roadmap.md

FluentState Roadmap

This document outlines planned improvements and potential features for the FluentState library.

✅ 1. Enhanced Auto-transition Configuration

Dependencies: None

Extend the AutoTransitionConfig interface with more control over transition behavior:

interface AutoTransitionConfig<TContext = unknown> {
  condition: (state: State, context: TContext) => boolean | Promise<boolean>;
  targetState: string;
  // New properties:
  priority?: number;  // Higher priority transitions are evaluated first
  debounce?: number; // Delay evaluation by specified milliseconds
  retryConfig?: {     // Retry failed transitions
    maxAttempts: number;
    delay: number;
  };
}

Benefits:

• Better control over transition order and timing
• Improved handling of race conditions
• Automatic retry for transient failures

User Story: As a developer using FluentState in a complex application, I want to have fine-grained control over how auto-transitions are evaluated and executed, So that I can handle race conditions, prioritize certain transitions, and make my state machine more resilient to transient failures.

Acceptance Criteria:

1. Priority-based Transitions

   • When multiple auto-transitions are possible from a state, they are evaluated in order of priority (highest to lowest)
   • Transitions with the same priority are evaluated in the order they were defined
   • Transitions without a priority value default to priority 0
   • Only the first successful transition (highest priority) is executed

2. Debounced Transitions

   • When a debounce value is set, the transition evaluation waits for the specified milliseconds after the last context update
   • If another context update occurs during the debounce period, the timer resets
   • Debounced transitions maintain their priority order when evaluated
   • Resources (timers) are properly cleaned up when the state changes or the state machine is destroyed

3. Retry Configuration

   • Failed transition attempts (where condition throws an error) are retried up to maxAttempts times
   • Each retry attempt waits for the specified delay in milliseconds
   • Retries stop immediately if the condition returns false (vs throwing an error)
   • Retry attempts are logged for debugging purposes
   • The state machine remains responsive to other transitions during retry delays

Example Usage:

// Priority example
fs.from("reviewing")
  .to<Document>("approved", {
    condition: (_, doc) => doc.approvals >= 2,
    priority: 2  // Checked first
  })
  .to<Document>("rejected", {
    condition: (_, doc) => doc.rejections >= 1,
    priority: 1  // Checked second
  });

// Debounce example
fs.from("typing")
  .to<SearchState>("searching", {
    condition: (_, state) => state.query.length >= 3,
    debounce: 300  // Wait 300ms after last keystroke
  });

// Retry example
fs.from("connecting")
  .to<ApiState>("connected", {
    condition: async (_, state) => {
      const response = await checkConnection(state.endpoint);
      return response.isConnected;
    },
    retryConfig: {
      maxAttempts: 3,
      delay: 1000  // Wait 1 second between attempts
    }
  });

✅ 2. Transition History

Dependencies: None

Add a system for tracking and querying transition history:

class TransitionHistory {
  private history: Array<{
    from: string;
    to: string;
    timestamp: number;
    context: unknown;
    success: boolean;
  }> = [];

  add(entry: TransitionHistoryEntry): void;
  getLastTransition(): TransitionHistoryEntry | null;
  getTransitionsForState(stateName: string): TransitionHistoryEntry[];
  clear(): void;
}

Benefits:

• Debug complex state flows
• Audit state changes
• Time travel debugging capabilities
• Analytics and monitoring

User Story: As a developer working with complex state machines in FluentState, I want to track and query the history of state transitions, So that I can debug issues, audit state changes, implement time travel debugging, and gather analytics about my application's state flow.

