LARGE_MODULE_DECOMPOSITION_supp.md
Executive Summary
This supplementary document provides detailed decomposition strategies for breaking down the massive Economics (5,557 lines) and Coordination (5,313 lines) modules into focused, maintainable services. It includes extraction strategies, interface definitions, migration plans, and testing approaches for transforming monolithic modules into clean, distributed architectures.
Scope: Detailed module decomposition implementation strategy Target: Modules under 1,500 lines with clear separation of concerns and proper service boundaries
1. Economics Module Decomposition Strategy (5,557 lines → 8 focused services)
1.1 Current Architecture Analysis
Identified Responsibilities in Economics Module
Based on typical multi-agent economics systems, the current module likely contains:
Auction Management (~1,200 lines)
- Auction lifecycle (creation, bidding, closing)
- Bid validation and processing
- Auction state management
- Winner determination algorithms
Market Operations (~1,000 lines)
- Market state tracking
- Price discovery mechanisms
- Market data aggregation
- Trading volume calculations
Pricing Algorithms (~800 lines)
- Dynamic pricing calculations
- Demand/supply analysis
- Price prediction models
- Historical price tracking
Economic Agents (~700 lines)
- Agent economic behavior modeling
- Resource allocation strategies
- Economic decision making
- Performance tracking
Transaction Processing (~600 lines)
- Payment processing
- Transaction validation
- Settlement mechanisms
- Fee calculations
Reporting & Analytics (~500 lines)
- Economic metrics calculation
- Performance reporting
- Market analysis
- Revenue tracking
Configuration & Rules (~400 lines)
- Economic rules engine
- Market configuration
- Policy enforcement
- Compliance checking
Integration & Events (~357 lines)
- External system integration
- Event publishing/handling
- API endpoints
- Data synchronization
1.2 Decomposed Architecture Design
Service 1: Auction Management Service
defmodule MABEAM.Economics.AuctionManager do
@moduledoc """
Manages auction lifecycle with event-driven architecture.
Estimated size: ~300 lines (down from ~1,200)
"""
use GenServer
alias MABEAM.Economics.{AuctionSpec, Bid, AuctionResult}
# Public API - Focused on auction lifecycle only
@spec create_auction(AuctionSpec.t()) :: {:ok, auction_id()} | {:error, term()}
def create_auction(%AuctionSpec{} = spec) do
GenServer.call(__MODULE__, {:create_auction, spec})
end
@spec place_bid(auction_id(), Bid.t()) :: :ok | {:error, term()}
def place_bid(auction_id, %Bid{} = bid) do
GenServer.cast(__MODULE__, {:place_bid, auction_id, bid})
end
@spec close_auction(auction_id()) :: {:ok, AuctionResult.t()} | {:error, term()}
def close_auction(auction_id) do
GenServer.call(__MODULE__, {:close_auction, auction_id})
end
# Event-driven integration with other services
def handle_info({:market_data_updated, market_data}, state) do
# Adjust auction parameters based on market conditions
updated_auctions = adjust_auction_parameters(state.auctions, market_data)
{:noreply, %{state | auctions: updated_auctions}}
end
# Private functions focused only on auction logic
defp determine_winner(bids) when is_list(bids) do
# Winner determination algorithm
end
defp validate_auction_spec(%AuctionSpec{} = spec) do
# Auction specification validation
end
end
Service 2: Market Data Service
defmodule MABEAM.Economics.MarketDataService do
@moduledoc """
Manages market state, price discovery, and market data aggregation.
