Book Review of Systems Engineering for the Digital Age: Practitioner Perspectives

MARCH 2024 I Volume 45, Issue 1

Book Review of Systems Engineering for the Digital Age: Practitioner Perspectives

Editor: Dinesh Verma 

Available on Amazon

Reviewed by:  Mark A. London, Ph.D. 

Adjunct Assistant Professor of Systems Engineering 

Embry-Riddle Aeronautical University

The growth of Model-Based Systems Engineering (MBSE) has formed a broad foundation for the expansion of digital tool development and integration in the systems engineering process. This expansion has, in recent years, coalesced into the field of digital engineering. The present book under review, Systems Engineering for the Digital Age: Practitioner Perspectives, edited by Dinesh Verma, provides a useful overview of digital engineering concepts and practices, and presents insightful, practical applications of digital engineering within the systems engineering environment as well as coverage of specific fields such as risk analysis, systems safety, and analytic methods. From his biographical statement on the Systems Engineering Research Center (SERC) website, we note Dr. Verma’s credentials include serving as the Founding Dean of the School of Systems and Enterprises at Stevens Institute of Technology from 2007 through 2017. He currently serves as the Executive Director of SERC, a US Department of Defense-sponsored University Affiliated Research Center (UARC) focused on systems engineering research. Dr. Verma served as Scientific Advisor to the Director of the Embedded Systems Institute in Eindhoven, Holland, from 2003 through 2008. Prior to this role, he served as Technical Director at Lockheed Martin Undersea Systems in Manassas, Virginia, in the area of adapted systems and supportability engineering processes, methods, and tools for complex system development. 


As noted in the book’s Preface, this book features a total of 41 chapters organized into eight topical clusters. It has been written with the practitioner community of engineers and systems engineers in mind and emphasizes a pragmatic and utilitarian orientation. The chapter lengths have been kept reasonable and well-balanced in terms of the breadth and depth of the content matter. In addition, the book has an accompanying website ( with additional materials organized in a manner consistent with the organization of this book. Each of these chapter clusters was organized and edited by the associated cluster leaders. Every one of the cluster leaders has been a principal investigator on multiple research projects within SERC. A brief description of each of the eight topical areas is provided below. 

