Learn how to tell whether a domain concept is an Entity or a Value Object by asking if its identity matters or only its attributes, see concrete examples with Money, Address and Order, understand immutable design, proper equals/hashCode implementation, and validation through unit tests.
The article explains that an Entity is distinguished by a unique identifier while a Value Object is defined solely by its attributes and must be immutable, illustrating the concepts with Java Entity, record, and JPA mapping examples, and providing three practical questions to decide which to use.
The article explains why traditional three‑layer architectures let business logic bloat inside services, demonstrates the pitfalls of anemic domain models with a 7,000‑line SalaryService example, and shows how DDD’s rich domain model restores rule ownership and maintainability.
A mis‑designed phone number column can silently degrade index performance, overload CPU, and cause a cascade of timeouts in a 2‑billion‑user system, but by treating the phone as a domain value object, using a normalized VARCHAR, aligning indexing rules, and applying consistent sharding and migration strategies, you can prevent the database from collapsing under high concurrency.
This article provides a comprehensive introduction to Domain‑Driven Design (DDD), covering its origins, core principles, layered architecture, key concepts such as entities, value objects, aggregates, bounded contexts, and how DDD improves communication and maintainability in complex software systems.
This article delves into the tactical design of Domain‑Driven Design, explaining core building blocks such as entities, value objects, aggregates, domain events, repositories, application services, and domain services, and shows how they help keep business logic centralized and expressive.
The article explains how the Value Object pattern, combined with PHP 8.1/8.2 features like readonly properties and named arguments, can eliminate primitive‑type validation duplication, prevent parameter‑order mistakes, and ensure immutability, thereby making PHP code more robust, maintainable, and self‑documenting.
This article redefines what constitutes good code by using a star‑chart analogy, exposing typical spaghetti‑code pitfalls, and introducing three design patterns—Value Object, Side‑Effect‑Free Function, and Intention‑Revealing Interface—to help developers refactor and write maintainable software.
This article explains Domain‑Driven Design fundamentals, covering how to define bounded contexts and subdomains, the criteria for domain division, practical modeling experiences, and detailed guidance on modeling entities and value objects with illustrative Go code examples.
This article explains the core DDD concepts of entities, value objects, and aggregate roots in Go, detailing how unique identifiers differ from database primary keys, when to use value objects versus primitive types, and best practices for generating and handling IDs within aggregates.
This article walks through applying Domain‑Driven Design in Go, focusing on value objects: their definition, immutability, implementation details, common pitfalls with pointers and serialization, practical code patterns, and how to model enums, offering concrete guidance for robust backend development.
The article explains the core traits of entities—identity and continuity—through domain‑driven design examples, demonstrates why a Message should be modeled as an entity, and discusses the reasoning behind treating Sender and Recipient as value objects or entities in a messaging domain.
This article explains the core characteristics of entities—identity and continuity—using domain‑driven design principles, analyzes why a Message should be modeled as an entity, and argues that senders and recipients are better represented as entities rather than value objects in a messaging system.
The article explains the core characteristics of entities—identity and continuity—using DDD concepts, demonstrates why a Message in a messaging scenario qualifies as an entity, and argues that senders and recipients (contacts) should also be modeled as entities rather than value objects.
