Semantic Integration Engine: A BoK Integration Demo for the AI Era

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      "text": "ns and structural descriptions. This allows AI to understand the meaning of the model, thereby assisting in generation and validation. Furthermore, in addition to the literate model and DSL, the Body of Knowledge (BoK) developed by SimpleModeling serves as the foundation for circulating knowledge between models and AI. Literate Model–Driven AI-Assisted Development Literate model–driven AI-assisted development is a development approach in which AI supports tasks such as design, generation, and verification based on a literate model that integrates natural language with formal specifications. In this approach, the literate model functions as a shared foundation for both human understanding and machine processing, allowing AI to enhance the consistency and efficiency of development processes ",
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      "text": "in large-scale applications, it is difficult to represent all functions solely through DSLs and models, requiring manual supplementation for parts that fall outside specifications or unique implementation elements. At this point, the key idea is to decompose functionality structurally and combine it in reusable units. In other words, the CBD approach complements the limitations of models and DSLs, serving as the key to enabling large-scale development. What Is a Component The Unified Process (UP) is based on Component-Based Development (CBD), and in UML, a component is positioned as a unit that defines contracts and interfaces. A component encapsulates functionality as a reusable and replaceable design unit. In SimpleModeling, it is redefined as a unit that can be directly handled by AI an",
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      "text": "d the literate model. Furthermore, a component is positioned at the intersection of the logical and physical models. On the logical model side, it serves as an abstract structural unit that defines responsibilities, contracts, and collaborations. On the physical model side, it materializes as implementation, deployment, and operational units such as modules, services, or deployable artifacts. Viewpoint Logical Model Physical Model Definition Abstract unit with responsibilities, contracts, and dependencies Concrete entities such as code, binaries, or services Purpose Structuring for functional separation and reuse Configuration management for deployment, execution, and integration Connections Collaboration and dependencies among models APIs, messaging, and deployments Thus, a component func",
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      "text": "Component-Based Development in the Age of AI ASAMI, Tomoharu Created: 2025-10-06 Building on the significance of DSL (Domain Specific Language)-driven development in the AI era, this article reconsiders AI-assisted Component-Based Development centered on the literate model (see 📄 AI-Driven Program Generation ― Possibilities and Challenges for details). Literate Model and CBD SimpleModeling adopts Component-Based Development (CBD) as the core of its development methodology. By leveraging the literate model, design information and specifications can be integrated into a form understandable by both humans and AI, enabling structured and consistent development with AI assistance. A literate model is a representational form that integrates natural-language explanations with formal specificatio",
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      "text": "ty with existing component assets. AI Across the Software Lifecycle In the AI era of Component-Based Development (CBD), AI is expected to contribute across the entire software development lifecycle. AI will function not merely as a generation tool but as a collaborative engineering partner. Because CBD is based on clearly defined structural units called components, it is particularly well-suited for AI assistance. Each component explicitly defines responsibilities, contracts, inputs/outputs, and dependencies, making them easy for AI to analyze and optimize. As a result, design, verification, and integration can be effectively automated. Furthermore, by combining SimpleModeling’s Body of Knowledge (BoK), AI can reference past design knowledge, modeling examples, and implementation patterns ",
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