Estimated size: ~350 lines (down from ~1,000)
"""
use GenServer
alias MABEAM.Economics.{MarketState, PriceData, TradingVolume}
# ETS-backed fast reads for market data
@market_data_table :market_data_cache
@spec get_current_market_state() :: MarketState.t()
def get_current_market_state() do
case :ets.lookup(@market_data_table, :current_state) do
[{:current_state, state}] -> state
[] -> MarketState.default()
end
end
@spec update_price_data(PriceData.t()) :: :ok
def update_price_data(%PriceData{} = price_data) do
GenServer.cast(__MODULE__, {:update_price_data, price_data})
end
@spec get_trading_volume(time_range()) :: TradingVolume.t()
def get_trading_volume(time_range) do
case :ets.lookup(@market_data_table, {:trading_volume, time_range}) do
[{_, volume}] -> volume
[] -> TradingVolume.zero()
end
end
# Asynchronous market data updates
def handle_cast({:update_price_data, price_data}, state) do
# Update market state
new_state = MarketState.update_prices(state.market_state, price_data)
# Update ETS cache for fast reads
:ets.insert(@market_data_table, {:current_state, new_state})
# Publish market update event
Foundation.Events.publish("economics.market.price_updated", %{
price_data: price_data,
new_state: new_state,
timestamp: DateTime.utc_now()
})
{:noreply, %{state | market_state: new_state}}
end
end
Service 3: Pricing Engine
defmodule MABEAM.Economics.PricingEngine do
@moduledoc """
Handles dynamic pricing, demand/supply analysis, and price predictions.
Estimated size: ~250 lines (down from ~800)
"""
# Async pricing calculations using Task delegation
@spec calculate_dynamic_price(market_conditions()) :: {:ok, calculation_id()}
def calculate_dynamic_price(market_conditions) do
calculation_id = generate_calculation_id()
Task.Supervisor.start_child(MABEAM.Economics.TaskSupervisor, fn ->
price = perform_pricing_calculation(market_conditions)
# Publish pricing result
Foundation.Events.publish("economics.pricing.calculated", %{
calculation_id: calculation_id,
price: price,
market_conditions: market_conditions,
calculated_at: DateTime.utc_now()
})
# Cache result
:ets.insert(:pricing_cache, {market_conditions_hash(market_conditions), price})
end)
{:ok, calculation_id}
end
@spec get_cached_price(market_conditions()) :: {:ok, price()} | {:error, :not_cached}
def get_cached_price(market_conditions) do
cache_key = market_conditions_hash(market_conditions)
case :ets.lookup(:pricing_cache, cache_key) do
[{^cache_key, price}] -> {:ok, price}
[] -> {:error, :not_cached}
end
end
# Demand/supply analysis functions
defp analyze_demand_supply(market_conditions) do
# Focused demand/supply analysis logic
end
defp perform_pricing_calculation(market_conditions) do
# Core pricing algorithm implementation
end
end
Service 4: Economic Agent Behavior Service
defmodule MABEAM.Economics.AgentBehaviorService do
@moduledoc """
Models economic behavior, resource allocation, and decision making for agents.
Estimated size: ~280 lines (down from ~700)
"""
alias MABEAM.Economics.{AgentProfile, ResourceAllocation, EconomicDecision}
@spec analyze_agent_behavior(agent_id(), behavior_context()) ::
{:ok, EconomicDecision.t()} | {:error, term()}
def analyze_agent_behavior(agent_id, context) do
with {:ok, profile} <- get_agent_profile(agent_id),
{:ok, allocation} <- calculate_resource_allocation(profile, context),
{:ok, decision} <- make_economic_decision(profile, allocation, context) do
{:ok, decision}
end
end
@spec update_agent_performance(agent_id(), performance_metrics()) :: :ok
def update_agent_performance(agent_id, metrics) do
GenServer.cast(__MODULE__, {:update_performance, agent_id, metrics})
end
# Agent behavior modeling functions
defp calculate_resource_allocation(profile, context) do
# Resource allocation strategy based on agent profile
end
defp make_economic_decision(profile, allocation, context) do
# Economic decision making algorithm
end
end
Service 5: Transaction Processing Service
defmodule MABEAM.Economics.TransactionProcessor do
@moduledoc """
Handles payment processing, validation, settlement, and fee calculations.
Estimated size: ~200 lines (down from ~600)
"""
alias MABEAM.Economics.{Transaction, Payment, Settlement}
@spec process_transaction(Transaction.t()) :: {:ok, transaction_id()} | {:error, term()}
def process_transaction(%Transaction{} = transaction) do
transaction_id = generate_transaction_id()
# Asynchronous transaction processing
Task.Supervisor.start_child(MABEAM.Economics.TaskSupervisor, fn ->
case validate_and_process_transaction(transaction) do
{:ok, result} ->
Foundation.Events.publish("economics.transaction.completed", %{
transaction_id: transaction_id,
result: result,
processed_at: DateTime.utc_now()
})
{:error, reason} ->
Foundation.Events.publish("economics.transaction.failed", %{
transaction_id: transaction_id,
reason: reason,
failed_at: DateTime.utc_now()
})
end
end)
{:ok, transaction_id}
end
defp validate_and_process_transaction(transaction) do
with :ok <- validate_transaction(transaction),
{:ok, payment_result} <- process_payment(transaction.payment),
{:ok, settlement} <- create_settlement(transaction, payment_result) do
{:ok, %{payment: payment_result, settlement: settlement}}
end
end
end
Service 6: Economics Analytics Service
defmodule MABEAM.Economics.AnalyticsService do
@moduledoc """
Generates economic metrics, performance reports, and market analysis.
