Estimating Systems Engineering Reuse

Systems engineering reuse is the utilization of previously developed systems engineering products or artifacts such as architectures, requirements, and test plans across different projects. Such reuse is intended as a means of reducing development cost, project schedule, or performance risk, by avoiding the repetition of some systems engineering activities. Although projects involving systems engineering reuse are becoming more frequent, models or tools for estimating the cost, benefit, and overall impact on a project as a result of reusing products or artifacts have not yet been adequately developed. This paper provides an overview of systems engineering reuse and recent developments with the Constructive Systems Engineering Cost Model (COSYSMO) to estimate the effect of reuse on systems engineering effort. The overview of systems engineering reuse includes a review of how reuse is handled in other domains and results from an industry survey. The recent developments in COSYSMO presents on-going research in the creation of a reuse extension for the model such as the identification of categories of systems engineering reuse, reuse extensions for the size drivers in the model, and a revised set of cost drivers

Advances in knowledge-based software engineering

The underlying hypothesis of this work is that a rigorous and comprehensive software reuse methodology can bring about a more effective and efficient utilization of constrained resources in the development of large-scale software systems by both government and industry. It is also believed that correct use of this type of software engineering methodology can significantly contribute to the higher levels of reliability that will be required of future operational systems. An overview and discussion of current research in the development and application of two systems that support a rigorous reuse paradigm are presented: the Knowledge-Based Software Engineering Environment (KBSEE) and the Knowledge Acquisition fo the Preservation of Tradeoffs and Underlying Rationales (KAPTUR) systems. Emphasis is on a presentation of operational scenarios which highlight the major functional capabilities of the two systems

A Product Line Systems Engineering Process for Variability Identification and Reduction

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.Comment: 12 pages, 6 figures, 2 tables; submitted to the IEEE Systems Journal on 3rd June 201

An ontology framework for developing platform-independent knowledge-based engineering systems in the aerospace industry

This paper presents the development of a novel knowledge-based engineering (KBE) framework for implementing platform-independent knowledge-enabled product design systems within the aerospace industry. The aim of the KBE framework is to strengthen the structure, reuse and portability of knowledge consumed within KBE systems in view of supporting the cost-effective and long-term preservation of knowledge within such systems. The proposed KBE framework uses an ontology-based approach for semantic knowledge management and adopts a model-driven architecture style from the software engineering discipline. Its phases are mainly (1) Capture knowledge required for KBE system; (2) Ontology model construct of KBE system; (3) Platform-independent model (PIM) technology selection and implementation and (4) Integration of PIM KBE knowledge with computer-aided design system. A rigorous methodology is employed which is comprised of five qualitative phases namely, requirement analysis for the KBE framework, identifying software and ontological engineering elements, integration of both elements, proof of concept prototype demonstrator and finally experts validation. A case study investigating four primitive three-dimensional geometry shapes is used to quantify the applicability of the KBE framework in the aerospace industry. Additionally, experts within the aerospace and software engineering sector validated the strengths/benefits and limitations of the KBE framework. The major benefits of the developed approach are in the reduction of man-hours required for developing KBE systems within the aerospace industry and the maintainability and abstraction of the knowledge required for developing KBE systems. This approach strengthens knowledge reuse and eliminates platform-specific approaches to developing KBE systems ensuring the preservation of KBE knowledge for the long term

Flexible Product Line Derivation applied to a Model Based Systems Engineering process

soumis a CSDM 2012Systems engineering enables the successful realization of systems, focusing on defining customer needs early in the development cycle. However there is a lack of methodological support when the development of systems needs to rely on legacy system designs. Furthermore, in the automotive domain, product diversity increases system complexity so much, that reuse becomes much more difficult and time con- suming than usually. We believe a specific strategy must be adopted to prepare for reuse and to achieve systems engineering by reuse. While product line derivation provides the means to obtain single products form a collection of assets, there is still little support for integration with systems engineering practices. In this paper we present an approach which takes into account systems engineering methodolog- ical aspects in product line engineering by rendering the derivation process more flexible. We present the implementation of the tool support for our approach based on the Papyrus1 SysML modeller and exemplify the concepts through a derivation example of the electric parking brake system

A Model-Driven Engineering Approach for ROS using Ontological Semantics

This paper presents a novel ontology-driven software engineering approach for the development of industrial robotics control software. It introduces the ReApp architecture that synthesizes model-driven engineering with semantic technologies to facilitate the development and reuse of ROS-based components and applications. In ReApp, we show how different ontological classification systems for hardware, software, and capabilities help developers in discovering suitable software components for their tasks and in applying them correctly. The proposed model-driven tooling enables developers to work at higher abstraction levels and fosters automatic code generation. It is underpinned by ontologies to minimize discontinuities in the development workflow, with an integrated development environment presenting a seamless interface to the user. First results show the viability and synergy of the selected approach when searching for or developing software with reuse in mind.Comment: Presented at DSLRob 2015 (arXiv:1601.00877), Stefan Zander, Georg Heppner, Georg Neugschwandtner, Ramez Awad, Marc Essinger and Nadia Ahmed: A Model-Driven Engineering Approach for ROS using Ontological Semantic

Extensions of COSYSMO to Represent Reuse

As the maturity of COSYSMO increases, users continue to identify areas in which the model can be improved. Recent emphasis has been placed on the clarification of counting rules for the COSYSMO size drivers. These drivers represent various attributes of the total size of the task of the systems engineering effort estimated by COSYSMO; in terms of person months. The intent of these rules is to ensure consistent interpretation and use of the size input parameters that include: requirements, interfaces, algorithms, and operational scenarios. Experience in applying these rules has exposed a limitation of the current version of the model; there was no way of including the affect of reusing system components in the calculation of systems engineering effort. This has resulted in inaccurate estimates of systems engineering effort for systems that incorporated significant reuse, as in the case of programs with a high degree of COTS integration. As a result, a method was needed to account for the fact that not all of the requirements that drive systems engineering effort are new. Specifically, some of the requirements for a new system may be “reused” from a prior system. Further, some of the new system’s requirements may be “modified” from a prior system. Moreover, the evolution of system requirements over the system life cycle may result in “deleted” requirements from the initial configuration baseline. On the surface, the notion of reuse in COSYSMO may appear as a necessity-is-the-mother-of-invention activity but in reality it was an inevitable feature. One reason is that most software cost estimation models – especially COCOMO II – go into great detail in addressing aspects of software reuse. The other is that reuse is more prevalent among defense contractors that aim for higher productivity gains as they avoid pursuing designs from scratch. For these reasons, this paper provides (1) an approach for handling reuse in systems engineering in terms of the number of systems requirements in COSYSMO, (2) a discussion on the potential cost drivers that could be influenced by reuse, and (3) strategies in which this approach can be extended to include the three other size drivers in the model