2025

ASAMI, Tomoharu

Date	Kind	Event	Category	Title	Summary
2025-12-29	Article	New	Blog	Semantic Integration Engine CLI	This section explains how to use the REST API provided by the Semantic Integration Engine as a CLI (Command Line Interface). By using the CLI, SIE’s semantic search capabilities can be easily accessed from a wide range of execution environments, including shell scripts and generative AI systems.
2025-12-22	Article	New	Blog	Integration between the Semantic Integration Engine and VSCode	This article explains the configuration for using the Semantic Integration Engine (SIE) from VSCode via MCP (Model Context Protocol). Following the REST and ChatGPT integrations, it introduces the design and demo setup for VSCode integration as an entry point for AI-assisted development and knowledge utilization in the local development environment.
2025-12-15	Article	New	Blog	Integration between the Semantic Integration Engine and ChatGPT	This article explains, at the protocol level, what happens when the Semantic Integration Engine and ChatGPT are integrated via MCP (Model Context Protocol), focusing on how ChatGPT uses SIE’s knowledge, performs reasoning, and generates the final response. It provides a detailed explanation from a protocol-level perspective. The important point is that ChatGPT is not requesting “the answer itself” from SIE, but rather retrieving the materials and evidence it needs to reason on its own. In this article, we recreate a simulated MCP session, and examine why SIE’s response structure—concept / passage / graph / score— has a high degree of affinity with the reasoning model of generative AI.
2025-12-15	Article	Update	Domain Modeling	SimpleObject	I removed a sentence that had been left unintentionally.
2025-12-08	Article	New	Blog	Semantic Integration Engine: A BoK Integration Demo for the AI Era	An overview and live demo of the Semantic Integration Engine (SIE), which transforms BoK knowledge into RDF and vector representations for AI-ready semantic retrieval.
2025-12-08	Glossary	New	Glossary	Semantic Integration Engine	An integration engine that unifies structured knowledge (RDF) and document knowledge (SmartDox) derived from the BoK, making them directly accessible to AI.
2025-12-08	Glossary	New	Glossary	fragment IRI	An identifier appended to an IRI in the form #fragment, pointing to a specific section or element inside a document.
2025-12-08	Glossary	New	Glossary	predicate IRI	The IRI identifying the predicate of an RDF triple, defining the semantics of relationships and attributes.
2025-12-08	Glossary	New	Glossary	node IRI	A general term for IRIs that identify nodes in the knowledge graph—concept nodes, document nodes, predicate nodes, etc.
2025-12-08	Glossary	New	Glossary	IRI	A resource identifier used in RDF. It uniquely identifies any resource—concepts, documents, properties—on the Web.
2025-12-08	Glossary	New	Glossary	concept IRI	The IRI identifying a concept. Corresponds to LexiDox terms, BoK concepts, or SmartDox terminology heads.
2025-12-08	Glossary	New	Glossary	document IRI	The IRI identifying a document—SmartDox articles, glossary terms, or other document-level nodes.
2025-12-08	Glossary	New	Glossary	property IRI	The IRI identifying an OWL ObjectProperty or DatatypeProperty. A subtype of predicate IRIs with structural semantics.
2025-12-08	Glossary	New	Glossary	class IRI	The IRI identifying a class in RDFS/OWL. Represents types such as entities, terms, or document categories.
2025-12-08	Glossary	New	Glossary	term IRI	The IRI identifying a term defined in LexiDox. Used for vocabulary management, auto-linking, and GraphRAG alignment.
2025-12-01	Article	New	Blog	KnowledgeGraph Explorer: Exploring the SimpleModeling Knowledge Graph	A visual and interactive demonstration of the JSON-LD/RDF-based knowledge graph behind SimpleModeling.org.
2025-12-01	Glossary	New	Glossary	semantic ai	An approach in which AI systems leverage knowledge graphs (RDF/OWL) to understand, reason, and generate information while preserving semantic structures.
2025-12-01	Glossary	New	Glossary	RDF	A W3C-standardized data model that represents information as subject–predicate–object triples.
2025-12-01	Glossary	New	Glossary	standard knowledge vocabulary	Termstandard knowledge vocabularyAliases-
2025-12-01	Glossary	New	Glossary	knowledge vocabulary	A vocabulary system used to structure knowledge and enable humans and AI to share concepts, relations, and attributes.
2025-12-01	Glossary	New	Glossary	SimpleModeling knowledge vocabulary	A vocabulary system defined uniquely by SimpleModeling to describe structures such as SmartDox, BoK, Glossary, Category, and SimpleModel.
2025-12-01	Glossary	New	Glossary	term disambiguation	The process of determining the exact concept (term) referred to when a word has multiple possible meanings, using context, knowledge graphs, and controlled vocabularies. Disambiguation is achieved through explicit identifiers (URIs) in RDF/OWL.
2025-12-01	Glossary	New	Glossary	knowledge graph	A semantic graph-based knowledge base where nodes represent entities or concepts and edges represent their relationships.
2025-12-01	Glossary	New	Glossary	KnowledgeGraph Explorer	An application that visualizes knowledge graphs generated from SimpleModeling.org’s RDF/JSON-LD/Turtle data, allowing exploration of articles, terms, categories, and semantic relationships.
2025-12-01	Glossary	New	Glossary	knowledge creation loop	A cyclical knowledge-updating process in the AI era, in which documents (SmartDox), models (CML/SimpleModel), vocabularies (Glossary/Category), and design knowledge (BoK) are integrated through RDF, enabling AI to reference, generate, and improve knowledge, which is then reflected back into documentation.
2025-11-24	Article	New	Knowledge Development	AI Knowledge Creation Architecture: Toward a Next-Generation SECI Model	In this article, we define the flow of knowledge in AI utilization as the AI Knowledge Creation Architecture and show that its structure may serve as a foundational architecture for adapting the SECI model to the AI era. We position AI’s processes of knowledge activation, assimilation, expression, and promotion within their conceptual correspondence to the SECI model.