Acceptance Criteria:

1. Transition Recording

   • All state transitions are recorded with their source state, target state, timestamp, context data, and success status
   • Transitions are stored in chronological order
   • Failed transition attempts are also recorded with appropriate success status
   • The history can be configured to have a maximum size limit to prevent memory issues
   • When the size limit is reached, oldest entries are removed first

2. History Querying

   • Developers can retrieve the most recent transition with getLastTransition()
   • Developers can query transitions related to a specific state with getTransitionsForState()
   • Query results maintain the chronological order of transitions
   • The API provides a way to clear the history when needed

3. Integration with State Machine

   • Transition history recording is optional and can be enabled/disabled
   • History recording has minimal performance impact on the state machine
   • The history is accessible through the state machine instance
   • History is properly maintained even during complex transition scenarios (e.g., auto-transitions, conditional transitions)

4. Serialization Support

   • Transition history can be serialized to JSON for storage or transmission
   • Sensitive context data can be filtered during serialization
   • Serialized history can be imported back into a TransitionHistory instance

Example Usage:

// Enable history tracking
const machine = new FluentState({
  initialState: "idle",
  enableHistory: true,
  historyOptions: {
    maxSize: 100,
    includeContext: true
  }
});

// Later, query the history
const lastTransition = machine.history.getLastTransition();
console.log(`Last transition: ${lastTransition.from} -> ${lastTransition.to}`);

// Get all transitions involving the "processing" state
const processingTransitions = machine.history.getTransitionsForState("processing");
console.log(`Processing state was involved in ${processingTransitions.length} transitions`);

// Export history for debugging
const serializedHistory = JSON.stringify(machine.history);

✅ 3. Batch Context Updates

Dependencies:

• Enhanced Auto-transition Configuration (for proper handling of debounced transitions during batch updates)
• State Manager Performance Optimizations (for batching configuration)

Add support for batching multiple context updates:

// In State class
async batchUpdate<T>(updates: Partial<T>[], options?: {
  // Only trigger auto-transitions after all updates are applied
  evaluateAfterComplete?: boolean;
  // Abort batch if any update fails
  atomic?: boolean;
}): Promise<boolean>;

Benefits:

• Improved performance for multiple updates
• Atomic updates when needed
• Reduced unnecessary transition evaluations

User Story: As a developer working with FluentState in a performance-sensitive application, I want to batch multiple related context updates together, So that I can optimize state machine performance, ensure atomic operations, and reduce unnecessary state transition evaluations.

Acceptance Criteria:

1. Batch Update API

   • The State class provides a batchUpdate method that accepts an array of partial context updates
   • The method returns a Promise that resolves to a boolean indicating success or failure
   • The API maintains type safety with the context type parameter
   • Updates are processed in the order they are provided in the array
   • The method supports empty update arrays (no-op) and returns true

2. Transition Evaluation Control

   • When evaluateAfterComplete is true, auto-transitions are only evaluated after all updates are applied
   • When evaluateAfterComplete is false (default), auto-transitions are evaluated after each update
   • During batch updates with evaluateAfterComplete: true, the state machine remains responsive to manual transitions
   • If auto-transitions are triggered during batch processing, they respect transition priorities and debounce settings

3. Atomic Update Support

   • When atomic is true, the entire batch fails if any single update fails
   • When atomic is true and an update fails, any previously applied updates in the batch are reverted
   • When atomic is false (default), updates are applied independently and the method returns true if any updates succeeded
   • The batch process properly handles errors and provides meaningful error information
   • Atomic operations properly clean up any resources used during the process

4. Integration with Existing Features

   • Batch updates are properly recorded in transition history when history tracking is enabled
   • Batch updates work seamlessly with debounced transitions
   • Batch updates respect transition group configurations
   • The batching mechanism works with custom equality checking functions
   • Performance metrics are available when debugging features are enabled

Example Usage:

// Basic batch update
await machine.currentState.batchUpdate([
  { counter: 1 },
  { status: 'processing' },
  { progress: 0.5 }
]);

// Atomic batch update with evaluation after completion
try {
  const success = await machine.currentState.batchUpdate(
    [
      { step1: 'complete' },
      { step2: 'complete' },
      { step3: 'complete' }
    ],
    {
      evaluateAfterComplete: true,
      atomic: true
    }
  );
  
  if (success) {
    console.log('All steps completed successfully');
  }
} catch (error) {
  console.error('Failed to complete all steps:', error);
}

✅ 4. Conditional Auto-transition Evaluation

Dependencies:

• Enhanced Auto-transition Configuration (for priority and timing control)

More granular control over when auto-transitions are evaluated:

interface AutoTransitionEvaluationConfig {
  // Only evaluate when these context properties change
  watchProperties?: string[];
  // Skip evaluation if these conditions are met
  skipIf?: (context: unknown) => boolean;
  // Custom evaluation timing
  evaluationStrategy?: 'immediate' | 'nextTick' | 'idle';
}

Benefits:

• Better performance through selective evaluation
• More predictable transition behavior
• Optimized for different use cases

User Story: As a developer working with complex state machines in FluentState, I want fine-grained control over when auto-transitions are evaluated, So that I can optimize performance, reduce unnecessary evaluations, and create more predictable state transition behavior.