  • Part I: Transforming Engineering Through Digital and Model-Based Methods (chapters 1-5). The book opens with Chapter 1, which describes the overarching concept of digital engineering (DE), with four subsequent chapters introducing various facets of DE, including the use of DE models, methods, tools, and technologies to transform the traditional document-based approach for requirements generation and management. Chapter 2 describes applications of DE modeling techniques for several publicly available use cases, including an industry scan to determine the optimal approaches for applying modeling process, methods and tools. Chapter 3 formally introduces the Digital Engineering Framework for Integration and Interoperability (DEFII) as a methodological foundation for the use of ontologies and graph data structures in a digital engineering context. Chapter 4  proceeds to consider how data visualization can transform the interactions between stakeholders and engineers.  
  • Part II: Executing Digital Engineering (chapters 6-12). This second cluster of chapters proceeds to consider how DE is executed within the context of complex system-of-systems. Chapter 6 addresses the challenges of the Fourth Industrial Revolution (with systems engineering being a driving factor) as well as increasing system complexity. Gaps in existing SE methods are described which are particularly amenable to transformation and support through digital engineering. Chapters 7 and 8 describe the collaboration by SERC with the Digital Engineering Measures Working Group to create a formal measurement framework for this digital transformation, emphasizing value-creation research on methods, processes, and frameworks that support decision capabilities. Chapters 9 and 10 describe the application of DE to acquisition processes, including the scaling of contracting processes within larger enterprise organizations. Chapter 11 provides practitioners with an approach to verifying and validating existing system behavior specifications using the Monterey Phoenix (MP) toolset, which leverages aspects of SysML attributes. Chapter 12 concludes this cluster of chapters with a case study from the Joint Program Executive Office for Chemical, Biological, Radiological, and Nuclear Defense (JPEO-CBRND). 
  • Part III: Tradespace Analysis in a Digital Engineering Ecosystem–Context and Implications (chapters 13-17). Leveraging the foundation laid in the prior chapter clusters, Chapter 13 introduces concepts to address specific needs across the Defense enterprise, including the highly challenging problem of system qualities (the “-ilities”), which represent major stakeholder needs. Chapter 14 presents a complete trade-space analysis framework and a summary of key lessons learned to realize a successful trade-space analysis for complex systems. Chapter 16 describes an approach to implementing system resilience functions and reducing the risk of disruptive events that degrade performance and dependability. Finally, chapter 17 presents a methodological framework for effectively exploiting AI in systems engineering, especially for human-machine-engineered systems.   
  • Part IV: Evaluating and Improving System Risk (chapters 18-21). The fourth chapter cluster focuses principally on system reliability and risk considerations. Chapter 18 introduces engineered systems’ complexity in relation to system risk and describes some examples of current and previous efforts to capture and model complexity. Chapter 19 introduces the concept of Technical Debt (TD), which refers to short-term compromises in software artifacts that make future refactoring or maintenance very expensive. Technology Readiness Levels (TRLs) and System Readiness Levels (SRLs) are presented in Chapter 20, with a corresponding discussion on how these system maturity assessments can then be correlated to the decisions regarding the potential acquisition of systems. The final chapter of this cluster covers various risk assessment methods. 
  • Part V: Model-Based Design of Safety, Security, and Resilience Systems (chapters 22-27). This cluster of chapters proceeds from system risk to system safety and resilience design considerations. Chapter 22 evaluates historical and contemporary methods to support system assurance and the limits of traditional system assurance methods. Chapter 23 presents the Systems-Theoretic Accident Model and Process (STAMP) model, which enables decision-makers to improve a system’s safety, resilience, and security. The subsequent chapters, 24-26, consider system awareness concerns for cyber-resilience and meta-models for improving cyber-resilience design and development. A case study demonstrating the implementation of these approaches is featured in chapter 27.   
  • Part VI: Analytic Methods for Design and Analysis of Missions and Systems-of-Systems (chapters 28-33). Chapter 28 introduces analytical methods for the design and analysis of complex systems-of-systems (SoS). It addresses questions about the unique challenges such systems pose for the systems engineer. A SoS analytics workbench is presented in Chapter 29, which provides a set of computational tools to facilitate improved decision-making for newer SoS architectures. Computational intelligence approaches to the field of meta-architecting are presented in chapter 31, with recommendations for mission engineering and technology insertion in large corporate enterprise systems, which are considered in chapters 32-33.  
  • Part VII: Applying Systems Engineering to Enterprise Systems and Portfolio Management (chapters 34-37). This penultimate chapter cluster takes up where the prior cluster ended by covering enterprise systems and portfolio management. Twelve major systems engineering management challenges are posed in Chapter 34, and the urgency to meet these challenges is affirmed by the need to support proper information technology and knowledge management practices. A decision framework is introduced in Chapter 35 that effectively enables flexibility and agility while providing some general guidance on optimal solution methods for portfolio management. Chapter 36  continues this discussion with an overview of emerging research in portfolio optimization and data visualization techniques. Particular emphasis on ongoing SERC research is considered in chapter 37, with historical motivation and transfer of modular system methods to the broader SoS perspectives being notable discussion areas.   
  • Part VIII: Systems Education and Competencies in the Age of Digital Engineering, Convergence, and AI (chapters 38-41). This final chapter cluster moves away from systems engineering proper and looks at ongoing educational initiatives. An overview of the SEBoK is presented in chapter 38, with the subsequent chapter focused on career guidance and opportunities for systems engineers. Chapter 40 discusses the current structure of systems engineering university programs in the United States, and the final chapter discusses the Capstone Marketplace, an in-development tool to support the knowledge development and application of systems engineering to other engineering disciplines.  