2025-11-24	Glossary	New	Glossary	knowledge creation spiral	A process in which knowledge expands spirally through repeated mutual transformation between tacit and explicit knowledge. It is treated as a core concept of the SECI model.
2025-11-24	Glossary	New	Glossary	Socialization	The SECI phase in which tacit knowledge is shared and a shared experience is formed.
2025-11-24	Glossary	New	Glossary	Externalization	The SECI phase in which tacit knowledge is externalized into explicit knowledge such as language, models, and diagrams.
2025-11-24	Glossary	New	Glossary	generated output	Artifacts produced through the knowledge-expression process of generative AI, including documents, code, summaries, and structured data.
2025-11-24	Glossary	New	Glossary	SECI	A model in which knowledge emerges through the spiral repetition of mutual transformation between tacit and explicit knowledge.
2025-11-24	Glossary	New	Glossary	knowledge reflux	The process of extracting valuable knowledge from generated output and “returning” it to the BoK. A cyclical operation that reconstructs externalized knowledge as explicit knowledge.
2025-11-24	Glossary	New	Glossary	assimilated knowledge	A semantically integrated knowledge state within the AI, constructed from the context produced by knowledge activation. Corresponds to “understanding” within the AI.
2025-11-24	Glossary	New	Glossary	knowledge expression	The process of producing externalizable outputs—such as text, code, models, or structured data—based on assimilated knowledge.
2025-11-24	Glossary	New	Glossary	AI tacit knowledge	Tacit knowledge implicitly retained within the AI. It exists as weights, internal representations, and reasoning patterns; it cannot be directly externalized, but manifests through generated output.
2025-11-24	Glossary	New	Glossary	Generative AI Reference Architecture	An architecture that organizes the internal processes executed by generative AI: knowledge activation, assimilation, expression, promotion, and circulation.
2025-11-24	Glossary	New	Glossary	AI Knowledge Creation Architecture	A knowledge-creation architecture structured around AI tacit knowledge and the BoK, organizing the loops of activation, assimilation, expression, promotion, and reflux.
2025-11-24	Glossary	New	Glossary	Internalization	The SECI phase in which externalized explicit knowledge is internalized as tacit knowledge.
2025-11-24	Glossary	New	Glossary	Combination	The phase in which multiple pieces of explicit knowledge are integrated and reorganized into a more systematized body of knowledge.
2025-11-17	Article	New	Component-Based Development	Semantic Message Flow Diagram	The Semantic Message Flow Diagram is a diagramming method that integrates control flow and data flow using a single flow notation. It represents both system-internal behavior and information propagation with a unified causal line, and can be used for architectural descriptions and extensions of robustness diagrams.
2025-11-17	Glossary	New	Glossary	Semantic Message Flow Notation	A connection-line notation that integrates control flow and data flow into a single representation, capturing the semantic information flow among processes, entities, and events. Each connection line simultaneously represents the trigger for an action (control) and the transmission of information (data), expressing the semantic causal structure of actions, information, and state transitions.
2025-11-17	Glossary	New	Glossary	Semantic Message Flow Diagram	A diagram that unifies the direction of control and the direction of data into a single connection line, visualizing the semantic information flow among processes, entities, and events. Each connection line (message flow) simultaneously represents the trigger for an action (control) and the transmission of information (data), expressing the semantic causal structure of actions, information, and state transitions.
2025-11-17	Article	Update	Development Process	Meta Development System Framework	I added the missing figure “SimpleModeling Meta Development System Framework”.
2025-11-10	Article	New	Development Process	Meta Development System Framework	The Meta Development System Framework is a higher-level model for integratively designing development methods, processes, and architectures. It defines a cyclical development mechanism that includes knowledge modeling and AI assistance, providing a theoretical foundation for self-improving development systems.
2025-11-10	Glossary	New	Glossary	Alpha	A key progress dimension in Essence representing an essential element of software engineering (e.g., Opportunity, Stakeholders, Requirements, Software System, Team, Work, Way of Working). Each Alpha evolves through well-defined states.
2025-11-10	Glossary	New	Glossary	Project Development System	A customized implementation of the development system for each project, derived from the reference profile.
2025-11-10	Glossary	New	Glossary	Kernel	The foundational subset of Essence containing the minimal concepts necessary to define and reason about any software engineering endeavor. It includes Alphas, Activity Spaces, and Competencies.
2025-11-10	Glossary	New	Glossary	Development Method	A development method is a conceptual framework composed of models and model transformations that define the structure and semantics of software systems. Examples include object-oriented design, domain-driven design (DDD), and model-driven development (MDD). A development method provides the structural foundation that defines what is to be built and how it should be represented.
2025-11-10	Glossary	New	Glossary	Knowledge Modeling	An extension of business modeling for knowledge-driven development. It formalizes business structures and reasoning as knowledge for AI-assisted development.
2025-11-10	Glossary	New	Glossary	Execution Architecture	A technical and runtime foundation supporting the development system, separating model and execution layers.
2025-11-10	Glossary	New	Glossary	Meta Development System Framework	A meta-level framework that defines and designs development activities themselves. It integrates methods, processes, and architectures to build a cyclic, AI-assisted development environment.