Acceptance Criteria:

1. Property-based Evaluation Triggering

   • Transitions with watchProperties defined are only evaluated when those specific properties change
   • Support for deep property paths using dot notation (e.g., 'user.profile.name')
   • Support for array notation for indexed properties (e.g., 'items[0].status')
   • Proper handling of property additions/deletions, not just value changes
   • Performance improvement when many properties exist but only few trigger transitions

2. Conditional Evaluation Skipping

   • When skipIf returns true, auto-transition evaluation is completely bypassed
   • The skipIf function receives the full context object for decision making
   • Skip conditions are evaluated before any transition conditions to avoid unnecessary work
   • Skip conditions do not affect manual transitions, only auto-transitions
   • Support for multiple skip conditions with composable functions

3. Evaluation Timing Strategies

   • 'immediate' strategy evaluates transitions synchronously after context changes (default)
   • 'nextTick' strategy defers evaluation to the next event loop tick
   • 'idle' strategy uses requestIdleCallback (or polyfill) to evaluate during idle periods
   • Strategy selection affects all transitions or can be configured per transition/group
   • Appropriate fallbacks for environments without certain timing capabilities

4. Integration with Existing Features

   • Compatible with transition priorities from Enhanced Auto-transition Configuration
   • Works correctly with debounce settings and properly combines timing effects
   • Integrates with transition groups for group-level evaluation configuration
   • Evaluation strategies properly reflected in transition history
   • Evaluation control properly respects batch update configurations

Example Usage:

// Only evaluate when specific properties change
fs.from("form")
  .to<FormState>("valid", {
    condition: (_, form) => form.isValid,
    evaluationConfig: {
      watchProperties: ['values.email', 'values.password']
    }
  });

// Skip evaluation based on application state
fs.from("idle")
  .to<AppState>("loading", {
    condition: (_, state) => state.hasQueuedActions,
    evaluationConfig: {
      skipIf: (state) => state.isOffline || state.isBatteryLow
    }
  });

// Use idle time for non-critical transitions
fs.from("data")
  .to<DataState>("analyzed", {
    condition: (_, data) => data.needsAnalysis,
    evaluationConfig: {
      evaluationStrategy: 'idle'  // Process during browser idle time
    }
  });

✅ 5. Transition Groups

Dependencies:

• Enhanced Auto-transition Configuration (for group-level configuration inheritance)

Organize related transitions into manageable groups:

class TransitionGroup {
  constructor(name: string);
  addTransition(from: string, to: string, config?: AutoTransitionConfig): void;
  enable(): void;
  disable(): void;
  isEnabled(): boolean;
}

// Usage example
const uploadFlow = new TransitionGroup('upload');
uploadFlow.addTransition('idle', 'uploading', { /* config */ });
uploadFlow.addTransition('uploading', 'processing', { /* config */ });
fs.addGroup(uploadFlow);

Benefits:

• Better organization of complex state machines
• Ability to enable/disable groups of transitions
• Improved maintainability

User Story: As a developer working with complex state machines in FluentState, I want to organize related transitions into logical groups that can be managed collectively, So that I can better structure my application's state flow, enable/disable sets of transitions as a unit, and improve the maintainability of my state machine.