Estimated size: ~180 lines (down from ~500)
"""
alias MABEAM.Economics.{MetricsReport, PerformanceAnalysis, MarketAnalysis}
@spec generate_metrics_report(time_period()) :: {:ok, MetricsReport.t()}
def generate_metrics_report(time_period) do
# Delegate report generation to background task
Task.Supervisor.start_child(MABEAM.Economics.TaskSupervisor, fn ->
report = compile_metrics_report(time_period)
# Cache report for fast access
:ets.insert(:analytics_cache, {{:metrics_report, time_period}, report})
# Publish report availability
Foundation.Events.publish("economics.analytics.report_ready", %{
report_type: :metrics,
time_period: time_period,
generated_at: DateTime.utc_now()
})
end)
{:ok, :report_generation_started}
end
@spec get_cached_report(report_type(), time_period()) ::
{:ok, report()} | {:error, :not_available}
def get_cached_report(report_type, time_period) do
case :ets.lookup(:analytics_cache, {report_type, time_period}) do
[{_, report}] -> {:ok, report}
[] -> {:error, :not_available}
end
end
end
Service 7: Economics Rules Engine
defmodule MABEAM.Economics.RulesEngine do
@moduledoc """
Manages economic rules, market configuration, and policy enforcement.
Estimated size: ~160 lines (down from ~400)
"""
alias MABEAM.Economics.{Rule, Policy, Compliance}
@spec validate_economic_action(action_type(), action_params()) ::
:ok | {:error, compliance_violation()}
def validate_economic_action(action_type, action_params) do
applicable_rules = get_applicable_rules(action_type)
case apply_rules(applicable_rules, action_params) do
[] -> :ok
violations -> {:error, {:compliance_violations, violations}}
end
end
@spec update_economic_policy(Policy.t()) :: :ok | {:error, term()}
def update_economic_policy(%Policy{} = policy) do
GenServer.call(__MODULE__, {:update_policy, policy})
end
defp get_applicable_rules(action_type) do
# Fast rule lookup from ETS
case :ets.lookup(:economic_rules, action_type) do
[{^action_type, rules}] -> rules
[] -> []
end
end
end
Service 8: Economics Integration Hub
defmodule MABEAM.Economics.IntegrationHub do
@moduledoc """
Handles external system integration, event routing, and API coordination.
Estimated size: ~140 lines (down from ~357)
"""
@spec sync_with_external_market(market_id()) :: :ok | {:error, term()}
def sync_with_external_market(market_id) do
GenServer.cast(__MODULE__, {:sync_external_market, market_id})
end
@spec handle_external_event(external_event()) :: :ok
def handle_external_event(external_event) do
# Route external events to appropriate internal services
case determine_event_destination(external_event) do
:auction_manager ->
Foundation.Events.publish("economics.auction.external_event", external_event)
:market_data ->
Foundation.Events.publish("economics.market.external_update", external_event)
:pricing_engine ->
Foundation.Events.publish("economics.pricing.external_signal", external_event)
_ ->
Logger.warn("Unhandled external event", event: external_event)
end
end
end
2. Coordination Module Decomposition Strategy (5,313 lines → 7 focused services)
2.1 Current Architecture Analysis
Identified Responsibilities in Coordination Module
- Agent Coordination (~1,100 lines) - Agent lifecycle, communication, state management
- Task Distribution (~900 lines) - Work assignment, load balancing, task scheduling
- Consensus Protocols (~800 lines) - Distributed consensus, voting, agreement algorithms
- Communication Management (~700 lines) - Message routing, protocol handling, channels
- Synchronization Primitives (~600 lines) - Barriers, locks, semaphores, coordination points
- Fault Tolerance (~500 lines) - Failure detection, recovery, redundancy management
- Performance Monitoring (~713 lines) - Metrics collection, performance analysis, optimization
2.2 Decomposed Coordination Architecture
Service 1: Agent Coordination Service
defmodule MABEAM.Coordination.AgentCoordinator do
@moduledoc """
Manages agent coordination, lifecycle, and state synchronization.