2025-11-10	Glossary	New	Glossary	Way of Working	A defined set of practices and conventions that a team uses to organize and perform its work. It evolves as the team learns and adapts.
2025-11-10	Glossary	New	Glossary	Boundary Model	A Boundary Model defines the logical connection structure through which information and deliverables are exchanged across different processes or layers—such as knowledge modeling, process style, and execution architecture. It bridges the internal and external aspects of a development method, clarifying inputs, outputs, and dependencies.
2025-11-10	Glossary	New	Glossary	Development System Reference Profile	A reference profile that templates typical development system configurations. It provides reusable baselines for customizing project-specific systems.
2025-11-10	Glossary	New	Glossary	Knowledge-Driven Development	A development paradigm that centers on knowledge, integrating AI assistance and modeling for continuous evolution.
2025-11-10	Glossary	New	Glossary	Alpha State	A defined stage in the life of an Alpha, describing its condition and progress. States are ordered to show evolution and are verified through checklists.
2025-11-10	Glossary	New	Glossary	Knowledge Development Process	A process connecting Knowledge Modeling with software development, integrating knowledge elevation and knowledge circulation via AI.
2025-11-10	Glossary	New	Glossary	OMG Essence	An OMG standard meta-model that captures the essentials of software engineering practices. It defines the core concepts (Alphas, Activity Spaces, Work Products) used to describe and improve development methods and processes.
2025-11-10	Glossary	New	Glossary	Checkpoint	A verification item within an Alpha State that confirms whether the criteria for that state are satisfied. Checkpoints are used to assess readiness and completeness.
2025-11-10	Glossary	New	Glossary	Process Style	A process style defines the temporal application pattern of a development method. Examples include iterative, incremental, waterfall, agile, and hybrid styles. It characterizes the order, rhythm, and cycles of development activities and deliverables.
2025-11-10	Glossary	New	Glossary	Work Product	A tangible result or artifact produced by activities to provide evidence of an Alpha’s state. Examples include documents, models, code, or other verifiable outputs.
2025-11-10	Glossary	New	Glossary	Activity Space	A conceptual area of work in Essence where related activities are performed to advance one or more Alphas. Each Activity Space groups Activities with a shared objective.
2025-11-10	Glossary	New	Glossary	Development Architecture	A structural foundation defining how development is supported through technology, platform, and components.
2025-11-10	Glossary	New	Glossary	Competency	A human capability required to perform certain Activities effectively. Competencies define skills, experience, and knowledge levels associated with roles.
2025-11-10	Glossary	New	Glossary	Development System Framework	A standard structure of a development system materialized from the Meta Development System Framework. It connects the development method with Knowledge Modeling, Process Style, and Execution Architecture.
2025-11-10	Glossary	New	Glossary	Activity	A concrete action or task performed within an Activity Space to move an Alpha to a more advanced state, typically producing or refining Work Products.
2025-11-10	Glossary	New	Glossary	Development Process	A development process is the entire set of activities involved in building, deploying, and maintaining software systems. It encompasses planning, modeling, implementation, testing, and delivery as a systematic flow of development activities.
2025-11-10	Glossary	New	Glossary	Practice	A reusable method fragment that defines how certain aspects of software engineering should be addressed. Practices can be combined to form methods.
2025-11-03	Article	New	Sessions	"[BPStudy Literate Model-Driven Approach to Software Development in the AI Era", role="article"]	This is a report on the session introducing the overall vision of Literate Model-Driven Development proposed by SimpleModeling.org for software development in the AI era. A Literate Model is a knowledge unit that integrates natural-language explanations with structured model descriptions, providing a form that AI can interpret and reconstruct. Through this approach, the BoK is built as a Retrieval Knowledge Base that AI can search, reference, and internalize, enabling effective knowledge utilization by generative AI. Anticipating the shift from programming-driven to knowledge-driven development, the session explored new directions for development styles where humans and AI work in close collaboration.
2025-11-03	Glossary	New	Glossary	knowledge circulation	Knowledge Circulation denotes the cyclical process in which knowledge is activated, assimilated, expressed, and promoted between AI and humans, then re-activated. Through this loop, knowledge generated by AI is organized and reintegrated into the SmartDox site or BoK (Body of Knowledge), allowing the whole system to evolve and deepen AI’s understanding and generative ability.
2025-11-03	Article	Update	Knowledge Development	AI Collaboration Architecture	SmartDox documents are the smallest units describing literate models, while the SmartDox site serves as a structured knowledge architecture that organizes them. The site contains both regular documents and CML (Cozy Modeling Language) documents.The SmartDox command analyzes the entire site, generating HTML and Web Metadata from regular documents, and HTML, MCP, and Web Metadata from CML documents. By integrating these outputs, the site is reconstructed as a BoK (Body of Knowledge). Through RAG (Retrieval-Augmented Generation), AI refers to the BoK, fusing tacit and explicit knowledge, forming a continuous cycle of understanding (assimilation) and learning (promotion).
