Domain-Driven Design
An approach to software development that focuses on modeling complex domains.
Classification
- ComplexityMedium
- Impact areaTechnical
- Decision typeDesign
- Organizational maturityIntermediate
Technical context
Principles & goals
Use cases & scenarios
Compromises
- Misunderstandings in domain modeling
- Over-complexity due to too many models
- Resistance to change
- Engaged collaboration between IT and business departments.
- Iterative development and feedback loops.
- Documentation of domain models.
I/O & resources
- Stakeholder requirements
- Technical specifications
- Market research findings
- Functional software
- Documented processes
- Fulfilled requirements
Description
Domain-Driven Design (DDD) is a concept aimed at managing the complexity of software projects by placing the domain of the problem at the center. It promotes close collaboration between domain experts and developers to create a shared understanding of the domain and develop effective models.
✔Benefits
- Improved software quality
- Increased flexibility
- Better collaboration between teams
✖Limitations
- High initial effort
- Complexity in modeling
- Dependency on domain experts
Trade-offs
Metrics
- Customer satisfaction
Measurement of user satisfaction with the software.
- Error rate
Number of errors per 1000 lines of code.
- Development time
Time taken to develop new features.
Examples & implementations
Application of DDD in a financial services company
A financial service provider uses DDD to model complex business rules in a new lending system.
Development of a CRM solution
A company implements DDD to develop a customized CRM solution that addresses specific customer requirements.
Optimization of an e-commerce system
An e-commerce company uses DDD to enhance the user experience by specifically modeling the purchasing processes.
Implementation steps
Conduct workshops for requirement analysis.
Create prototypes to validate models.
Regularly review and adjust models.
⚠️ Technical debt & bottlenecks
Technical debt
- Insufficient documentation of models.
- Technical debt from quick fixes.
- Outdated technologies in implementation.
Known bottlenecks
Misuse examples
- Using DDD without sufficient domain knowledge.
- Modeling without user feedback.
- Neglecting technical constraints.
Typical traps
- Assuming all domain experts have the same perspective.
- Overestimating the complexity of the domain.
- Underestimating the training needs.
Required skills
Architectural drivers
Constraints
- • Compliance with security standards
- • Regulatory requirements
- • Technological constraints