Estimated size: ~350 lines (down from ~1,100)
"""
alias MABEAM.Coordination.{AgentGroup, CoordinationPlan, AgentState}
@spec coordinate_agent_group(AgentGroup.t()) :: {:ok, coordination_id()} | {:error, term()}
def coordinate_agent_group(%AgentGroup{} = group) do
coordination_id = generate_coordination_id()
# Event-driven coordination initiation
Foundation.Events.publish("coordination.agent_group.initiated", %{
coordination_id: coordination_id,
group: group,
initiated_at: DateTime.utc_now()
})
{:ok, coordination_id}
end
@spec update_agent_coordination_state(agent_id(), AgentState.t()) :: :ok
def update_agent_coordination_state(agent_id, %AgentState{} = state) do
# Fast ETS update for coordination state
:ets.insert(:agent_coordination_states, {agent_id, state})
# Event notification for state change
Foundation.Events.publish("coordination.agent.state_updated", %{
agent_id: agent_id,
new_state: state,
updated_at: DateTime.utc_now()
})
:ok
end
@spec get_coordination_status(coordination_id()) ::
{:ok, coordination_status()} | {:error, :not_found}
def get_coordination_status(coordination_id) do
# Fast ETS lookup
case :ets.lookup(:coordination_status, coordination_id) do
[{^coordination_id, status}] -> {:ok, status}
[] -> {:error, :not_found}
end
end
end
Service 2: Task Distribution Service
defmodule MABEAM.Coordination.TaskDistributor do
@moduledoc """
Handles work assignment, load balancing, and task scheduling.
Estimated size: ~300 lines (down from ~900)
"""
alias MABEAM.Coordination.{Task, WorkAssignment, LoadBalancer}
@spec distribute_task(Task.t()) :: {:ok, distribution_id()} | {:error, term()}
def distribute_task(%Task{} = task) do
distribution_id = generate_distribution_id()
# Async task distribution using background process
Task.Supervisor.start_child(MABEAM.Coordination.TaskSupervisor, fn ->
case find_optimal_agent_assignment(task) do
{:ok, assignment} ->
execute_task_assignment(assignment)
record_distribution_success(distribution_id, assignment)
{:error, reason} ->
record_distribution_failure(distribution_id, reason)
end
end)
{:ok, distribution_id}
end
@spec get_agent_load(agent_id()) :: {:ok, load_metrics()} | {:error, :not_found}
def get_agent_load(agent_id) do
case :ets.lookup(:agent_loads, agent_id) do
[{^agent_id, load_metrics}] -> {:ok, load_metrics}
[] -> {:error, :not_found}
end
end
defp find_optimal_agent_assignment(task) do
# Load balancing algorithm implementation
end
end
Service 3: Consensus Protocol Service
defmodule MABEAM.Coordination.ConsensusProtocol do
@moduledoc """
Implements distributed consensus, voting, and agreement algorithms.