Acceptance Criteria:

1. Group Creation and Management

   • ✅ Developers can create transition groups using a fluent API: fluentState.createGroup('groupName')
   • ✅ Groups can be chained with additional configuration: fluentState.createGroup('groupName').withConfig({ priority: 2 })
   • ✅ Groups can be retrieved using a fluent method: fluentState.group('groupName')
   • ✅ Return null or throw a specific error when a group is not found
   • ✅ The API prevents duplicate group names within the same state machine
   • ✅ Groups can be removed using a fluent method: fluentState.removeGroup('groupName')
   • ✅ Provide a mechanism to list all available groups: fluentState.getAllGroups()
   • ✅ Support for group namespaces or categories (e.g., authentication:login, authentication:register)
   • ✅ Option to initialize groups from a serialized configuration object

2. Transition Definition and Organization

   • ✅ Transitions can be added to a group using a fluent syntax: group.from('stateA').to('stateB', config)
   • ✅ Multiple transitions can be chained: group.from('stateA').to('stateB').or('stateC')
   • ✅ The group maintains direct references to the original Transition objects rather than recreating them
   • ✅ Transitions in a group are properly registered with the FluentState instance
   • ✅ Transitions can be removed using a fluent method: group.removeTransition('stateA', 'stateB')
   • ✅ When a state is removed from the state machine, any transitions involving that state are automatically removed from all groups
   • ✅ Method to check if a specific transition belongs to a group: group.hasTransition('stateA', 'stateB')
   • ✅ Support for transition tagging within groups for sub-categorization

3. Group-level Configuration

   • ✅ Group-level configuration can be set using a fluent API: group.withConfig({ priority: 2, debounce: 300 })
   • ✅ Individual transition configurations override group-level configurations when both are specified
   • ✅ Configuration options include:
     • ✅ Priority levels for all transitions in the group
     • ✅ Debounce settings for all transitions in the group
     • ✅ Retry configuration for all transitions in the group
   • ✅ Support for configuration inheritance between related groups
   • ✅ Provide a method to get the effective configuration for a transition: group.getEffectiveConfig('stateA', 'stateB')
   • ✅ Support for dynamic configuration that can change based on application state

4. Group Enabling/Disabling

   • ✅ Groups can be enabled or disabled using fluent methods: group.enable() and group.disable()
   • ✅ The enabled state can be queried: group.isEnabled()
   • ✅ When a group is disabled, none of its transitions are evaluated during auto-transition evaluation
   • ✅ When a group is disabled, manual transitions within the group are still possible (unless explicitly prevented)
   • ✅ Add an option to also prevent manual transitions when a group is disabled
   • ✅ Enabling a previously disabled group immediately makes its transitions available for evaluation
   • ✅ The API provides a fluent way to temporarily disable a group: group.disableTemporarily(duration)
   • ✅ Provide a restoration callback for when a temporarily disabled group is re-enabled
   • ✅ Support for conditionally enabled groups based on a predicate function

5. Event Handling

   • ✅ Groups can have event handlers attached using a fluent API:
     • ✅ group.onTransition((from, to) => { /* handler */ })
     • ✅ group.onEnable(() => { /* handler */ })
     • ✅ group.onDisable(() => { /* handler */ })
   • ✅ Event handlers receive relevant context about the event (states involved, transition configuration, etc.)
   • ✅ Multiple handlers can be chained: group.onTransition(handler1).onTransition(handler2)
   • ✅ Add support for removing event handlers: group.offTransition(handler)
   • ✅ Add support for one-time event handlers: group.onceTransition(handler)
   • ✅ Support for event bubbling between nested groups
   • ✅ Add group-level middleware that can intercept and modify transitions

6. Integration with Existing Features

   • ✅ Transition groups work seamlessly with the existing transition history feature
   • ✅ History entries include the group name for transitions that belong to a group
   • ✅ Transition groups are compatible with the debugging and visualization tools
   • ✅ Groups can be visualized as clusters in state machine diagrams
   • ✅ Support for serialization and deserialization of group definitions
   • ✅ Integration with the proposed logging system to provide group-specific logging

7. Nested Groups and Composition

   • ✅ Support for defining groups within groups for hierarchical organization
   • ✅ Child groups inherit configuration from parent groups unless overridden
   • ✅ Enable/disable operations cascade to child groups
   • ✅ Provide methods to navigate the group hierarchy: group.parent(), group.children()
   • ✅ Support for composition patterns to reuse group definitions across state machines

