Domain driven design and model driven development
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This document discusses domain driven design and model driven development. It introduces ontology and how it relates to domain driven design. The document outlines key domain driven design building blocks like the domain model, entities, value objects, repositories, services, and aggregates. It also discusses challenges of domain driven design and code generation techniques.
Domain driven design and model driven development
- 1. Domain Driven Design and Model Driven Development Geyzersky Dmitry IT Architect, Co-Owner of PerformIT [email protected] http://www.performit.co.il
- 2. “Any fool can write code that a computer can understand. Good programmers write code that humans can understand.“ Martin Fowler
- 3. Session Objectives and Agenda • Introduction to Ontology. • From the Ontology to Domain Driven Design. • DDD Building Blocks. • Modeling Techniques.
- 4. Ontology • In philosophy ontology is the theory of the nature of existence. • In the context of information science it is the study of entities and their relations. • It is about modeling a domain of knowledge by using high level of abstraction.
- 6. Ontology and Semantic Technologies
- 7. Domain Driven Design • Model driven software design approach used to tackle complexity of software projects. • DDD focuses on the domain logic. • The term was coined by Eric Evans in his book.
- 8. “Strategy is doing the right things, tactics is doing things right.“ Peter Ferdinand Drucker
- 9. Ubiquitous Language • Learn and talk the language of the domain experts. • The language evolves with the domain model and enables to describe the characteristics of the domain with increased precision. • Change in the language = change in the model and vice versa. • Knowledge crunching.
- 11. Domain Model • Model is the backbone of Domain Driven Design. • Model forms ubiquitous language. • Perfect tool for communication between domain experts and developers. • Explains complex domain in a simple way. • Model and Code are bound.
- 12. Layering
- 13. DDD Building Blocks Domain Model
- 14. Entities Objects having a unique identity throughout the states of the software.
- 15. Entities We compare entities by their IDs.
- 16. Value Objects • Objects describing certain aspects of the domain which don’t have identity and lifecycle. • Immutable - if you need to change the object, just create a new one.
- 17. Value Objects • We compare Value Types by comparing their properties one-by-one.
- 18. Repositories • A Repository encapsulates domain objects persistence and retrieval. • Clean separation and one-way dependency between the domain and data mapping layers. • Usually implemented with Object Relational Mapping (ORM) techniques. • May encapsulate different fetching strategies, distributed caching, NoSQL and etc.
- 19. Services • Define an application's boundary. • Services usually manipulate Entities and Value Objects. • A service typically implements a business rule, generally something that software must do.
- 20. Aggregates • Each Aggregate has one Root Entity. • The root identity is global, the identities of entities inside are local. • External objects may have references only to root. • Internal objects cannot be changed outside the Aggregate.
- 21. Factories • A program elements whose responsibility is the creation of other objects. • Create and manage complex domain objects. • Especially useful for creating aggregates when atomicity is required.
- 22. Domain Events Represent the states of Entities
- 23. DDD Challenges • The model must reflect code changes and vice versa. • The amount of boilerplate code must be as minimal as possible. • The main focus is on the business domain and not the infrastructure. • Minimum friction with technology. • Continuous integration, testing and refactory. • As much automation as possible.
- 24. Code Generation Techniques • NHibernate with NVelocity (.Net). • Xtext with Xtend (Java, Eclipse). • Protege (Java). • Enterprise Architect (any language). • MS Entity Framework (.Net) with T4. • UML (any language). • Spring Data (Java, Neo4J) and etc.
- 25. References • Domain-Driven Design: Tackling Complexity in the Heart of Software (by Eric Evans). • http://nhforge.org/blogs/nhibernate. • http://www.springsource.org/spring-data. • http://www.eclipse.org/xtend/. • A Legal Case OWL Ontology with an Instantiation of Popov v. Hayashi Adam Wyner and Rinke Hoekstra, Knowledge Engineering Review.
- 26. For more information: [email protected] or http://www.performit.co.il