Estimated size: ~280 lines (down from ~800)
"""
alias MABEAM.Coordination.{Proposal, Vote, ConsensusResult}
@spec initiate_consensus(Proposal.t()) :: {:ok, consensus_id()} | {:error, term()}
def initiate_consensus(%Proposal{} = proposal) do
consensus_id = generate_consensus_id()
# Initialize consensus state in ETS
consensus_state = %{
proposal: proposal,
votes: %{},
status: :voting,
initiated_at: DateTime.utc_now()
}
:ets.insert(:consensus_states, {consensus_id, consensus_state})
# Publish consensus initiation event
Foundation.Events.publish("coordination.consensus.initiated", %{
consensus_id: consensus_id,
proposal: proposal
})
{:ok, consensus_id}
end
@spec cast_vote(consensus_id(), agent_id(), Vote.t()) :: :ok | {:error, term()}
def cast_vote(consensus_id, agent_id, %Vote{} = vote) do
case :ets.lookup(:consensus_states, consensus_id) do
[{^consensus_id, consensus_state}] ->
updated_state = record_vote(consensus_state, agent_id, vote)
:ets.insert(:consensus_states, {consensus_id, updated_state})
# Check if consensus reached
check_consensus_completion(consensus_id, updated_state)
:ok
[] ->
{:error, :consensus_not_found}
end
end
defp check_consensus_completion(consensus_id, consensus_state) do
if consensus_reached?(consensus_state) do
result = calculate_consensus_result(consensus_state)
Foundation.Events.publish("coordination.consensus.completed", %{
consensus_id: consensus_id,
result: result,
completed_at: DateTime.utc_now()
})
end
end
end
Service 4: Communication Management Service
defmodule MABEAM.Coordination.CommunicationManager do
@moduledoc """
Manages message routing, protocol handling, and communication channels.
Estimated size: ~250 lines (down from ~700)
"""
alias MABEAM.Coordination.{Message, Channel, RoutingRule}
@spec send_coordination_message(Message.t()) :: :ok | {:error, term()}
def send_coordination_message(%Message{} = message) do
case determine_routing(message) do
{:ok, routing} ->
execute_message_routing(message, routing)
{:error, reason} ->
Logger.error("Message routing failed", message: message, reason: reason)
{:error, reason}
end
end
@spec create_communication_channel(channel_spec()) ::
{:ok, channel_id()} | {:error, term()}
def create_communication_channel(channel_spec) do
channel_id = generate_channel_id()
# Create channel in ETS for fast access
channel = Channel.create(channel_id, channel_spec)
:ets.insert(:communication_channels, {channel_id, channel})
# Publish channel creation event
Foundation.Events.publish("coordination.channel.created", %{
channel_id: channel_id,
spec: channel_spec,
created_at: DateTime.utc_now()
})
{:ok, channel_id}
end
defp determine_routing(message) do
# Message routing logic based on content and destination
end
defp execute_message_routing(message, routing) do
# Execute message delivery based on routing rules
end
end
Service 5: Synchronization Primitives Service
defmodule MABEAM.Coordination.SynchronizationPrimitives do
@moduledoc """
Implements barriers, locks, semaphores, and coordination points.
Estimated size: ~220 lines (down from ~600)
"""
alias MABEAM.Coordination.{Barrier, Lock, Semaphore}
@spec create_coordination_barrier(barrier_spec()) :: {:ok, barrier_id()}
def create_coordination_barrier(barrier_spec) do
barrier_id = generate_barrier_id()
barrier_state = %{
spec: barrier_spec,
participants: %{},
status: :waiting,
created_at: DateTime.utc_now()
}
:ets.insert(:coordination_barriers, {barrier_id, barrier_state})
{:ok, barrier_id}
end
@spec wait_at_barrier(barrier_id(), participant_id()) :: :ok | {:error, term()}
def wait_at_barrier(barrier_id, participant_id) do
case :ets.lookup(:coordination_barriers, barrier_id) do
[{^barrier_id, barrier_state}] ->
updated_state = add_participant_to_barrier(barrier_state, participant_id)
:ets.insert(:coordination_barriers, {barrier_id, updated_state})
if barrier_complete?(updated_state) do
notify_barrier_completion(barrier_id)
:ok
else
wait_for_barrier_completion(barrier_id)
end
[] ->
{:error, :barrier_not_found}
end
end
defp wait_for_barrier_completion(barrier_id) do
receive do
{:barrier_complete, ^barrier_id} -> :ok
after
30_000 -> {:error, :barrier_timeout}
end
end
end
Service 6: Fault Tolerance Service
defmodule MABEAM.Coordination.FaultToleranceManager do
@moduledoc """
Handles failure detection, recovery, and redundancy management.
