Refactoring & Re-architecture

Codebase and architecture assessment

• Code review: structure, layering, coupling, test coverage, dependency health and build times.
• Static analysis: complexity hotspots, duplication and outdated or vulnerable dependencies.
• Architecture review: services, data stores, integration points and how they scale.
• Hotspot analysis: files that change often *and* are complex. That is where refactoring pays off first.
• Architecture decision records: a short record of each important decision and the reasoning behind it.

Refactoring with proven patterns

We apply patterns where they solve a real problem, not for their own sake:

• Structure: layered / clean / hexagonal architecture to separate business rules from frameworks and infrastructure.
• Data access and transactions: repository and unit of work.
• Behaviour and wiring: strategy, factory, adapter and facade to replace large conditionals and isolate third-party APIs.
• Events: observer / domain events, plus outbox for reliable event publishing.
• Robustness: dependency injection for testability, and circuit breaker, retry and idempotency for network calls.
• Mobile and frontend state: BLoC, Riverpod, MVVM or Redux-style state management.

Every refactoring step is covered by tests first (characterisation tests where none exist), kept small, and released on its own.

Re-architecture where needed

• Modular monolith: clear module boundaries inside one deployable app, often the best first step.
• Service extraction: splitting out the parts that need independent scaling or ownership, using the strangler fig pattern.
• Event-driven processing: queues and pub/sub for slow or bursty workloads.
• Data store changes: for example, separating transactional data from analytics, adding caching, or read replicas.
• Consolidation: merging over-split microservices back together where that reduces cost and complexity.

Safety net

• Tests: unit, integration and contract tests.
• Delivery: CI/CD improvements and feature flags.
• Visibility: observability, so you can see the effect of each change in production.

1. Scoping call. We discuss your pain points, goals and timelines.
2. Assessment (1–3 weeks). Findings and a target architecture.
3. Roadmap. Prioritised refactoring steps, each with effort, risk and expected benefit.
4. Incremental delivery. Small, reviewed pull requests behind tests and feature flags. No big-bang rewrite.
5. Knowledge transfer. Pairing, documentation and architecture walkthroughs with your team.
6. Review. We measure progress against agreed indicators, such as build time, change failure rate, test coverage and lead time.

• Assessment report: hotspots, risks and dependency status.
• A target architecture: diagrams (C4 model) and architecture decision records.
• A prioritised refactoring roadmap.
• Refactored code delivered as reviewed pull requests, with tests.
• CI/CD and testing improvements.
• Documentation and handover sessions.

Aligned with:

• design patterns as described by Gang of Four, Fowler and Evans (Domain-Driven Design)
• SOLID principles
• the C4 model for architecture diagrams
• the Twelve-Factor App
• the AWS Well-Architected Framework and Google Cloud Architecture Framework

Tools: SonarQube, CodeScene-style hotspot analysis, Dependabot/Renovate, OpenTelemetry, GitHub Actions/GitLab CI, and language-specific linters and test frameworks.

We offer fixed-price packages for businesses with different needs. Scope, timeline and deliverables are agreed in writing after the scoping call.

Book a 30-minute call to talk through your product and what you need.

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