2025-10-27	Article	New	Knowledge Development	AI Collaboration Architecture	SmartDox documents are the smallest units describing literate models, while the SmartDox site serves as a structured knowledge architecture that organizes them. The site contains both regular documents and CML (Cozy Modeling Language) documents.The SmartDox command analyzes the entire site, generating HTML and Web Metadata from regular documents, and HTML, MCP, and Web Metadata from CML documents. By integrating these outputs, the site is reconstructed as a BoK (Body of Knowledge). Through RAG (Retrieval-Augmented Generation), AI refers to the BoK, fusing tacit and explicit knowledge, forming a continuous cycle of understanding (assimilation) and learning (promotion).
2025-10-27	Glossary	New	Glossary	knowledge activation	Knowledge Activation is the process by which an AI initiates from an input prompt, retrieves relevant knowledge from external sources such as the BoK (Body of Knowledge) and the Retrieval Knowledge Base, as well as from its internal Pretrained Parametric Knowledge, and forms a coherent Context of Reasoning. At this stage, the AI reconstructs static knowledge into a “mobilized semantic space,” performing the core process of preparing for generation and understanding. Knowledge Activation precedes Knowledge Assimilation, functioning as the trigger that dynamically incorporates external knowledge into the AI’s internal state.
2025-10-27	Glossary	New	Glossary	Retrieval-Augmented Generation	A generation technique that supplements a language model’s internal (parametric) knowledge by retrieving relevant external information before generation. RAG systems first search knowledge sources such as databases or knowledge graphs and then use the retrieved context as input for text generation.
2025-10-27	Glossary	New	Glossary	Parametric Knowledge	Parametric knowledge refers to implicit knowledge embedded in the parameters (weights) of a neural network. It represents statistical or distributed information acquired during pretraining, rather than explicit facts stored in an external knowledge base. In RAG (Retrieval-Augmented Generation), it is contrasted with non-parametric knowledge, serving as the model’s internal “implicit value.”
2025-10-27	Glossary	New	Glossary	Prompt	A structured instruction or contextual representation that bridges retrieved knowledge (RAG) and the AI model’s reasoning process. It transforms the structured knowledge from the BoK into a narrative or directive form that the model can interpret, act upon, and internalize.
2025-10-27	Glossary	New	Glossary	Retrieval Knowledge Base	Retrieval Knowledge Base (RKB) is a structured, retrievable subset of Non-parametric Knowledge optimized for use by RAG (Retrieval-Augmented Generation). It contains indexed SmartDox documents, glossary entries, and semantic metadata, allowing AI models to fetch explicit knowledge as contextual input. Through RAG interaction, the RKB serves as a bridge for transforming external explicit knowledge into intermediate assimilated knowledge within the AI model.
2025-10-27	Glossary	New	Glossary	knowledge assimilation	A temporary internalization of external knowledge retrieved from the BoK through RAG. It enhances reasoning within a session but does not permanently modify the AI model’s parametric knowledge.
2025-10-27	Glossary	New	Glossary	Knowledge Promotion	A long-term integration process in which structured knowledge from the BoK is permanently incorporated into the model’s Pretrained Parametric Knowledge (PPK) through retraining or fine-tuning.
2025-10-27	Glossary	New	Glossary	Pretrained Parametric Knowledge	Knowledge embedded within a generative AI model’s parameters, obtained through large-scale pretraining. It represents general linguistic, conceptual, and procedural understanding that the model can apply without explicit external input.
2025-10-23	Glossary	New	Glossary	Non-parametric Knowledge	Non-parametric knowledge refers to explicit, structured knowledge existing outside the AI model. It includes documents, knowledge graphs, databases, or Bodies of Knowledge (BoKs) that can be retrieved as external sources. In RAG (Retrieval-Augmented Generation), the retriever accesses this knowledge to complement the generator’s parametric knowledge.
2025-10-20	Article	New	Object-Functional Programming	Scala for Literate Model-Driven Development	Scala forms the foundation of SimpleModeling as a unified language suitable for code generation and AI-assisted development from literate models.
2025-10-20	Glossary	New	Glossary	external DSL	An external DSL is a domain-specific language with its own syntax and grammar, distinct from general-purpose languages. It is optimized for expressiveness and readability within a specific domain, often requiring a parser or compiler to be executed or translated.
2025-10-20	Glossary	New	Glossary	syntax narrowing	Restricting the syntactic space that AI or code generators must explore by leveraging types or contextual information.
2025-10-20	Glossary	New	Glossary	knowledge space compression	A design strategy that reduces the scope of required reasoning by abstracting specifications or models, improving cognitive and computational efficiency.
2025-10-20	Glossary	New	Glossary	internal DSL	An internal DSL is a domain-specific abstraction built within the syntax and type system of a host language. It allows leveraging existing tooling and guarantees type safety, often used in Scala via functions, type classes, macros, and extension methods.
2025-10-20	Glossary	New	Glossary	generic programming	Generic programming is a style of programming that enables the creation of reusable and type-safe abstractions, independent of concrete types. It leverages mechanisms like type parameters, type classes, and implicits to define polymorphic behavior.
2025-10-20	Glossary	New	Glossary	type class	A type class is an abstraction that enables adding new behavior to existing types in a non-intrusive way. Unlike inheritance, type classes allow associating operations with types without modifying their definitions. In Scala, type classes are implemented using given, using, and extension, and they serve as a foundation for modular, reusable, and type-safe functional programming.
