b Rieu, Agnès Front, Brian Henderson-sellers
    Abstract:

    Several Process metamodels exist. Each of them presents a different viewpoint of the same information Systems Engineering Process. However, there are no existing correspondences between them. We propose a method to build unified, fitted and multi-viewpoint Process metamodels for information Systems Engineering. Our method is based on a Process domain metamodel that contains the main concepts of information Systems Engineering Process field. This Process domain metamodel helps selecting the needed metamodel concepts for a particular situational context. Our method is also based on patterns to refine the Process metamodel. The Process metamodel can then be instantiated according to the organisation's needs. The resulting method is represented as a pattern system. © 2009 Elsevier Inc. All rights reserved.

Agnès Front - One of the best experts on this subject based on the ideXlab platform.

  • A method to build information Systems Engineering Process metamodels
    Journal of Systems and Software, 2009
    Co-Authors: Agnès Front, D.b Rieu, Brian Henderson-sellers
    Abstract:

    Several Process metamodels exist. Each of them presents a different viewpoint of the same information Systems Engineering Process. However, there are no existing correspondences between them. We propose a method to build unified, fitted and multi-viewpoint Process metamodels for information Systems Engineering. Our method is based on a Process domain metamodel that contains the main concepts of information Systems Engineering Process field. This Process domain metamodel helps selecting the needed metamodel concepts for a particular situational context. Our method is also based on patterns to refine the Process metamodel. The Process metamodel can then be instantiated according to the organisation's needs. The resulting method is represented as a pattern system.

  • A method to build information Systems Engineering Process metamodels
    Journal of Systems and Software, 2009
    Co-Authors: Charlotte Hug, D.b Rieu, Agnès Front, Brian Henderson-sellers
    Abstract:

    Several Process metamodels exist. Each of them presents a different viewpoint of the same information Systems Engineering Process. However, there are no existing correspondences between them. We propose a method to build unified, fitted and multi-viewpoint Process metamodels for information Systems Engineering. Our method is based on a Process domain metamodel that contains the main concepts of information Systems Engineering Process field. This Process domain metamodel helps selecting the needed metamodel concepts for a particular situational context. Our method is also based on patterns to refine the Process metamodel. The Process metamodel can then be instantiated according to the organisation's needs. The resulting method is represented as a pattern system. © 2009 Elsevier Inc. All rights reserved.

D.b Rieu - One of the best experts on this subject based on the ideXlab platform.

  • A method to build information Systems Engineering Process metamodels
    Journal of Systems and Software, 2009
    Co-Authors: Agnès Front, D.b Rieu, Brian Henderson-sellers
    Abstract:

    Several Process metamodels exist. Each of them presents a different viewpoint of the same information Systems Engineering Process. However, there are no existing correspondences between them. We propose a method to build unified, fitted and multi-viewpoint Process metamodels for information Systems Engineering. Our method is based on a Process domain metamodel that contains the main concepts of information Systems Engineering Process field. This Process domain metamodel helps selecting the needed metamodel concepts for a particular situational context. Our method is also based on patterns to refine the Process metamodel. The Process metamodel can then be instantiated according to the organisation's needs. The resulting method is represented as a pattern system.

  • A method to build information Systems Engineering Process metamodels
    Journal of Systems and Software, 2009
    Co-Authors: Charlotte Hug, D.b Rieu, Agnès Front, Brian Henderson-sellers
    Abstract:

    Several Process metamodels exist. Each of them presents a different viewpoint of the same information Systems Engineering Process. However, there are no existing correspondences between them. We propose a method to build unified, fitted and multi-viewpoint Process metamodels for information Systems Engineering. Our method is based on a Process domain metamodel that contains the main concepts of information Systems Engineering Process field. This Process domain metamodel helps selecting the needed metamodel concepts for a particular situational context. Our method is also based on patterns to refine the Process metamodel. The Process metamodel can then be instantiated according to the organisation's needs. The resulting method is represented as a pattern system. © 2009 Elsevier Inc. All rights reserved.

Charlotte Hug - One of the best experts on this subject based on the ideXlab platform.

  • A method to build information Systems Engineering Process metamodels
    Journal of Systems and Software, 2009
    Co-Authors: Charlotte Hug, D.b Rieu, Agnès Front, Brian Henderson-sellers
    Abstract:

    Several Process metamodels exist. Each of them presents a different viewpoint of the same information Systems Engineering Process. However, there are no existing correspondences between them. We propose a method to build unified, fitted and multi-viewpoint Process metamodels for information Systems Engineering. Our method is based on a Process domain metamodel that contains the main concepts of information Systems Engineering Process field. This Process domain metamodel helps selecting the needed metamodel concepts for a particular situational context. Our method is also based on patterns to refine the Process metamodel. The Process metamodel can then be instantiated according to the organisation's needs. The resulting method is represented as a pattern system. © 2009 Elsevier Inc. All rights reserved.

Siyuan Ji - One of the best experts on this subject based on the ideXlab platform.

  • A Product Line Systems Engineering Process for Variability Identification and Reduction
    IEEE Systems Journal, 2019
    Co-Authors: Mole Li, Alan Grigg, Charles E. Dickerson, Lin Guan, Siyuan Ji
    Abstract:

    Software product line Engineering has attracted attention in the last two decades due to its promising capabilities to reduce costs and time to market through the reuse of requirements and components. In practice, developing system level product lines in a large-scale company is not an easy task as there may be thousands of variants and multiple disciplines involved. The manual reuse of legacy system models at domain Engineering to build reusable system libraries and configurations of variants to derive target products can be infeasible. To tackle this challenge, a product line Systems Engineering Process is proposed. Specifically, the Process extends research in the system orthogonal variability model to support hierarchical variability modeling with formal definitions; utilizes Systems Engineering concepts and legacy system models to build the hierarchy for the variability model and to identify essential relations between variants; and finally, analyzes the identified relations to reduce the number of variation points. The Process, which is automated by computational algorithms, is demonstrated through an illustrative example on generalized Rolls-Royce aircraft engine control Systems. To evaluate the effectiveness of the Process in the reduction of variation points, it is further applied to case studies in different Engineering domains at different levels of complexity. Subjected to system model availability, reduction of 14%–40% in the number of variation points is demonstrated in the case studies.

  • A Product Line Systems Engineering Process for Variability Identification and Reduction.
    arXiv: Software Engineering, 2018
    Co-Authors: Mole Li, Alan Grigg, Charles E. Dickerson, Lin Guan, Siyuan Ji
    Abstract:

    Software Product Line Engineering has attracted attention in the last two decades due to its promising capabilities to reduce costs and time to market through reuse of requirements and components. In practice, developing system level product lines in a large-scale company is not an easy task as there may be thousands of variants and multiple disciplines involved. The manual reuse of legacy system models at domain Engineering to build reusable system libraries and configurations of variants to derive target products can be infeasible. To tackle this challenge, a Product Line Systems Engineering Process is proposed. Specifically, the Process extends research in the System Orthogonal Variability Model to support hierarchical variability modeling with formal definitions; utilizes Systems Engineering concepts and legacy system models to build the hierarchy for the variability model and to identify essential relations between variants; and finally, analyzes the identified relations to reduce the number of variation points. The Process, which is automated by computational algorithms, is demonstrated through an illustrative example on generalized Rolls-Royce aircraft engine control Systems. To evaluate the effectiveness of the Process in the reduction of variation points, it is further applied to case studies in different Engineering domains at different levels of complexity. Subject to system model availability, reduction of 14% to 40% in the number of variation points are demonstrated in the case studies.