Doug Rosenberg

From the beginning of software time, people have wondered why it isn’t possible to accelerate software projects by simply adding staff. This is sometimes known as the “nine women can’t make a baby in one month” problem. The most famous treatise declaring this to be impossible is Fred Brooks’ 1975 book The Mythical Man-Month, in which he declares that “adding more programmers to a late software project makes it later,” and indeed this has proven largely true over the decades. Aided by a domain-driven code generator that quickly creates database and API code, Parallel Agile (PA) achieves significant schedule compression using parallelism: as many developers as necessary can independently and concurrently develop the scenarios from initial prototype through production code. Projects can scale by elastic staffing, rather than by stretching schedules for larger development efforts. Schedule compression with a large team of developersworking in parallel is analogous to hardware acceleration of compute problems using parallel CPUs. PA has some similarities with and differences from other Agile approaches. Like most Agile methods, PA "gets to code early" and uses feedback from executable software to drive requirements and design. PA uses technical prototyping as a risk-mitigation strategy, to help sanity-check requirements for feasibility, and to evaluate different technical architectures and technologies. Unlike many Agile methods, PA does not support "design by refactoring," and it doesn't drive designs from unit tests. Instead, PA uses a minimalist UML-based design approach (Agile/ICONIX) that starts out with a domain model to facilitate communication across the development team, and partitions the system along use case boundaries, which enables parallel development. Parallel Agile is fully compatible with the Incremental Commitment Spiral Model (ICSM), which involves concurrent effort of a systems engineering team, a development team, and a test team working alongside the developers. The authors have been researching and refining the PA process for several years on multiple test projects that have involved over 200 developers. The book’s example project details the design of one of these test projects, a crowdsourced traffic safety system.

From the beginning of software time, people have wondered why it isn’t possible to accelerate software projects by simply adding staff. This is sometimes known as the “nine women can’t make a baby in one month” problem. The most famous treatise declaring this to be impossible is Fred Brooks’ 1975 book The Mythical Man-Month, in which he declares that “adding more programmers to a late software project makes it later,” and indeed this has proven largely true over the decades. Aided by a domain-driven code generator that quickly creates database and API code, Parallel Agile (PA) achieves significant schedule compression using parallelism: as many developers as necessary can independently and concurrently develop the scenarios from initial prototype through production code. Projects can scale by elastic staffing, rather than by stretching schedules for larger development efforts. Schedule compression with a large team of developersworking in parallel is analogous to hardware acceleration of compute problems using parallel CPUs. PA has some similarities with and differences from other Agile approaches. Like most Agile methods, PA "gets to code early" and uses feedback from executable software to drive requirements and design. PA uses technical prototyping as a risk-mitigation strategy, to help sanity-check requirements for feasibility, and to evaluate different technical architectures and technologies. Unlike many Agile methods, PA does not support "design by refactoring," and it doesn't drive designs from unit tests. Instead, PA uses a minimalist UML-based design approach (Agile/ICONIX) that starts out with a domain model to facilitate communication across the development team, and partitions the system along use case boundaries, which enables parallel development. Parallel Agile is fully compatible with the Incremental Commitment Spiral Model (ICSM), which involves concurrent effort of a systems engineering team, a development team, and a test team working alongside the developers. The authors have been researching and refining the PA process for several years on multiple test projects that have involved over 200 developers. The book’s example project details the design of one of these test projects, a crowdsourced traffic safety system.

Unlock the potential of Model-Based Systems Engineering (MBSE) and Artificial Intelligence in "AI Assisted MBSE with SysML: An Integrated Systems/Software Approach." Authored by experts Doug Rosenberg, Tim Weilkiens, and Brian Moberley, this book bridges systems and software engineering, offering a holistic approach to modern engineering challenges. Explore the integration of AI and MBSE with SysML to enhance systems and software design processes. This book provides practical insights and methodologies for leveraging AI in MBSE, making it a resource for engineers, developers, and technical managers. Follow a comprehensive example, the design of a Scanning Electron Microscope, covering both hardware and software development from start to finish. Key Features: - Comprehensive AI Integration: Understand how AI can be integrated into MBSE practices to boost efficiency and accuracy. - Practical Example: Follow a end-to-end case study of a Scanning Electron Microscope to see AI-assisted MBSE in action. - AI Personas: Learn how to interact with various AI personas specialized in different aspects of engineering. - SysML v1 and SysML v2: Get up-to-date with the latest advancements in SysML. - Expert Insights: Benefit from the combined expertise of Doug Rosenberg, Tim Weilkiens, and Brian Moberley, each a thought leader in their field. - Systems Engineering: Requirements modeling, domain modeling, logical/physical architecture, parametric simulation. - Software Engineering: Use case development, code generation for microcontroller code, UI design/wireframing, DBMS integration, and testing. About the Authors: - Doug Rosenberg, founder and CEO of Parallel Agile Inc., has over three decades of experience in software and systems engineering. A pioneer in object-oriented design and a leader in MBSE, Doug offers insights into integrating AI and systems engineering. - Tim Weilkiens, a prominent MBSE consultant, trainer, and member of the executive board of oose, has extensive involvement in the development of SysML and MBSE methodologies. - Brian Moberley, the Chief Model-Based Systems Engineer at STC, an Arcfield Company, is a leading expert in modeling and simulation. His expertise spans defense systems, commercial projects, and digital transformation. Foreword by Dr. Azad M. Madni: Gain insights from a renowned expert in systems engineering and artificial intelligence as he highlights the importance of bridging systems and software engineering through AI.

The groundbreaking book Design Driven Testing brings sanity back to the software development process by flipping around the concept of Test Driven Development (TDD)—restoring the concept of using testing to verify a design instead of pretending that unit tests are a replacement for design. Anyone who feels that TDD is “Too Damn Difficult” will appreciate this book. Design Driven Testing shows that, by combining a forward-thinking development process with cutting-edge automation, testing can be a finely targeted, business-driven, rewarding effort. In other words, you’ll learn how to test smarter, not harder. Applies a feedback-driven approach to each stage of the project lifecycle. Illustrates a lightweight and effective approach using a core subset of UML. Follows a real-life example project using Java and Flex/ActionScript. Presents bonus chapters for advanced DDTers covering unit-test antipatterns (and their opposite, “test-conscious” design patterns), and showing how to create your own test transformation templates in Enterprise Architect.

Software development can go in many different directions...ICONIX Process has a long track record of helping companies avoid analysis paralysis on a multitude of projects, and is best suited for developing web and GUI-based systems. But what if your project has some other complexities? What if you're modeling business processes, or developing with web services, or designing an embedded hardware/software system? Answer: Use one (or more) of the process roadmaps in this book! This book contains a treasure-trove of tailored roadmaps, proven on demanding real-life projects: Business Process Modeling; Service Oriented Architecture (SOA) web service orchestration with BPMN/BPEL; Embedded hardware/software systems designed with SysML; Design Driven Testing of SysML Models; and Algorithmically complex systems. This book will guide you through these roadmaps, illustrating their use by example. From the author of "Use Case Driven Object Modeling with UML".