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Selects small structural and behavioral patterns from the problem being solved instead of pattern-name recognition.
Explains inward dependency flow, stable business policy, adapters, and when a smaller project structure is enough.
Applies CQRS proportionally, separating model responsibilities without assuming separate databases, messaging, or event sourcing.
Distinguishes explicit dependency injection from runtime service lookup and identifies the narrow framework boundaries where scoped resolution is legitimate.
Keeps business policy independent from infrastructure while centralizing concrete dependency assembly at the application edge.
Turns a modular-monolith choice into enforceable code and data ownership rather than relying on folders and team discipline alone.
Improves architecture through protected behavior, incremental boundaries, and measurable delivery instead of a risky all-at-once rewrite.
Designs consumer-focused contracts that reduce accidental authority and coupling without producing meaningless one-method wrappers.
Explains substitutability through inputs, outputs, side effects, and failure behavior rather than inheritance syntax alone.
Uses stable extension points for genuinely variable behavior while avoiding speculative abstractions and configuration-driven branching.
Places invariants and state transitions near the data they protect while keeping orchestration and infrastructure out of domain entities.
Evaluates repositories by domain language, query ownership, and substitutability instead of treating them as a mandatory wrapper around DbSet.
Uses separate models where they protect contracts, invariants, or storage evolution while avoiding repetitive mapping with no boundary value.
Applies single responsibility to reasons for change, cohesive behavior, and maintainable service boundaries instead of counting methods.
Chooses code organization from change locality, shared policy, and cross-cutting needs rather than adopting one folder structure universally.