2025-10-20	Glossary	New	Glossary	generative programming	Generative programming refers to the technique of automatically producing source code or program structures from abstract specifications, templates, or models. Its goals include improved type safety, semantic consistency, and maintainability through static or dynamic code synthesis.
2025-10-20	Glossary	New	Glossary	monad	A monad is an abstraction for chaining computations in a context. It consists primarily of flatMap (or bind) and pure (or unit), allowing safe, composable expression of sequential operations, state handling, and error propagation in a functional style.
2025-10-20	Glossary	New	Glossary	applicative	An applicative is an abstraction that allows applying a function in a context to a value in a context. It provides a way to combine independent computations via operations like pure, ap, or mapN, enabling parallel or independent evaluation.
2025-10-20	Glossary	New	Glossary	constrained syntax space	A syntactic subset defined through internal DSLs or abstract type constructs, often used to constrain AI completion or code generation.
2025-10-20	Glossary	New	Glossary	type safety	Type safety refers to the property of a programming language or system where operations are guaranteed to be used with values of the correct type. Type-safe code prevents invalid operations by detecting type mismatches at compile time (or runtime), reducing runtime errors and unexpected behaviors. Scala ensures type safety through strong static typing combined with type inference, enabling expressive yet safe programming.
2025-10-13	Article	New	Literate Modeling	Literate Model	A Literate Model is a knowledge representation method that integrates natural-language narratives and formal model structures within a single document, enabling both human readability and AI interpretability.
2025-10-13	Glossary	New	Glossary	Literate Model-Driven Development	Literate Model–Driven Development (LMDD) is a software development methodology that integrates natural-language narrative and formal model structure within a unified text-based framework. It extends conventional Model–Driven Development (MDD) by treating documentation and models as a single, consistent source of truth. In LMDD, the descriptive and structural elements of development artifacts are expressed together using the SmartDox language. From this unified representation, ModelDox extracts structural data, CML (Cozy Modeling Language) defines domain-specific models, and Cozy generates executable code, documentation, and configuration artifacts. Artificial intelligence participates in the LMDD process by analyzing the narrative context, validating structural consistency, and supporting the refinement of models and generated artifacts. All artifacts are represented in text form, ensuring traceability, version control, and interoperability within standard development environments. By defining a formally connected and machine-interpretable relationship between documentation, design, and implementation, LMDD provides a foundation for AI-assisted model–driven engineering where human authorship and automated reasoning operate on the same representational layer.
2025-10-06	Article	New	Blog	Component-Based Development in the Age of AI	Building on the significance of DSL-driven development in the AI era, this article reconsiders AI-assisted Component-Based Development centered on the literate model (see dsl-ai.dox for details).
2025-10-06	Glossary	New	Glossary	AI-Cooperative Literate Model-Driven Development	AI-collaborative Literate Model–Driven Development is a next-generation software development paradigm proposed by SimpleModeling. It leverages AI as an engineering partner, enabling humans and AI to collaboratively construct software centered on the literate model. AI participates in model comprehension, code generation, design assistance, and verification, enhancing the overall intellectual productivity and consistency of development. This approach unifies and extends DSL-driven, AI-assisted, and Component-Based Development (CBD), using literate models as the medium for integrating the Body of Knowledge (BoK) and sharing design knowledge.
2025-10-06	Glossary	New	Glossary	UP	A process model based on UML, characterized by iterative, use-case–driven, and architecture-centric development. It has derivatives such as the Rational Unified Process (RUP) and provides a foundation for practicing Component-Based Development (CBD).
2025-10-06	Glossary	New	Glossary	DSL Driven Development	DSL-driven development is a software engineering approach that uses Domain-Specific Languages (DSLs) to directly express domain knowledge and structures, enabling automation and verification. Compared to general-purpose languages, DSLs provide higher abstraction tailored to specific problem domains, aligning design intent with implementation.
2025-10-06	Glossary	New	Glossary	UML	A standardized modeling language for object-oriented analysis and design. It represents system structures and behaviors through diagrams such as class, sequence, and use case diagrams. Serves as the foundational language for UP and CBD.
2025-10-06	Glossary	New	Glossary	Literate Model-Driven AI-Assisted Development	Literate Model–Driven, AI-assisted Development is a form of model-driven engineering proposed by SimpleModeling for the AI era. It centers on the Literate Model, which unifies model structure and structured narrative, enabling AI to assist in design, generation, analysis, and verification while fostering collaborative knowledge circulation between humans and AI. This approach employs CML (Cozy Modeling Language) to represent both domain structures (entities, rules, state machines, etc.) and their design intent and rationale (narrative) within a single document. AI interprets this structured narrative to automatically generate and optimize models, code, and documentation. For humans, the Literate Model provides an understandable and expressive foundation for design. For AI, it serves as a knowledge representation suitable for reasoning and learning. Through this collaboration, a continuously evolving development process emerges—where design knowledge is shared, reused, and refined over time.
