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Cognitive Work Analysis (CWA) has proved successful in supporting Human Factors analysis, providing a system-level view of operations that can be used to understand how systems achieve their missions. However, a critical gap exists in the transition from CWA to prototype design and implementation. The aim of this paper is to fill this gap between CWA and implementation. This paper describes an approach for the design of software system in which CWA descriptions are converted to Unified Modeling Language (UML) models. The approach presented in this paper is intended to be minimalistic and streamlined, to focus on the design of a prototype. Following the design process, a Decision Aid prototype was developed. This prototype is evaluated against the original CWA to check that the translation has been effective. This paper shows how CWA can be integrated with UML for prototype design and implementation. We believe that this paper should prove useful to a range of practitioners concerned about maintaining a user's cognitive perspective during specification and analysis of a system. [ABSTRACT FROM AUTHOR]

Distance learning (DL) is undergoing a rapid growth in academia, business, industry, and the military. Recent technological developments in computer-based training, along with shrinking internal resources, and rising industry interest in sustainable workforce development, provide a strong impetus for DL investments. Due to the multiplicity of efforts involved in planning and executing a DL program, it is imperative that organizations view this nontraditional mode of knowledge transfer from a systems perspective. This paper presents a coordination-centric systems framework for implementing a DL program using the SIMILAR systems engineering process. The paper also suggests linking SIMILAR to two complementary models, Triple C and D-E-J-I, to enhance the overall systems approach. Implementing DL from a systems view aids in identifying the interrelating components, resource interfaces, and improvements needed in techniques used to deliver educational material at a distance. The proposed framework is effective in assisting DL instructors, students, administrators, and other stakeholders to improve the learning environment and manage the complex interaction of people, technology, and instructional processes. Because of its large and diverse operational base, the military is embracing DL programs aggressively. An example is presented of the DL program for graduate systems engineering program at the Air Force Institute of Technology (AFIT). © 2011 Wiley Periodicals, Inc. Syst Eng [ABSTRACT FROM AUTHOR]

This paper addresses the challenges facing the three different groups within the professional community that support the development of large-scale scientific and engineering (CSE) software applications. Scientific and engineering systems are but one example of large-scale complex (LSC) systems. The authors recognize that many of the observations made in this paper also apply to the larger domain. The focus of this paper is restricted to CSE because it is the source of the experiences from which the observations are derived. The first of the groups encompasses the application developers of large-scale scientific and engineering software systems, especially those requiring high-performance computing (HPC). The second group covers the HPC software development and run-time environments. The third consists of the integrators of the first two groups, with a focus on the systems engineers whose task is to bridge the technical and cultural gap between the other two. These challenges reside in several areas, the most important being the educational and cultural backgrounds that are reflected in the knowledge, expertise, and experience of the principals involved. In particular, the cultural gaps and thus the communications and ultimate systems integration challenges are the byproducts of the academic educational system that graduates most software engineers without formal courses in systems engineering, process control, and systems integration. All three groups of challenges are explored individually and in conjunction with each other. Thus, a major problem addressed here is centered in software, because the developers of LSC systems in CSE perceive hardware through the HPC software development environment. Given the unique attributes and characteristics of LSC-HPC systems, to meet the challenge of the risk modeling, assessment, and management associated with them-at least partially-this paper discusses two complementary approaches: decomposition and hierarchical modeling, which, when applied in conjunction with conventional aggregate modeling methods, offers several promising advantages, especially when dealing with LSC-HPC systems, and Phantom System Models, used as a real-time and virtual modeling laboratory for systems integration and risk assessment and management. © 2009 Wiley Periodicals, Inc. Syst Eng [ABSTRACT FROM AUTHOR]

ABSTRACT This paper introduces a conceptual, yet quantifiable, architecture framework by extending the notion of system modularity in its broadest sense. Acknowledging that modularity is not a binary feature and comes in various types and levels, the proposed framework introduces higher levels of modularity that naturally incorporate decentralized architecture on the one hand and autonomy in agents and subsystems on the other. This makes the framework suitable for modularity decisions in Systems of Systems and for analyzing the impact of modularity on broader surrounding ecosystems. The stages of modularity in the proposed framework are naturally aligned with the level of variations and uncertainty in the system and its environment, a relationship that is central to the benefits of modularity. The conceptual framework is complemented with a decision layer that makes it suitable to be used as a computational architecture decision tool to determine the appropriate stage and level of modularity of a system, for a given profile of variations and uncertainties in its environment. We further argue that the fundamental systemic driving forces and trade-offs of moving from monolithic to distributed architecture are essentially similar to those for moving from integral to modular architectures. The spectrum, in conjunction with the decision layer, could guide system architects when selecting appropriate parameters and building a system-specific computational tool from a combination of existing tools and techniques. To demonstrate the applicability of the framework, a case for fractionated satellite systems based on a simplified demo of the DARPA F6 program is presented where the value of transition from a monolithic architecture to a fractionated architecture, as two consecutive levels of modularity in the proposed spectrum, is calculated and ranges of parameters where fractionation increases systems value are determined. [ABSTRACT FROM AUTHOR]