8. Testing and Debugging Support

   • ✅ Provide snapshot capabilities for group state: group.createSnapshot()
   • ✅ Provide metrics on group transition frequency and performance

Example Usage:

// Create a group for user authentication flow with fluent API
const authFlow = fluentState.createGroup('authentication')
  .withConfig({
    priority: 2,
    retryConfig: {
      maxAttempts: 3,
      delay: 1000
    }
  });

// Add transitions to the group with fluent syntax
authFlow
  .from('loggedOut').to('authenticating', {
    condition: (_, context) => context.credentials !== null
  })
  .from('authenticating').to('loggedIn', {
    condition: (_, context) => context.isAuthenticated
  })
  .or('error', {
    condition: (_, context) => context.authError !== null
  });

// Add event handlers with fluent API
authFlow
  .onTransition((from, to) => console.log(`Auth transition: ${from} -> ${to}`))
  .onEnable(() => console.log('Auth flow enabled'))
  .onDisable(() => console.log('Auth flow disabled'));

// Later, disable the entire authentication flow
fluentState.group('authentication').disable();

// Enable it again when needed
fluentState.group('authentication').enable();

// Temporarily disable for 5 minutes
fluentState.group('authentication').disableTemporarily(5 * 60 * 1000);

// Check if the group is currently enabled
const isAuthFlowEnabled = fluentState.group('authentication').isEnabled();

✅ 6. State Manager Performance Optimizations

Dependencies: None

Configuration options for optimizing state manager performance:

interface StateManagerConfig<T> {
  // Batch multiple rapid state updates
  batchUpdates?: boolean;
  batchTimeWindow?: number;
  // Memoize computed values from state
  enableMemoization?: boolean;
  // Custom equality function for state updates
  areEqual?: (prev: T, next: T) => boolean;
  // Performance metrics collection
  metrics?: {
    enabled: boolean;
    // Track update frequency and timing
    measureUpdates?: boolean;
    // Track memory usage of state
    measureMemory?: boolean;
    // Track computation time of state derivations
    measureComputations?: boolean;
    // Callback for metrics reporting
    onMetrics?: (metrics: StateManagerMetrics) => void;
  };
}

interface StateManagerMetrics {
  // Average time between updates
  updateFrequency: number;
  // Time spent processing updates
  updateDuration: number;
  // Number of updates in the current time window
  updateCount: number;
  // Memory usage statistics
  memoryUsage?: {
    stateSize: number;
    memoizedSize: number;
  };
  // Computation timing
  computationDuration?: {
    equality: number;
    memoization: number;
    derivations: number;
  };
}

Benefits:

• Improved performance for rapid updates
• Memory optimization through memoization
• Custom update detection
• Performance monitoring and optimization insights
• Real-time metrics for debugging and profiling

User Story: As a developer building a performance-critical application with FluentState, I want to optimize how state updates are processed and monitored, So that I can minimize performance bottlenecks, reduce unnecessary re-renders, and gain insights into my application's state management behavior.

Acceptance Criteria:

1. Batched Updates

   • Multiple state updates occurring within the configured time window are batched into a single update
   • The batchTimeWindow parameter controls how long to wait before processing batched updates
   • Batching can be enabled/disabled globally via the batchUpdates configuration option
   • Batched updates maintain the same final state as if updates were processed individually

2. Memoization Support

   • When enableMemoization is true, derived values from state are cached and only recalculated when dependencies change
   • Memoization works with both simple and complex state structures
   • Memoized values are properly invalidated when their dependencies change
   • Memory usage is optimized by clearing unused memoized values

3. Custom Equality Checking

   • Developers can provide a custom areEqual function to determine if state has actually changed
   • The custom equality function is used to prevent unnecessary updates when state is structurally equivalent
   • Default equality checking uses a shallow comparison for objects and arrays
   • Custom equality checking works with all state update methods

4. Performance Metrics

   • When metrics.enabled is true, the state manager collects performance data
   • Update frequency, duration, and count are tracked when measureUpdates is true
   • Memory usage statistics are collected when measureMemory is true
   • Computation timing for equality checks, memoization, and derivations is measured when measureComputations is true
   • Metrics are provided to the onMetrics callback for custom reporting or visualization
   • Metrics collection has minimal impact on overall performance