Estimated size: ~200 lines (down from ~500)
"""
alias MABEAM.Coordination.{FailureDetector, RecoveryPlan, RedundancyManager}
@spec monitor_coordination_health() :: :ok
def monitor_coordination_health() do
GenServer.cast(__MODULE__, :perform_health_check)
end
@spec handle_coordination_failure(failure_event()) :: {:ok, recovery_plan()}
def handle_coordination_failure(failure_event) do
# Async failure handling
Task.Supervisor.start_child(MABEAM.Coordination.TaskSupervisor, fn ->
recovery_plan = create_recovery_plan(failure_event)
execute_recovery_plan(recovery_plan)
Foundation.Events.publish("coordination.fault_tolerance.recovery_completed", %{
failure_event: failure_event,
recovery_plan: recovery_plan,
recovered_at: DateTime.utc_now()
})
end)
{:ok, :recovery_initiated}
end
def handle_cast(:perform_health_check, state) do
# Perform health checks on coordination components
health_status = check_coordination_component_health()
case detect_failures(health_status) do
[] -> :ok
failures ->
Enum.each(failures, &handle_coordination_failure/1)
end
{:noreply, state}
end
defp create_recovery_plan(failure_event) do
# Create recovery plan based on failure type and context
end
end
Service 7: Coordination Performance Monitor
defmodule MABEAM.Coordination.PerformanceMonitor do
@moduledoc """
Collects metrics, analyzes performance, and provides optimization recommendations.
Estimated size: ~190 lines (down from ~713)
"""
alias MABEAM.Coordination.{PerformanceMetrics, OptimizationReport}
@spec collect_coordination_metrics() :: :ok
def collect_coordination_metrics() do
GenServer.cast(__MODULE__, :collect_metrics)
end
@spec get_performance_report(time_period()) ::
{:ok, PerformanceMetrics.t()} | {:error, :not_available}
def get_performance_report(time_period) do
case :ets.lookup(:performance_reports, time_period) do
[{^time_period, report}] -> {:ok, report}
[] -> {:error, :not_available}
end
end
def handle_cast(:collect_metrics, state) do
# Collect performance metrics from all coordination services
metrics = gather_coordination_metrics()
# Update ETS cache
current_period = get_current_time_period()
:ets.insert(:performance_reports, {current_period, metrics})
# Check for performance issues
case analyze_performance_issues(metrics) do
[] -> :ok
issues ->
Foundation.Events.publish("coordination.performance.issues_detected", %{
issues: issues,
metrics: metrics,
detected_at: DateTime.utc_now()
})
end
{:noreply, state}
end
defp gather_coordination_metrics() do
# Collect metrics from all coordination services
end
end
3. Migration Strategy and Implementation Plan
3.1 Phased Decomposition Approach
Phase 1: Service Extraction (Weeks 1-2)
defmodule MABEAM.Migration.ServiceExtractor do
@moduledoc """
Utilities for extracting services from monolithic modules.
"""
@spec extract_service_from_module(
source_module :: atom(),
target_service :: atom(),
functions :: [atom()]
) :: {:ok, extraction_result()} | {:error, term()}
def extract_service_from_module(source_module, target_service, functions) do
with :ok <- validate_extraction_feasibility(source_module, functions),
{:ok, extracted_code} <- extract_functions(source_module, functions),
{:ok, service_module} <- create_service_module(target_service, extracted_code),
:ok <- setup_service_supervision(target_service),
:ok <- update_client_references(source_module, target_service, functions) do
{:ok, %{
extracted_functions: functions,
service_module: service_module,
clients_updated: true
}}
end
end
# Service supervision setup
defp setup_service_supervision(service_module) do
# Add service to appropriate supervision tree
case service_module do
module when module in [
MABEAM.Economics.AuctionManager,
MABEAM.Economics.MarketDataService,
MABEAM.Economics.PricingEngine
] ->
add_to_economics_supervisor(module)
module when module in [
MABEAM.Coordination.AgentCoordinator,
MABEAM.Coordination.TaskDistributor,
MABEAM.Coordination.ConsensusProtocol
] ->
add_to_coordination_supervisor(module)
end
end
end
Phase 2: Interface Establishment (Week 3)
defmodule MABEAM.Migration.InterfaceEstablisher do
@moduledoc """
Establishes clean interfaces between decomposed services.
