Agentic Integration in Software Testing

# Agentic Testing Framework Implementation
import asyncio
import json
from typing import Dict, List, Any, Optional
from dataclasses import dataclass, field
from enum import Enum
from datetime import datetime

class AgentType(Enum):
    EXPLORER = "explorer"  # Discovers new test scenarios
    EXECUTOR = "executor"  # Runs tests and collects results
    ANALYZER = "analyzer"  # Analyzes results and identifies issues
    MAINTAINER = "maintainer"  # Updates and maintains test suites
    ORCHESTRATOR = "orchestrator"  # Coordinates other agents

@dataclass
class TestingContext:
    """Shared context for all testing agents"""
    application_url: str
    test_environment: str
    current_build: str
    test_history: List[Dict] = field(default_factory=list)
    known_issues: List[Dict] = field(default_factory=list)
    performance_baselines: Dict[str, float] = field(default_factory=dict)
    
class BaseTestingAgent:
    """Base class for all testing agents"""
    
    def __init__(self, agent_id: str, agent_type: AgentType, context: TestingContext):
        self.agent_id = agent_id
        self.agent_type = agent_type
        self.context = context
        self.memory = []
        self.capabilities = []
        
    async def observe(self) -> Dict[str, Any]:
        """Observe current application state"""
        pass
        
    async def reason(self, observations: Dict[str, Any]) -> Dict[str, Any]:
        """Reason about observations and plan actions"""
        pass
        
    async def act(self, plan: Dict[str, Any]) -> Dict[str, Any]:
        """Execute planned actions"""
        pass
        
    async def learn(self, results: Dict[str, Any]) -> None:
        """Learn from action results"""
        self.memory.append({
            'timestamp': datetime.now().isoformat(),
            'action': results.get('action'),
            'outcome': results.get('outcome'),
            'effectiveness': results.get('effectiveness', 0.5)
        })

print("Agentic Testing Framework Base Classes Defined")
print("Ready for specialized agent implementations")

# Specialized Testing Agent Implementation Examples

class ExplorerAgent(BaseTestingAgent):
    """Agent specialized in discovering new test scenarios"""
    
    def __init__(self, context: TestingContext):
        super().__init__("explorer-001", AgentType.EXPLORER, context)
        self.capabilities = [
            "web_crawling", "user_flow_analysis", "edge_case_discovery",
            "accessibility_scanning", "security_probing"
        ]
    
    async def observe(self) -> Dict[str, Any]:
        """Observe application for new testing opportunities"""
        return {
            "new_endpoints": await self._discover_endpoints(),
            "user_interactions": await self._analyze_user_flows(),
            "ui_changes": await self._detect_ui_changes(),
            "performance_patterns": await self._monitor_performance()
        }
    
    async def reason(self, observations: Dict[str, Any]) -> Dict[str, Any]:
        """Generate test scenarios based on observations"""
        scenarios = []
        
        # Generate scenarios for new endpoints
        for endpoint in observations.get("new_endpoints", []):
            scenarios.append({
                "type": "api_test",
                "target": endpoint,
                "priority": self._calculate_priority(endpoint),
                "test_types": ["happy_path", "error_handling", "boundary_testing"]
            })
        
        # Generate scenarios for UI changes
        for change in observations.get("ui_changes", []):
            scenarios.append({
                "type": "ui_test",
                "target": change["element"],
                "priority": "high" if change["breaking"] else "medium",
                "test_types": ["visual_regression", "interaction_testing"]
            })
        
        return {"test_scenarios": scenarios}

class ExecutorAgent(BaseTestingAgent):
    """Agent specialized in test execution"""
    
    def __init__(self, context: TestingContext):
        super().__init__("executor-001", AgentType.EXECUTOR, context)
        self.capabilities = [
            "playwright_automation", "api_testing", "performance_testing",
            "parallel_execution", "result_collection"
        ]
    
    async def execute_test_scenario(self, scenario: Dict[str, Any]) -> Dict[str, Any]:
        """Execute a test scenario"""
        results = {
            "scenario_id": scenario.get("id"),
            "start_time": datetime.now().isoformat(),
            "status": "running",
            "test_results": []
        }
        
        try:
            if scenario["type"] == "api_test":
                results["test_results"] = await self._execute_api_tests(scenario)
            elif scenario["type"] == "ui_test":
                results["test_results"] = await self._execute_ui_tests(scenario)
            
            results["status"] = "completed"
            results["end_time"] = datetime.now().isoformat()
            
        except Exception as e:
            results["status"] = "failed"
            results["error"] = str(e)
            results["end_time"] = datetime.now().isoformat()
        
        return results

print("Specialized Testing Agents Implemented")
print("Explorer Agent: Discovers new test scenarios")
print("Executor Agent: Runs tests autonomously")

# Multi-Agent Orchestration System

class TestingOrchestrator(BaseTestingAgent):
    """Orchestrator agent that coordinates specialized testing agents"""
    
    def __init__(self, context: TestingContext):
        super().__init__("orchestrator-001", AgentType.ORCHESTRATOR, context)
        self.agents = {}
        self.message_queue = []
        self.shared_knowledge = {
            "test_repository": {},
            "execution_history": [],
            "application_model": {},
            "active_issues": []
        }
    
    def register_agent(self, agent: BaseTestingAgent):
        """Register a specialized agent with the orchestrator"""
        self.agents[agent.agent_id] = agent
        print(f"Registered {agent.agent_type.value} agent: {agent.agent_id}")
    
    async def coordinate_testing_cycle(self) -> Dict[str, Any]:
        """Coordinate a complete testing cycle across all agents"""
        cycle_results = {
            "cycle_id": f"cycle_{datetime.now().strftime('%Y%m%d_%H%M%S')}",
            "start_time": datetime.now().isoformat(),
            "phases": []
        }
        
        # Phase 1: Discovery
        explorer_agents = [a for a in self.agents.values() if a.agent_type == AgentType.EXPLORER]
        discovery_results = []
        
        for explorer in explorer_agents:
            observations = await explorer.observe()
            scenarios = await explorer.reason(observations)
            discovery_results.append(scenarios)
        
        cycle_results["phases"].append({
            "phase": "discovery",
            "results": discovery_results
        })
        
        # Phase 2: Execution
        executor_agents = [a for a in self.agents.values() if a.agent_type == AgentType.EXECUTOR]
        execution_results = []
        
        for result in discovery_results:
            for scenario in result.get("test_scenarios", []):
                for executor in executor_agents:
                    if self._can_execute_scenario(executor, scenario):
                        exec_result = await executor.execute_test_scenario(scenario)
                        execution_results.append(exec_result)
                        break
        
        cycle_results["phases"].append({
            "phase": "execution",
            "results": execution_results
        })
        
        return cycle_results

print("Multi-Agent Orchestration System Implemented")
print("Ready to coordinate specialized testing agents")