Example Usage:

// Configure performance optimizations
const machine = new FluentState({
  initialState: "idle",
  stateManagerConfig: {
    batchUpdates: true,
    batchTimeWindow: 50, // 50ms batching window
    enableMemoization: true,
    areEqual: (prev, next) => _.isEqual(prev, next), // Deep equality check
    metrics: {
      enabled: true,
      measureUpdates: true,
      measureMemory: process.env.NODE_ENV === 'development',
      measureComputations: process.env.NODE_ENV === 'development',
      onMetrics: (metrics) => {
        console.log('State Manager Metrics:', metrics);
        if (metrics.updateFrequency < 16) { // Less than 60fps
          console.warn('Performance warning: High update frequency detected');
        }
      }
    }
  }
});

✅ 7. Debugging and Development Tools

Dependencies:

• Transition History (for comprehensive debugging capabilities)
• State Manager Performance Optimizations (for performance metrics collection and reporting)
• Transition Groups (for complete state machine visualization)

Comprehensive debugging and development tools:

interface DebugConfig {
  // Log detailed transition information
  logLevel: 'none' | 'error' | 'warn' | 'info' | 'debug';
  // Track performance metrics
  measurePerformance?: boolean;
  // Save transition history
  keepHistory?: boolean;
  historySize?: number;
  // Export state machine configuration
  exportConfig?: () => string;
  // Visualize state machine (requires Transition Groups for complete visualization)
  generateGraph?: {
    format: 'mermaid' | 'dot' | 'svg';
    options?: {
      // Include transition conditions in the graph
      showConditions?: boolean;
      // Show transition groups as clusters
      groupClusters?: boolean;
      // Include state metadata
      showMetadata?: boolean;
      // Highlight current state
      highlightCurrent?: boolean;
      // Show transition history
      showHistory?: boolean;
      // Custom styling
      styles?: {
        groups?: Record<string, string>;
        states?: Record<string, string>;
        transitions?: Record<string, string>;
      };
    };
  };
}

// Example visualization output (Mermaid format):
/*
stateDiagram-v2
  %% Upload Flow Group
  state "Upload Flow" as UploadFlow {
    [*] --> idle
    idle --> uploading: files.length > 0
    uploading --> processing: progress === 100
    processing --> complete: isValid
    processing --> error: !isValid
  }
  
  %% Auth Flow Group
  state "Auth Flow" as AuthFlow {
    [*] --> login
    login --> loading: credentials
    loading --> dashboard: validated
    loading --> error: !validated
  }
*/

Benefits:

• Easier debugging of complex state machines
• Performance monitoring
• Better development experience
• Visual state machine representation with:
  • Grouped states and transitions
  • Transition conditions
  • Current state highlighting
  • Historical transitions
  • Custom styling options

User Story: As a developer building and maintaining complex state machines with FluentState, I want comprehensive debugging and visualization tools, So that I can easily troubleshoot issues, understand state flow, gain performance insights, and communicate state machine architecture to my team.

Acceptance Criteria:

1. Logging and Monitoring

   • ✅ Different log levels ('none', 'error', 'warn', 'info', 'debug') can be configured through the logLevel property
   • ✅ Detailed information about state transitions, conditions, and context changes are logged at appropriate levels
   • ✅ Logs include timestamps, state information, and relevant context data
   • ✅ Performance metrics are collected when measurePerformance is enabled
   • ✅ Performance data includes transition evaluation time, condition execution time, and context update time
   • ✅ Logs can be directed to custom output channels (console, file, custom logger)
   • ✅ Log format is customizable to integrate with existing logging systems

2. History Tracking

   • ✅ Complete transition history is maintained when keepHistory is enabled
   • ✅ History size is configurable through historySize to prevent memory issues
   • ✅ History includes source state, target state, timestamp, context data, and metadata
   • ✅ History can be queried and filtered by state, time range, or metadata
   • ✅ Export functionality for history data in JSON format for external analysis
   • ✅ Clear separation between current state management and history tracking to minimize performance impact