"""
@spec establish_service_interfaces(services :: [atom()]) :: :ok | {:error, term()}
def establish_service_interfaces(services) do
Enum.each(services, fn service ->
create_service_interface(service)
setup_event_subscriptions(service)
configure_service_dependencies(service)
end)
end
defp create_service_interface(service) do
# Create standardized service interface
interface_module = Module.concat([service, "Interface"])
# Generate interface based on service public functions
public_functions = get_public_functions(service)
create_interface_module(interface_module, public_functions)
end
defp setup_event_subscriptions(service) do
# Setup appropriate event subscriptions for each service
subscriptions = determine_event_subscriptions(service)
Enum.each(subscriptions, fn {event_pattern, handler} ->
Foundation.Events.subscribe(service, event_pattern, handler)
end)
end
end
Phase 3: Data Migration (Week 4)
defmodule MABEAM.Migration.DataMigrator do
@moduledoc """
Migrates data from monolithic GenServer state to distributed service states.
"""
@spec migrate_economics_data() :: {:ok, migration_result()} | {:error, term()}
def migrate_economics_data() do
# Extract current economics state
{:ok, current_state} = get_current_economics_state()
# Distribute data to appropriate services
migration_tasks = [
migrate_auction_data(current_state.auctions),
migrate_market_data(current_state.market_data),
migrate_pricing_data(current_state.pricing_data),
migrate_agent_behavior_data(current_state.agent_data),
migrate_transaction_data(current_state.transactions),
migrate_analytics_data(current_state.analytics)
]
# Execute migrations concurrently
results = Task.await_many(migration_tasks, 30_000)
# Verify migration success
case verify_data_migration() do
:ok -> {:ok, %{migrated_services: 6, verification: :passed}}
{:error, reason} -> {:error, {:migration_verification_failed, reason}}
end
end
defp migrate_auction_data(auction_data) do
Task.async(fn ->
Enum.each(auction_data, fn {auction_id, auction_state} ->
MABEAM.Economics.AuctionManager.restore_auction_state(auction_id, auction_state)
end)
end)
end
defp verify_data_migration() do
# Comprehensive verification that all data was migrated correctly
verification_checks = [
verify_auction_data_integrity(),
verify_market_data_integrity(),
verify_pricing_data_integrity(),
verify_analytics_data_integrity()
]
case Enum.all?(verification_checks, & &1 == :ok) do
true -> :ok
false -> {:error, :data_integrity_check_failed}
end
end
end
3.2 Rollback Strategy
Rollback Implementation
defmodule MABEAM.Migration.RollbackManager do
@moduledoc """
Comprehensive rollback strategy for module decomposition.
"""
@spec rollback_decomposition(module :: atom()) ::
{:ok, rollback_result()} | {:error, term()}
def rollback_decomposition(module) do
case module do
MABEAM.Economics ->
rollback_economics_decomposition()
MABEAM.Coordination ->
rollback_coordination_decomposition()
_ ->
{:error, :unknown_module}
end
end
defp rollback_economics_decomposition() do
rollback_steps = [
:stop_decomposed_services,
:restore_original_economics_module,
:migrate_data_back_to_monolith,
:update_client_references,
:verify_rollback_success
]
execute_rollback_steps(rollback_steps, :economics)
end
defp execute_rollback_steps(steps, module) do
Enum.reduce_while(steps, {:ok, []}, fn step, {:ok, completed_steps} ->
case execute_rollback_step(step, module) do
:ok ->
{:cont, {:ok, [step | completed_steps]}}
{:error, reason} ->
{:halt, {:error, {step, reason, completed_steps}}}
end
end)
end
defp execute_rollback_step(:stop_decomposed_services, :economics) do
services = [
MABEAM.Economics.AuctionManager,
MABEAM.Economics.MarketDataService,
MABEAM.Economics.PricingEngine,
MABEAM.Economics.AgentBehaviorService,
MABEAM.Economics.TransactionProcessor,
MABEAM.Economics.AnalyticsService
]
Enum.each(services, fn service ->
GenServer.stop(service, :normal, 5_000)
end)
:ok
end
end
4. Testing Strategy for Decomposed Modules
4.1 Service Integration Testing
Integration Test Framework
defmodule MABEAM.Test.ServiceIntegration do
@moduledoc """
Integration testing framework for decomposed services.
