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impl UnifiedEngine {
/// Creates a new unified refactoring engine with the specified configuration.
///
/// Initializes the engine with AST analysis capabilities, caching, and a configurable
/// execution mode (Server, Interactive, or Batch). The engine uses a state machine
/// to coordinate refactoring operations across the target files.
///
/// # Parameters
///
/// * `ast_engine` - Shared AST analysis engine for parsing and analysis
/// * `cache` - Unified cache manager for performance optimization
/// * `mode` - Execution mode (Server/Interactive/Batch) with mode-specific settings
/// * `config` - Refactoring configuration (quality thresholds, operation types, etc.)
/// * `targets` - Vector of file paths to analyze and potentially refactor
///
/// # Examples
///
/// ```no_run
/// use pmat::services::refactor_engine::{
/// UnifiedEngine, EngineMode, ExplainLevel
/// };
/// use pmat::services::unified_ast_engine::UnifiedAstEngine;
/// use pmat::services::cache::unified_manager::UnifiedCacheManager;
/// use pmat::services::cache::unified::UnifiedCacheConfig;
/// use pmat::models::refactor::RefactorConfig;
/// use std::sync::Arc;
/// use std::path::PathBuf;
/// use std::time::Duration;
///
/// let ast_engine = Arc::new(UnifiedAstEngine::new());
/// let cache = Arc::new(UnifiedCacheManager::new(UnifiedCacheConfig::default()).expect("internal error"));
/// let config = RefactorConfig::default();
/// let targets = vec![PathBuf::from("src/main.rs")];
///
/// // Server mode for high-throughput processing
/// let mode = EngineMode::Server {
/// emit_buffer: Arc::new(tokio::sync::RwLock::new(
/// pmat::services::refactor_engine::RingBuffer::new(1000)
/// )),
/// latency_target: Duration::from_millis(100),
/// };
///
/// let engine = UnifiedEngine::new(
/// ast_engine,
/// cache,
/// mode,
/// config,
/// targets
/// );
///
/// // Engine is ready for analysis and refactoring
/// ```
#[must_use]
pub fn new(
ast_engine: Arc<UnifiedAstEngine>,
cache: Arc<UnifiedCacheManager>,
mode: EngineMode,
config: RefactorConfig,
targets: Vec<PathBuf>,
) -> Self {
// Skip analyzer pool setup for now - this is a compatibility stub
let state_machine = Arc::new(RwLock::new(RefactorStateMachine::new(targets, config)));
Self {
ast_engine,
cache,
analyzers: AnalyzerPool::new(), // Dummy analyzer pool for compatibility
mode,
state_machine,
metrics: Arc::new(EngineMetrics::default()),
}
}
/// Executes the refactoring engine according to its configured mode.
///
/// This is the main entry point that starts the refactoring process. The behavior
/// depends on the engine mode:
/// - **Server**: Continuous processing with latency targets and buffered output
/// - **Interactive**: Step-by-step processing with user confirmation
/// - **Batch**: Automated processing with checkpointing and parallelization
///
/// # Error Handling
///
/// The engine implements comprehensive error recovery:
/// - Parse errors -> skip file and continue
/// - I/O errors -> retry with exponential backoff
/// - State machine errors -> rollback to last checkpoint
///
/// # Examples
///
/// ```no_run
/// use pmat::services::refactor_engine::{
/// UnifiedEngine, EngineMode
/// };
/// use pmat::services::unified_ast_engine::UnifiedAstEngine;
/// use pmat::services::cache::unified_manager::UnifiedCacheManager;
/// use pmat::services::cache::unified::UnifiedCacheConfig;
/// use pmat::models::refactor::RefactorConfig;
/// use std::sync::Arc;
/// use std::path::PathBuf;
/// use std::time::Duration;
///
/// # tokio_test::block_on(async {
/// let ast_engine = Arc::new(UnifiedAstEngine::new());
/// let cache = Arc::new(UnifiedCacheManager::new(UnifiedCacheConfig::default()).expect("internal error"));
/// let config = RefactorConfig::default();
/// let targets = vec![PathBuf::from("src/example.rs")];
///
/// let mode = EngineMode::Batch {
/// checkpoint_dir: PathBuf::from(".refactor_state"),
/// resume: false,
/// parallel_workers: 4,
/// };
///
/// let mut engine = UnifiedEngine::new(
/// ast_engine,
/// cache,
/// mode,
/// config,
/// targets
/// );
///
/// // Run the refactoring process
/// let result = engine.run().await;
///
/// match result {
/// Ok(summary) => {
/// println!("Refactoring completed: {} operations", summary.refactors_applied);
/// }
/// Err(e) => {
/// eprintln!("Refactoring failed: {}", e);
/// }
/// }
/// # });
/// ```
pub async fn run(&mut self) -> Result<Summary, EngineError> {
match &self.mode {
EngineMode::Server { .. } => self.run_server().await,
EngineMode::Interactive { .. } => self.run_interactive().await,
EngineMode::Batch { .. } => self.run_batch().await,
}
}
pub async fn save_checkpoint(&self) -> Result<(), EngineError> {
if let EngineMode::Interactive {
checkpoint_file, ..