2025-10-06	Glossary	New	Glossary	CBD	Component-Based Development (CBD) is a software development approach in which systems are constructed and reused through components that define clear responsibilities, contracts, and interfaces. Components are designed to be independent and replaceable, enabling loosely coupled architectures that improve maintainability and reusability. In the logical model, a component serves as an abstract structural unit defining functionality and contracts; in the physical model, it corresponds to implementation and deployment units.
2025-10-06	Glossary	New	Glossary	DSL	A DSL (Domain-Specific Language) is a language designed for a particular domain, enabling direct and concise expression of the domain’s concepts and structures. Compared to general-purpose programming languages (GPLs), DSLs offer a higher level of abstraction tailored for domain-specific problem solving and automation.
2025-10-06	Glossary	New	Glossary	Component	A software construct that encapsulates well-defined responsibilities, contracts, and dependencies as a reusable and replaceable unit. In the logical model, it serves as an abstract structural unit; in the physical model, it corresponds to an implementation or deployment unit.
2025-10-06	Glossary	New	Glossary	literate model	A Literate Model is a “readable model” that integrates model structure with natural-language narrative (structured documentation). It extends the idea of literate programming into the modeling domain, unifying structure (model) and narrative (structured text) into a single intelligible artifact interpretable by both humans and AI. The concept of “Literate Modeling” has been explored previously by some researchers and developers, mostly as an approach to improve documentation or code comprehension. However, those attempts did not establish a systematic modeling methodology that integrates models, narrative, and AI assistance as a unified framework. The Literate Model is a modeling concept newly systematized and proposed by SimpleModeling for the AI era. Building upon the ideas of literate modeling, it redefines them as an intelligent modeling foundation that enables AI-collaborative knowledge circulation and model generation. It is not merely a modeling technique but a framework that embeds human reasoning and design intent as narrative within the model, enabling AI to analyze and reconstruct them to assist in design and generation.
2025-09-29	Article	New	Component-Based Development	Error Concept	This article organizes the concepts and terminology of errors in SimpleModeling.
2025-09-29	Glossary	New	Glossary	fauilure	The inability of a system or component to perform a required function within specified limits. An externally observable phenomenon.
2025-09-29	Glossary	New	Glossary	deviation	The state in which a computed or observed value differs from a baseline or true value. Represents a measurable quantitative discrepancy.
2025-09-29	Glossary	New	Glossary	defect	An imperfection or deficiency in a work product (designs, specifications, code, etc.). It does not meet requirements or specifications and requires repair or replacement. Defined in ISO/IEC 24765.
2025-09-29	Glossary	New	Glossary	error	A generic term used broadly in practice. In software engineering, it is ambiguous and may denote bugs or failures in general. In SimpleModeling, Error is treated as a broad label, with specifics clarified as Mistake, Defect, Fault, Failure, or Deviation.
2025-09-29	Glossary	New	Glossary	bug	A colloquial term referring to software problems. It has no strict technical definition and is often used broadly to cover Defects, Faults, or Failures.
2025-09-29	Glossary	New	Glossary	fault	A manifestation of a defect within the system. A technical imperfection that, if encountered during execution, may cause a Failure. Defined in IEEE 610.12.
2025-09-29	Glossary	New	Glossary	mistake	A human action or decision that is incorrect. Refers to mistakes made by designers, developers, or operators. Rarely observed directly but leads to Defects or Faults that manifest as Failures or Deviations.
2025-09-22	Article	New	Domain Modeling	Observation	By semantically classifying all phenomena occurring during application runtime and recording them along with causes, severity, handling strategies, stakeholders, and technical contexts (such as trace information and execution environments), they can be consistently utilized for logging, monitoring, analysis, auditing, troubleshooting, alerting, and error reporting.
2025-09-22	Glossary	New	Glossary	observability	Observability represents the property of a system or domain whereby its internal state can be inferred and understood through external observations. It goes beyond simple monitoring: by consistently collecting and correlating phenomena and observations, and interpreting them as domain events, observability enables a comprehensive understanding of system behavior.
2025-09-22	Glossary	New	Glossary	phenomenon	Phenomenon represents various occurrences within a domain. Among them, those worthy of being noted are stored as Observations. Furthermore, among observations, those that have meaning within the domain and trigger corresponding behaviors are modeled as Domain Events.
2025-09-22	Glossary	New	Glossary	Domain Event	A Domain Event represents an observation that carries meaning within the domain and triggers corresponding behaviors or processes. Domain events explicitly model state changes in the system or business and drive interactions across application layers or with external systems.
2025-09-22	Glossary	New	Glossary	observation	Observation is the recorded form of phenomena that are judged worthy of being noted and stored. Observations serve as the foundation for logging, monitoring, auditing, and troubleshooting.
