Implementation Approach

Implementation Strategy Selection Framework (Meta-cognitive Approach)

Meta-cognitive Strategy Selection Process

Phase 1: Decision-Sufficient Current State Analysis

Core Question: "What does the existing implementation look like?"

Analysis Framework

Architecture Analysis: Responsibility separation, data flow, dependencies, technical debt
Implementation Quality Assessment: Code quality, behavior-relevant test evidence, performance, security
Historical Context Understanding: Current form rationale, past decision validity, constraint changes, requirement evolution

Meta-cognitive Question List

• What is the true responsibility of this implementation?
• Which parts are business essence and which derive from technical constraints?
• What dependencies or implicit preconditions are unclear from the code?
• What benefits and constraints does the current design bring?

Stop when another current-state fact cannot change responsibility, reuse, option validity, total complexity, a contract, or verification.

Phase 2: Design Convergence

Complete these steps in order before selecting an implementation strategy:

1. Existing-Surface Baseline: Form the simplest end-to-end path that delivers the current outcome through existing responsibilities. Explicit requirements and accepted decisions are binding; suggested mechanisms remain candidates.
2. Evidence Check: Test that path against current requirements, verified constraints, observed in-scope problems, and evidence-backed material risks. Keep only the unmet conditions that can change the selected design.
3. Targeted Comparison: For each unmet condition, test reuse, derivation from existing data, on-demand computation, or responsibility at the current caller or boundary before adding design surface. Compare viable choices by total complexity across the dimensions that materially differ: user decisions, settings, modes, concepts, outputs, persistent state, implementation paths, UX, runtime, implementation, testing, documentation, and maintenance. Select the lowest-total-complexity choice that satisfies the condition.
4. Subtraction Check: Remove each proposed addition and re-test its governing condition. Retain it only when the confirmed outcome, a required boundary, or necessary proof becomes unmet.

Classify supporting claims as observed, inferred, or unknown. Route an unknown that blocks the next step as an exact evidence prerequisite; the caller's value-boundary and irreversible-action gates determine whether user interaction is required.

Candidate paths and rejected additions remain active analysis. The durable output is the Selected Design: the complete chosen path plus evidence for each added design surface and the condition that fails when it is removed. An accepted ADR may retain alternatives as decision history. An implementer uses the same convergence check without producing a separate artifact.

Phase 3: Strategy Exploration and Creation

Core Question: "When determining before → after, what implementation patterns or strategies should be referenced?"

Strategy Discovery Process

Direct Strategy: Smallest repository-supported change that satisfies the accepted requirements and constraints
Repository Alternatives: Existing patterns that materially differ in migration, dependency order, or verification boundary
External Research: Official/current sources only when repository evidence cannot resolve a time-sensitive capability, compatibility, or dependency decision

Reference Strategy Patterns

Legacy Handling Strategies:

• Strangler Pattern: Gradual migration through phased replacement
• Facade Pattern: Complexity hiding through unified interface
• Adapter Pattern: Bridge with existing systems

New Development Strategies:

• Feature-driven Development: Vertical implementation prioritizing user value
• Foundation-driven Development: Foundation-first construction prioritizing stability
• Risk-driven Development: Prioritize addressing maximum risk elements

Integration/Migration Strategies:

• Proxy Pattern: Transparent feature extension
• Decorator Pattern: Phased enhancement of existing features
• Bridge Pattern: Flexibility through abstraction

Use these patterns only when their named migration or dependency problem exists. Start with the direct strategy. Compare an alternative when it would materially change risk, rollout, compatibility, or the early verification point. Keep the option set limited to patterns that produce one of those material differences.

Phase 4: Material Risk Assessment and Control

Core Question: "What risks arise when applying this to existing implementation, and what's the best way to control them?"

Evaluate only risk categories for which current evidence can change the strategy, public contract, rollout, rollback, or verification boundary.

Conditional Risk Categories

Technical Risks: System impact, data consistency, performance degradation, integration complexity
Operational Risks: Service availability, deployment downtime, process changes, rollback procedures
Project Risks: Schedule delays, learning costs, quality achievement, team coordination

Risk Control Strategies

Preventive Measures: Phased migration, parallel operation verification, integration/regression tests, monitoring setup
Incident Response: Rollback procedures, log/metrics preparation, communication system, service continuation procedures

Phase 5: Decision-Relevant Constraint Compatibility

Core Question: "What are this project's constraints?"

Check only constraints evidenced by the governing requirements, repository, external contracts, or current environment that can change the selected strategy or verification boundary.

Conditional Constraint Categories

Technical Constraints: Library compatibility, resource capacity, mandatory requirements, numerical targets
Temporal Constraints: Deadlines/priorities, dependencies, milestones, learning periods
Resource Constraints: Team/skills, work hours/systems, budget, external contracts
Business Constraints: Market launch timing, customer impact, regulatory compliance

Phase 6: Implementation Approach Decision

Select the implementation approach that directly fits the verified dependency and delivery constraints:

Vertical Slice (Feature-driven)

Characteristics: Vertical implementation across all layers by feature unit Application Conditions: Default when an end-to-end value unit can be delivered and verified independently. Data-model sharing and layer breadth are supporting evidence, not substitutes for independent deliverability Verification Method: End-user value delivery at each feature completion