Reviewer Assessment 

This book represents a broad and deep swath of the contemporary systems engineering landscape with appropriate emphasis on newly developing fields like digital engineering. The book does a good job of presenting and discussing newer trends in digital engineering and how this discipline builds upon and expands the capabilities developed under earlier efforts in Model-Based Systems Engineering (MBSE). In addition, the chapter treatments provide a sound and practical application of these newer capabilities to the various needs of systems engineers to effectively model complex systems and support their design, development, and deployment across their representative acquisition lifecycle phases. Sufficient technical explanation is provided but within the context of relatively short and concise chapters that prevent the discussion from becoming tedious or pedantic. This balance between technical description and practical application of these concepts and tools is the principal value of this book. On a personal note, the present reviewer found the book to be an enjoyable read. However, perhaps with a little too much emphasis in some places on the specific research areas supported by SERC—although given the authorship of the chapters and the editor’s background, such considerations are easily overlooked. Nevertheless, the content is well-organized and clearly presented. The chapter on TRLs and SRLs (chapter 20) by Brian Sauser was particularly interesting to this reviewer, given his academic research interest in this topic area.  

Value to the T&E Community 

Besides the technical overview and the prior reviewer comments, one is compelled when doing a book review for the ITEA Journal to ask why a test engineer should read this book. Several reasons for interest and engagement by the test community come to mind. First, the initial cluster of chapters presents a wealth of current research on digital engineering, which enables the exploration of continued integration of test and evaluation earlier in the systems development process. For example, there are significant foundational test perspectives in Chapters Six and Nine, followed by new initiatives in testing for resilience in Chapter 25 and some combinatorial test design in Chapter 36. 

The development of newer modeling approaches to evaluate systems more thoroughly within the digital domain suggests opportunities to broaden testing engagement “early and often” in the system lifecycle. Second, using and applying these newer digital tools enables frequent testing of systems, especially those related to cyber-resilience or cyber-physical systems, which can help drive early design changes. Integrating digital testing techniques within Agile/Scrum system design paradigms may prove particularly effective in identifying and correcting system design flaws earlier in a system’s development. Third, a proper understanding of the role of digital engineering and its application across the systems engineering domain will prove valuable to the T&E engineer to better identify the critical points where system testing can influence design and development decisions within the system lifecycle. Fourth expanded digital testing capabilities can provide an increased understanding of how system testing across the digital and physical domains can be mutually reinforcing to enable more robust testing and requirements V&V activities. Finally, proper consideration of the digital engineering capabilities by the T&E community can support system testing in environments or system configurations that cannot be safely or conveniently tested at the physical incarnation level.  

Nevertheless, the book has some T&E-related weaknesses. Section VIII of the book continues a long-standing problem with US systems engineering programs and INCOSE’s SEBoK by continuing to subsume T&E under systems verification and validation processes, thereby failing to address V&V or T&E as distinct disciplines explicitly. In addition, Chapter 40 lists communities of interest related to systems engineering and yet does not mention ITEA. Moreover, the natural language program (NLP) analysis of major US systems engineering programs identifies no theme concerning T&E or even the more general terms of verification and validation in its top ten clusters, nor do existing V&V and T&E challenges discussed as critical and necessary skills for future systems engineer, despite the advent of AI-enabled systems with fundamental V&V and T&E ramifications.  

Even with these limitations in mind, this book provides a thorough and robust addition to the systems engineering body of knowledge and provides useful insights into the T&E role and practice within the digital engineering environment and how such newer capabilities can expand and improve system testing robustness and comprehensiveness across the system lifecycle. If testers are to “shift left” in philosophy and be effectively engaged early in a system’s development lifecycle, then this book fills a useful knowledge cap to enable the test community to implement this test philosophy better.  

Mark A. London, Ph.D., has earned B.S. and M.S. degrees in electrical engineering from the Pennsylvania State University and a Ph.D. in systems engineering from George Washington University. He is an Adjunct Assistant Professor in Systems Engineering at Embry-Riddle Aeronautical University-Worldwide Campus and is the Chief Operating Officer at T. C. Defense ( Dr. London has extensive experience in systems engineering and T&E of a variety of advanced electro-optical and infrared systems. His ongoing research interests include the integration of Bayesian statistics into flight testing operations and the application of graph-theory mathematical concepts for system modeling and performance analysis  

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