Integration Testing Patterns

This document covers integration testing strategies and patterns for multi-agent systems built with the agent-swarm-kit framework. It focuses on testing complete workflows involving agent interactions, session management, tool execution, and AI model integration. For unit testing individual components, see API Reference. For system performance testing, see Performance Monitoring.

Testing Architecture Overview

The agent-swarm-kit employs a comprehensive integration testing approach that validates end-to-end workflows across the entire system stack. Tests verify agent orchestration, session management, concurrent execution, and AI model integration patterns.

Mock Completion Patterns

Integration tests rely heavily on mock AI completions to provide deterministic, controllable responses. This approach isolates the testing from external AI service dependencies while maintaining realistic interaction patterns.

Basic Mock Completion Structure

Mock completions typically follow this pattern:

Pattern	Purpose	Example Usage
Message Echo	Return user input as response	Testing message flow
Tool Call Generation	Generate specific tool calls	Testing tool execution
State-based Response	Different responses based on agent state	Testing navigation
Incremental Counter	Numeric progression for concurrency testing	Testing parallel execution

Tool Call Mock Pattern

Concurrent Execution Testing

The framework includes extensive concurrent execution testing to validate message queuing, session isolation, and parallel agent operations.

Parallel Session Testing Pattern

The connection test demonstrates this pattern by running 50 parallel sessions with the same CLIENT_ID to verify proper message queuing:

Message Queue Validation

Agent Navigation Testing

Navigation testing validates agent transitions, swarm orchestration, and deadlock prevention mechanisms.

Navigation Test Architecture

Deadlock Prevention Testing

The framework includes specific tests for deadlock prevention when tools don't properly commit their outputs:

Connection Lifecycle Testing

Connection disposal and cleanup testing ensures proper resource management and prevents memory leaks in long-running systems.

Connection Disposal Pattern

Error Recovery Testing

The rescue (resque) testing validates error handling, model recovery, and graceful degradation patterns.

Rescue Strategy Testing

Validation Testing Patterns

Dependency validation testing ensures that all required components are properly configured before system execution.

Validation Test Matrix

Test Case	Missing Component	Expected Result
Complete Setup	None	Pass
Missing Swarm	addSwarm() call	Validation Error
Missing Completion	addCompletion() call	Validation Error
Missing Agent	addAgent() call	Validation Error
Missing Tool	addTool() call	Validation Error
Invalid Default Agent	Wrong defaultAgent reference	Validation Error

Event System Testing

Event testing validates the custom event system used for out-of-band communication between agents and clients.

Event Flow Testing

Test Utility Patterns

Common Test Utilities

Utility	Purpose	Usage Pattern
randomString()	Generate unique client IDs	const CLIENT_ID = randomString()
sleep(ms)	Add artificial delays	await sleep(1000)
getRawHistory(clientId)	Inspect message history	Validation and debugging
getErrorMessage(error)	Extract error messages	Error handling assertions

Test Configuration Management