"""
use ExUnit.Case
describe "Economics service integration" do
test "auction creation triggers market data update" do
# Setup
auction_spec = build_auction_spec()
# Subscribe to market data events
Foundation.Events.subscribe(self(), "economics.market.auction_created")
# Create auction
{:ok, auction_id} = MABEAM.Economics.AuctionManager.create_auction(auction_spec)
# Verify market data service receives event
assert_receive {:event, "economics.market.auction_created", %{auction_id: ^auction_id}}, 1_000
# Verify market state was updated
market_state = MABEAM.Economics.MarketDataService.get_current_market_state()
assert market_state.active_auctions[auction_id] != nil
end
test "pricing calculation triggers analytics update" do
market_conditions = build_market_conditions()
# Subscribe to analytics events
Foundation.Events.subscribe(self(), "economics.analytics.pricing_updated")
# Trigger pricing calculation
{:ok, calculation_id} =
MABEAM.Economics.PricingEngine.calculate_dynamic_price(market_conditions)
# Wait for calculation completion
assert_receive {:event, "economics.pricing.calculated", %{calculation_id: ^calculation_id}}, 5_000
# Verify analytics service was notified
assert_receive {:event, "economics.analytics.pricing_updated", _}, 1_000
end
end
describe "Coordination service integration" do
test "agent coordination triggers task distribution" do
agent_group = build_agent_group()
# Subscribe to task distribution events
Foundation.Events.subscribe(self(), "coordination.task.distribution_started")
# Initiate coordination
{:ok, coordination_id} =
MABEAM.Coordination.AgentCoordinator.coordinate_agent_group(agent_group)
# Verify task distribution was triggered
assert_receive {:event, "coordination.task.distribution_started",
%{coordination_id: ^coordination_id}}, 2_000
end
end
end
4.2 Performance Testing for Decomposed Services
Performance Validation Framework
defmodule MABEAM.Test.DecompositionPerformance do
@moduledoc """
Performance testing to validate decomposition benefits.
"""
use ExUnit.Case
test "decomposed economics services handle concurrent load" do
concurrent_operations = 1000
# Test concurrent auction operations
auction_tasks = Enum.map(1..concurrent_operations, fn _i ->
Task.async(fn ->
auction_spec = build_auction_spec()
start_time = System.monotonic_time(:microsecond)
{:ok, _auction_id} = MABEAM.Economics.AuctionManager.create_auction(auction_spec)
end_time = System.monotonic_time(:microsecond)
end_time - start_time
end)
end)
# Wait for all operations to complete
durations = Task.await_many(auction_tasks, 30_000)
# Validate performance characteristics
avg_duration = Enum.sum(durations) / length(durations)
max_duration = Enum.max(durations)
# Performance should be better than monolithic version
assert avg_duration < 50_000 # 50ms average
assert max_duration < 200_000 # 200ms max
assert length(durations) == concurrent_operations # All operations succeeded
end
test "decomposed coordination services maintain low latency" do
# Test coordination latency with decomposed services
coordination_operations = 500
latency_measurements = Enum.map(1..coordination_operations, fn _i ->
agent_group = build_agent_group()
start_time = System.monotonic_time(:microsecond)
{:ok, _coordination_id} =
MABEAM.Coordination.AgentCoordinator.coordinate_agent_group(agent_group)
end_time = System.monotonic_time(:microsecond)
end_time - start_time
end)
# Validate latency characteristics
avg_latency = Enum.sum(latency_measurements) / length(latency_measurements)
p95_latency = percentile(latency_measurements, 95)
assert avg_latency < 10_000 # 10ms average
assert p95_latency < 50_000 # 50ms p95
end
end
Conclusion
This comprehensive decomposition strategy transforms two massive monolithic modules into 15 focused, maintainable services:
Economics Module: 5,557 lines → 8 services (~2,260 total lines, 59% reduction) Coordination Module: 5,313 lines → 7 services (~2,010 total lines, 62% reduction)
Key Benefits Achieved:
- Maintainability: Clear separation of concerns with focused responsibilities
- Performance: Elimination of GenServer bottlenecks through service distribution
- Scalability: Independent scaling of services based on load requirements
- Fault Tolerance: Isolated failure domains with targeted recovery strategies
- Testability: Focused unit tests and comprehensive integration testing
- Development Velocity: Parallel development across service boundaries
Implementation Priority: MEDIUM - After critical architecture fixes Dependencies: GenServer bottleneck elimination, Foundation event system Testing Requirements: Comprehensive integration and performance validation