} = &self.mode
{
self.save_checkpoint_to(checkpoint_file.parent().unwrap_or(Path::new(".")))
.await
} else if let EngineMode::Batch { checkpoint_dir, .. } = &self.mode {
self.save_checkpoint_to(checkpoint_dir).await
} else {
Ok(())
}
}
pub(crate) async fn save_checkpoint_to(&self, dir: &Path) -> Result<(), EngineError> {
let state_machine = self.state_machine.read().await;
let checkpoint_data = serde_json::to_string_pretty(&*state_machine)?;
let checkpoint_path = dir.join("checkpoint.json");
tokio::fs::write(&checkpoint_path, checkpoint_data).await?;
Ok(())
}
pub(crate) async fn load_checkpoint(&mut self, dir: &Path) -> Result<(), EngineError> {
let checkpoint_path = dir.join("checkpoint.json");
if checkpoint_path.exists() {
let checkpoint_data = tokio::fs::read_to_string(&checkpoint_path).await?;
let state_machine: RefactorStateMachine = serde_json::from_str(&checkpoint_data)?;
*self.state_machine.write().await = state_machine;
}
Ok(())
}
pub(crate) async fn analyze_incremental(
&self,
path: &Path,
) -> Result<ComplexityInfo, EngineError> {
let extension = path.extension().and_then(|ext| ext.to_str()).unwrap_or("");
let (cyclomatic, cognitive, satd_count) = match extension {
"rs" => {
// For Rust files, read and analyze if it's a reasonable size
if let Ok(content) = tokio::fs::read_to_string(path).await {
if content.len() < 50000 {
// Only analyze files under 50KB
// Simple heuristic based on content patterns
let if_count = content.matches("if ").count();
let for_count = content.matches("for ").count();
let while_count = content.matches("while ").count();
let match_count = content.matches("match ").count();
let function_count = content.matches("fn ").count();
let estimated_cyclomatic =
(if_count + for_count + while_count + match_count + function_count)
.min(100) as u16;
let estimated_cognitive = (f32::from(estimated_cyclomatic) * 1.3) as u16;
// Count SATD markers
let todo_count = content.matches("TODO").count();
let fixme_count = content.matches("FIXME").count();
let hack_count = content.matches("HACK").count();
let satd = (todo_count + fixme_count + hack_count) as u32;
(estimated_cyclomatic, estimated_cognitive, satd)
} else {
(20, 25, 0) // Large files are likely complex but we didn't read them
}
} else {
(1, 1, 0) // Unreadable files
}
}
"ts" | "tsx" | "js" | "jsx" => {
// For JS/TS files, also try to read and count SATD
if let Ok(content) = tokio::fs::read_to_string(path).await {
let todo_count = content.matches("TODO").count();
let fixme_count = content.matches("FIXME").count();
let hack_count = content.matches("HACK").count();
let satd = (todo_count + fixme_count + hack_count) as u32;
(8, 12, satd)
} else {
(8, 12, 0)
}
}
"py" => {
// For Python files
if let Ok(content) = tokio::fs::read_to_string(path).await {
let todo_count = content.matches("TODO").count();
let fixme_count = content.matches("FIXME").count();
let hack_count = content.matches("HACK").count();
let satd = (todo_count + fixme_count + hack_count) as u32;
(6, 9, satd)
} else {
(6, 9, 0)
}
}
_ => (3, 4, 0), // Other files
};
Ok(ComplexityInfo {
complexity: [cyclomatic, cognitive],
tdg: (f32::from(cyclomatic) / 10.0).min(3.0),
satd: satd_count,
})
}
pub(crate) fn should_emit(&self, metrics: &ComplexityInfo) -> bool {
// Emit if complexity exceeds thresholds
metrics.complexity[0] > 15 || // Cyclomatic > 15
metrics.complexity[1] > 20 || // Cognitive > 20
metrics.tdg > 2.0 // TDG > 2.0
}
pub(crate) fn create_payload(
&self,
_path: &Path,
metrics: ComplexityInfo,
) -> DefectPayload {
DefectPayload {
file_hash: 0,
tdg_score: metrics.tdg,
complexity: (metrics.complexity[0], metrics.complexity[1]),
dead_symbols: 0,
timestamp: std::time::SystemTime::now()
.duration_since(std::time::UNIX_EPOCH)
.expect("internal error")
.as_secs(),
severity_flags: 0,
refactor_available: true,
refactor_type: RefactorType::ExtractFunction,
estimated_improvement: 0.3,
_padding: [0; 2],
}
}
}