ABSTRACT The government acquisition system is consistently plagued by cost growth and by attempts at acquisition reform. Despite these persistent challenges, the academic community lacks a methodology for studying complex acquisition programs both in-depth and longitudinally throughout their life cycles. In this paper, we present a framework for studying complex acquisition programs that provides researchers with a strategy for systematically studying cost growth mechanisms. The proposed framework provides a means to identify specific technical and organizational mechanisms for cost growth, to organize those mechanisms using design structure matrices, and to observe the evolution of those mechanisms throughout a program's life cycle. To illustrate the utility of our framework, we apply it to analyze a case study of the National Polar-orbiting Operational Environmental Satellite System (NPOESS) program. Ultimately, we demonstrate that the framework enables us to generate unique insights into the mechanisms that induced cost growth on NPOESS and that were unacknowledged by previous studies. Specifically, we observed that complexity was injected into the technical system well before the program's cost estimates began to increase and that it was the complexity of the NPOESS organization that hindered the program's ability to effectively estimate and to manage its costs. [ABSTRACT FROM AUTHOR]

Non‐functional requirements (NFRs) play a significant role in the software development process. However, the classical requirement prioritization methods for incremental software development, typically, consider the attributes of functional features only, often neglecting the non‐functional constraints. This might lead to catastrophic defects in the system design, as the conflicts among the NFRs are ignored. In this paper, a novel prioritization approach for functional requirements (FRs) is introduced within the incremental software development process. The proposed approach considers the conflicts among NFRs, in the prioritization process, to minimize the incon sistencies of software development. The devised NFR‐aware prioritization algorithm can be tuned according to the weights that the analyst assigns to NFR conflicts and FR‐NFR dependencies. We have assessed our prioritization approach using available requirements data sets and have compared the results in different scenarios. [ABSTRACT FROM AUTHOR]

Software Configuration Management (SCM) techniques have been considered the entry point to rigorous software engineering, where multiple organizations cooperate in a decentralized mode to save resources, ensure the quality of the diversity of software products, and manage corporate information to get a better return of investment. The incessant trend of Global Software Development (GSD) and the complexity of implementing a correct SCM solution grow not only because of the changing circumstances, but also because of the interactions and the forces related to GSD activities. This paper addresses the role SCM plays in the development of commercial products and systems, and introduces a SCM reference model to describe the relationships between the different technical, organizational, and product concerns any software development company should support in the global market. © 2012 Wiley Periodicals, Inc. Syst Eng [ABSTRACT FROM AUTHOR]

NASA's Vision for Space Exploration and the missions it comprises pose large-scale systems-engineering problems with concomitant large-budget investment decisions involving multiple disciplines (e.g., science, engineering, information technology), multiple constraints (e.g., time, mass, energy consumption), myriad uncertainties, and a hierarchical structure of problem decomposition with resolution of increasing fidelity. Navigation through this sea of complexity is greatly facilitated by an analytical system that includes optimization and analysis software tools. The interplay between program planning and decision-support tools is seen here in a case study of a hypothetical mission on the Moon. The architecture of one such tool, HURON, is discussed and its application is illustrated in a comparison of the relative productivity of employing two pressurized or two unpressurized robotic rovers with two pairs of astronauts to conduct a specified group of activities. For the mission scenarios studied, a pair of pressurized rovers is shown to be significantly more productive than a pair of unpressurized rovers when calculating work accomplished divided by marginal operational costs. The HURON decision-support system presented and successfully applied in this paper deals explicitly with combinatorial explosion of a huge design space in scheduling the activities of agents subject to constraints, deploys a productivity function as a measure of value, and automatically determines a ranked sensitivity list of important inputs. The approach is applicable to a wide class of large-scale systems-engineering applications. © 2009 Wiley Periodicals, Inc. Syst Eng [ABSTRACT FROM AUTHOR]