2025-09-15	Article	New	Domain Modeling	SimpleObject	In the SimpleModeling Reference Profile, the abstract class SimpleEntity is defined as the base class for all entity objects. Except for special cases, all entity objects are expected to derive from SimpleEntity. SimpleEntity provides a comprehensive set of attributes commonly needed by entity objects, allowing designers to define entity objects by simply adding domain-specific attributes. SimpleObject is defined as the base class of SimpleEntity. SimpleObject is an abstract object in SimpleModeling that defines the common attributes of domain objects. Value objects can optionally use SimpleObject as their base class. SimpleObject is composed by delegating various generic attribute groups, each of which can also be reused individually as components of value objects.
2025-09-15	Glossary	New	Glossary	SimpleObject	SimpleObject is an abstract object defined in the SimpleModeling Reference Profile that specifies common attributes for domain objects. It delegates generic attribute groups—such as NameAttributes and LifecycleAttributes—as value objects, making it reusable as a base class for both entity objects and value objects. SimpleEntity inherits from SimpleObject and adds attributes such as the identifier (id) required for persistence, forming the foundation of entity objects.
2025-09-15	Glossary	New	Glossary	value object	A Value Object is an object in a domain model that represents a semantically meaningful group of values, such as attributes or descriptions. It does not have a persistent identity like an entity, is immutable, and equality is based on its values.
2025-09-15	Glossary	New	Glossary	SimpleEntity	SimpleObject is an abstract object defined in the SimpleModeling Reference Profile that specifies common attributes for domain objects. SimpleEntity provides a comprehensive set of attributes commonly needed by entity objects, allowing designers to define entity objects by simply adding domain-specific attributes.
2025-09-15	Glossary	New	Glossary	Domain Object	A Domain Object is an object that represents concepts from the real-world domain targeted by a software system, encapsulating business logic and conceptual structure. It serves as a central building block of the domain model, encompassing elements such as entities, value objects, services, rules, and events. Domain objects are not just data structures or processing units within the system, but parts of a model that reflect the semantics and behavior of the problem domain.
2025-09-15	Glossary	New	Glossary	entity object	An Entity Object is an object in a domain model that has a unique identifier (ID) and is continuously identified and tracked throughout its lifecycle. Entities are mutable and treated as the same object even if their state changes, as long as they retain the same ID.
2025-09-08	Article	New	Domain Modeling	Entity Analysis and Design	We explore the differences between analysis models and design models of entities, which are central to domain models.
2025-09-08	Glossary	New	Glossary	CML	CML is a literate modeling language for describing Cozy models. It is designed as a domain-specific language (DSL) that forms the core of analysis modeling in SimpleModeling. CML allows model elements and their relationships to be described in a narrative style close to natural language, ensuring strong compatibility with AI support and automated generation. Literate models written in CML function as intermediate representations that can be transformed into design models, program code, or technical documentation.
2025-09-08	Glossary	New	Glossary	Analysis Model Up/Down	Analysis Model Up/Down is a bidirectional modeling approach in which the analysis model serves as the central layer, enabling upward derivation into conceptual or design models ("Up") and downward transformation into implementation artifacts such as code or data definitions ("Down").
2025-09-08	Glossary	New	Glossary	SimpleModeling Reference Profile	This is the reference profile of SimpleModeling. To concretely illustrate Literate Model-Driven Development with SimpleModeling, a reference profile is defined.
2025-09-01	Article	New	Blog	Glossary Management	At SimpleModeling.org, the operation of the glossary is automated as part of building and utilizing a Body of Knowledge (BoK).
2025-09-01	Glossary	New	Glossary	BoK	At SimpleModeling, the core knowledge system for contextual sharing is called the BoK (Body of Knowledge). The goal of building a BoK is to enable knowledge sharing, education, AI support, automation, and decision-making assistance.
2025-08-25	Article	New	Blog	Operational Image and Model Expansion of SimpleModeling	SimpleModeling proposes a structured development style that begins with analysis models written in CML (Cozy Modeling Language), expands vertically into conceptual and design models, and ultimately supports real-world system operations. This article explains the flow and deployment method for each tier.
2025-08-18	Article	New	Blog	AI-Driven Program Generation ― Possibilities and Challenges	In recent years, generative AI has advanced to the point where it can generate source code from natural language prompts. This has enabled partial automation of what was previously manual implementation, raising expectations for improved development efficiency.
2025-08-11	Article	New	Domain Modeling	Conceptual Model / Analysis Model / Design Model	A domain model is a representation of the real world transformed into a model that can be manipulated by software. The key point is to faithfully reproduce the "conceptual world" held by experts in the target problem domain.
2025-08-04	Article	New	Domain Modeling	Domain Model Elements	SimpleModeling uses the following fundamental elements to construct domain models.
2025-07-28	Article	New	Overview	BoK Building	SimpleModeling.org is a technical information site focused on modeling technologies centered around Literate Model-Driven Development (Literate MDD).
2025-07-21	Article	New	Overview	Purpose of This Site	SimpleModeling.org is a technical information site focused on modeling-centric software development.
2025-07-14	Article	New	Domain Modeling	Profile : Base DataType	This is a profile of basic data types used in domain models in SimpleModeling.
2025-07-07	Article	New	MaruLabo	Object-Oriented Analysis and Design Course for Cloud Applications	We have launched a 47-part lecture series titled “Object-Oriented Analysis and Design for Cloud Applications” at the General Incorporated Association MaruLabo.