3. Configuration Export

   • ✅ The exportConfig function produces a complete serialized representation of the state machine
   • ✅ Export format includes states, transitions, groups, and configuration settings
   • ✅ Exported configuration can be used to recreate an identical state machine
   • ✅ Configuration export supports redaction of sensitive information
   • ✅ Export function is extensible to support different output formats

4. State Machine Visualization

   • ✅ The generateGraph function creates visual representations of the state machine
   • ✅ Supported output formats include Mermaid, DOT, and SVG
   • ✅ Visualization shows all states, transitions, and their relationships
   • ✅ Transition groups are represented as clusters when groupClusters is enabled
   • ✅ Transition conditions are displayed when showConditions is enabled
   • ✅ Current state is highlighted when highlightCurrent is enabled
   • ✅ Historical transitions can be shown when showHistory is enabled
   • ✅ State metadata is included when showMetadata is enabled
   • ✅ Custom styling can be applied through the styles configuration for groups, states, and transitions
   • ✅ Generated visualizations can be used in documentation, presentations, or development tools

5. Developer Experience

   • ✅ All debugging features have minimal impact on production performance when disabled
   • ✅ Time-travel debugging support through integration with transition history
   • ✅ Warning system for potential issues such as unreachable states or conflicting transitions

Example Usage:

// Configure debugging tools

fluentState.debugConfig(config: DebugConfig);
// or
const fs = new FluentState({
  initialState: "idle",
  debug: {
    logLevel: process.env.NODE_ENV === 'development' ? 'debug' : 'error',
    measurePerformance: true,
    keepHistory: true,
    historySize: 100,
    exportConfig: () => JSON.stringify(machine.config, null, 2),
    generateGraph: {
      format: 'mermaid',
      options: {
        showConditions: true,
        groupClusters: true,
        highlightCurrent: true,
        showHistory: true,
        styles: {
          groups: {
            'authentication': 'fill:#f9f,stroke:#333,stroke-width:2px',
            'upload': 'fill:#bbf,stroke:#333,stroke-width:2px'
          }
        }
      }
    }
  }
});

// Later, generate visualization for documentation
const diagram = fs.debug.generateGraph();
fs.writeFileSync('state-machine.md', diagram);

// Export current configuration
const config = fs.debug.exportConfig();
localStorage.setItem('savedStateMachine', config);

// Analyze transition history
const authFailures = fs.debug.history.filter(entry => 
  entry.from === 'authenticating' && entry.to === 'error'
);
console.log(`Auth failures: ${authFailures.length}`);

Implementation Priority

Given the dependencies, here's the revised implementation order:

1. ✅ Enhanced Auto-transition Configuration (High)

   • Most immediately useful for existing users
   • Builds on current functionality
   • Required by multiple other features

2. ✅ State Manager Performance Optimizations (High)

   • Important for applications with frequent updates
   • Performance improvements benefit all users
   • Required for batch updates

3. ✅ Transition History (Medium)

   • Required for comprehensive debugging tools
   • Foundation for monitoring and analytics

4. ✅ Transition Groups (Medium)

   • Moved up in priority as it's required for complete debugging tools
   • Organizational improvement
   • Required for state machine visualization
   • Requires enhanced auto-transition configuration

5. ✅ Debugging and Development Tools (Medium)

• Critical for adoption and maintenance
• Helps users understand and debug their state machines
• Builds on transition history and groups
• Complete visualization support

6. ✅ Batch Context Updates (Medium)

• Performance optimization for specific use cases
• Requires auto-transition configuration and state manager optimizations

7. ✅ Conditional Auto-transition Evaluation (Low)

• Advanced optimization
• Requires enhanced auto-transition configuration

Compatibility

All proposed features will:

• Maintain backward compatibility
• Be optional/opt-in
• Build upon existing plugin system
• Follow current API patterns

Contributing

We welcome contributions to any of these features. Please:

1. Open an issue to discuss implementation details
2. Follow existing code style and patterns
3. Include tests and documentation
4. Consider backward compatibility