Abstract: Systems engineering in 2018 has many challenges, both to build the complex systems of systems of the future, and to build the complex systems of which they are composed. Systems engineering needs to be able to design around stable requirements when there are long‐lead manufactured items to be incorporated, and also needs to be able to evolve the design along with evolving requirements for larger systems. The “systems engineering of yesterday,” which, when done well, greatly enhanced the design and use of stand‐alone systems, has to be extended to adequately cover evolving systems of systems, being agile and resilient and responsive. This paper compares articles in 1 year of the first 5 years and 1 year of the last 5 years out of the 20‐year history of the Systems Engineering journal, and considers generality via lexicographic trend analysis. Based on the topics addressed by the articles in each year, there is more interest today in the larger system (e.g., economics, simulation of the environment, systems‐of‐systems), on quality attributes (more often called “ilities” or life‐cycle properties in systems engineering ) and on modeling, management, and technology maturity. There is less interest today in process and requirements. These can be explained by systems engineering having moved away from initially deeply‐explored topics into new areas. [ABSTRACT FROM AUTHOR]

Design patterns and architecture patterns have been considerably promoted by software engineering. The software oriented tools and methods have been adapted for systems engineering, conforming to the model driven engineering paradigm proposed by the Object Management Group. However, designers of complex sociotechnical systems have specific concerns, which differ from those of software designers. We propose a method of pattern implementation for systems engineering, based on a functional approach and relying on formal conceptual foundations in the form of a meta-model, which can be used for the management, application, and cataloguing of patterns specific to the field of systems engineering. A pattern instance in the field of control systems is proposed as an example application: © 2012 Wiley Periodicals, Inc. Syst Eng [ABSTRACT FROM AUTHOR]

In recent years, cyber‐physical systems (CPS) have been widely used in different problem domains. The hardware and software components in a CPS are deeply intertwined at various levels of abstraction under changing contexts to achieve the desired goals. One way to manage this complexity is through the use of modular architecture that enables portions of a CPS to be upgraded, replaced, or fixed in a plug‐and‐play manner. In practice, nominally modular architectures depart from this ideal. Thus, there is a need to identify, measure, and understand the causes of these departures. Techniques have been developed to accomplish this for pure software systems, but can these techniques be adapted to infer hardware‐related modularity violations in a CPS? To investigate this question, we adapted methods from pure‐software systems and analyzed two open‐source CPS: OpenWrt and MD PnP. We found that the software architecture of these systems is well modularized. However, we were able to detect and measure modularity violations associated with hardware and other domain‐related concepts. Furthermore, software components related to hardware were more likely to change frequently compared to general software components. Together, these findings suggest that it is feasible to identify a subset of hardware‐driven modularity violations using techniques adapted from pure software systems. [ABSTRACT FROM AUTHOR]

Component‐level system design first builds a design trade space of alternate solutions composed of one or more system function allocations (or partitions) to one or more physical hardware or software product component configurations. Alternate solutions are then analyzed to select a near‐optimal solution that satisfies all system requirements. The past two or more decades have seen much research into solution of the hardware/software partitioning problem. A traditional assumption has been that software executes on a single processing resource, whereas modern computer systems provide a heterogeneous combination of processing resources. These processing technologies enable performance (speed) optimization through algorithm parallelization at the expense of potentially conflicting power and thermal concerns. Current research focuses primarily on function partitioning with heterogeneous processors to achieve performance optimization. There still exists the problem of quantifying function partitioning for additional architecture attributes (electrical energy, thermal, reliability, etc.). This article presents an extensible, executable model‐based system engineering framework that supports these architecture attributes. A proof‐of‐concept executable performance attribute model for single‐CPU systems is presented that produces static performance estimates to support optimization analysis and dynamic estimates for simulation analysis. This model‐based method replaces current spreadsheet approaches for architecture analysis of alternatives. Improved performance estimation reduces the need for prototype development, saving time and money. Improved architecture attribute estimates foster early communication with specialty engineers, improving design through better informed trade‐offs. Design space exploration fidelity is improved through the ability to easily model computer resource alternatives. [ABSTRACT FROM AUTHOR]

The purpose of the study was to gain a greater understanding of the use of Systems Practice among engineers working in the Rolls-Royce Defence Sector at its Bristol site and develop hypotheses about its use. This study is part of a larger project to investigate and improve the use and embedding of Systems Practice among engineers at the site. The current situation was studied using a combination of grounded theory and system dynamics, supported by the use of a computer-aided qualitative data analysis software (CAQDAS) package. The results from this work show that Systems Practice is valued as a way of enabling quality in design but engineers find it challenging to adopt because of (i) lack of stakeholder appreciation of its value, (ii) their lack of experience with Systems Engineering, and (iii) logistical issues with its application. This work will be followed by group model building sessions to further develop the findings by identifying interventions to create and assess improvement in Systems Practice, in particular finding errors earlier in the design lifecycle. ©2012 Wiley Periodicals, Inc. Syst Eng 16 [ABSTRACT FROM AUTHOR]