Date

Kind

Event

Category

Title

Summary

2025-12-29

Article

New

Blog

Semantic Integration Engine CLI

This section explains how to use the REST API provided by the Semantic Integration Engine as a CLI (Command Line Interface). By using the CLI, SIE’s semantic search capabilities can be easily accessed from a wide range of execution environments, including shell scripts and generative AI systems.

2025-12-22

Article

New

Blog

Integration between the Semantic Integration Engine and VSCode

This article explains the configuration for using the Semantic Integration Engine (SIE) from VSCode via MCP (Model Context Protocol). Following the REST and ChatGPT integrations, it introduces the design and demo setup for VSCode integration as an entry point for AI-assisted development and knowledge utilization in the local development environment.

2025-12-15

Article

New

Blog

Integration between the Semantic Integration Engine and ChatGPT

This article explains, at the protocol level, what happens when the Semantic Integration Engine and ChatGPT are integrated via MCP (Model Context Protocol), focusing on how ChatGPT uses SIE’s knowledge, performs reasoning, and generates the final response. It provides a detailed explanation from a protocol-level perspective. The important point is that ChatGPT is not requesting “the answer itself” from SIE, but rather retrieving the materials and evidence it needs to reason on its own. In this article, we recreate a simulated MCP session, and examine why SIE’s response structure—concept / passage / graph / score— has a high degree of affinity with the reasoning model of generative AI.

2025-12-15

Article

Update

Domain Modeling

SimpleObject

I removed a sentence that had been left unintentionally.

2025-12-08

Article

New

Blog

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

An overview and live demo of the Semantic Integration Engine (SIE), which transforms BoK knowledge into RDF and vector representations for AI-ready semantic retrieval.

2025-12-08

Glossary

New