-module(reflection_mechanism). -behaviour(gen_statem). -export([start_link/0, start_link/1]). -export([start_introspection/1, analyze_system/2, adapt_behavior/2, get_reflection_report/1, enable_continuous_reflection/1, disable_continuous_reflection/1, trigger_deep_analysis/1]). -export([init/1, callback_mode/0, terminate/3, code_change/4]). -export([idle/3, introspection/3, system_analysis/3, pattern_recognition/3, adaptation_planning/3, behavior_modification/3, validation/3, continuous_monitoring/3, deep_analysis/3, reporting/3]). -record(reflection_context, { system_state :: #{atom() => term()}, process_registry :: #{pid() => #{atom() => term()}}, message_patterns :: [term()], performance_metrics :: #{atom() => number()}, error_history :: [term()], adaptation_history :: [term()], behavioral_patterns :: #{atom() => term()}, anomalies :: [term()], optimization_opportunities :: [term()], timestamp :: erlang:timestamp() }). -record(reflection_data, { session_id :: term(), current_context = #reflection_context{} :: #reflection_context{}, previous_contexts = [] :: [#reflection_context{}], analysis_depth = shallow :: shallow | deep | comprehensive, introspection_scope = local :: local | cluster | global, adaptation_strategy = conservative :: conservative | aggressive | experimental, continuous_mode = false :: boolean(), monitoring_interval = 5000 :: pos_integer(), pattern_library = #{} :: #{atom() => term()}, adaptation_rules = [] :: [term()], learning_model = #{} :: #{atom() => term()}, reflection_statistics = #{} :: #{atom() => term()}, anomaly_detector = #{} :: #{atom() => term()}, performance_baselines = #{} :: #{atom() => number()}, meta_reflection_data = #{} :: #{atom() => term()}, observers = [] :: [pid()], timeout = infinity :: timeout(), start_time :: erlang:timestamp() }). start_link() -> gen_statem:start_link(?MODULE, [], []). start_link(Options) -> gen_statem:start_link(?MODULE, Options, []). start_introspection(Pid) -> gen_statem:call(Pid, start_introspection). analyze_system(Pid, Scope) -> gen_statem:call(Pid, {analyze_system, Scope}). adapt_behavior(Pid, Strategy) -> gen_statem:call(Pid, {adapt_behavior, Strategy}). get_reflection_report(Pid) -> gen_statem:call(Pid, get_reflection_report). enable_continuous_reflection(Pid) -> gen_statem:call(Pid, enable_continuous_reflection). disable_continuous_reflection(Pid) -> gen_statem:call(Pid, disable_continuous_reflection). trigger_deep_analysis(Pid) -> gen_statem:call(Pid, trigger_deep_analysis). init(Options) -> Data = #reflection_data{ session_id = make_ref(), analysis_depth = proplists:get_value(depth, Options, shallow), introspection_scope = proplists:get_value(scope, Options, local), adaptation_strategy = proplists:get_value(strategy, Options, conservative), monitoring_interval = proplists:get_value(interval, Options, 5000), timeout = proplists:get_value(timeout, Options, infinity), start_time = erlang:timestamp(), pattern_library = initialize_pattern_library(), adaptation_rules = initialize_adaptation_rules(), learning_model = initialize_learning_model(), anomaly_detector = initialize_anomaly_detector(), performance_baselines = establish_performance_baselines(), reflection_statistics = #{ introspection_cycles => 0, adaptations_applied => 0, anomalies_detected => 0, patterns_learned => 0, optimizations_found => 0 } }, {ok, idle, Data}. callback_mode() -> [state_functions, state_enter]. idle(enter, _OldState, Data) -> case Data#reflection_data.continuous_mode of true -> {keep_state, Data, [{state_timeout, Data#reflection_data.monitoring_interval, continuous_cycle}]}; false -> {keep_state, Data} end; idle({call, From}, start_introspection, Data) -> NewData = initiate_introspection_session(Data), {next_state, introspection, NewData, [{reply, From, ok}]}; idle({call, From}, {analyze_system, Scope}, Data) -> UpdatedData = Data#reflection_data{introspection_scope = Scope}, {next_state, system_analysis, UpdatedData, [{reply, From, ok}]}; idle({call, From}, enable_continuous_reflection, Data) -> ContinuousData = Data#reflection_data{continuous_mode = true}, {keep_state, ContinuousData, [{reply, From, ok}, {state_timeout, Data#reflection_data.monitoring_interval, continuous_cycle}]}; idle({call, From}, disable_continuous_reflection, Data) -> {keep_state, Data#reflection_data{continuous_mode = false}, [{reply, From, ok}]}; idle({call, From}, trigger_deep_analysis, Data) -> DeepData = Data#reflection_data{analysis_depth = comprehensive}, {next_state, deep_analysis, DeepData, [{reply, From, ok}]}; idle(state_timeout, continuous_cycle, Data) -> {next_state, introspection, initiate_introspection_session(Data)}; idle(EventType, Event, Data) -> handle_common_events(EventType, Event, Data). introspection(enter, _OldState, Data) -> IntrospectionData = perform_system_introspection(Data), UpdatedStats = increment_stat(introspection_cycles, Data#reflection_data.reflection_statistics), {next_state, system_analysis, IntrospectionData#reflection_data{reflection_statistics = UpdatedStats}}; introspection(EventType, Event, Data) -> handle_common_events(EventType, Event, Data). system_analysis(enter, _OldState, Data) -> AnalysisData = conduct_comprehensive_analysis(Data), {next_state, pattern_recognition, AnalysisData}; system_analysis(EventType, Event, Data) -> handle_common_events(EventType, Event, Data). pattern_recognition(enter, _OldState, Data) -> PatternData = recognize_behavioral_patterns(Data), case detect_anomalies(PatternData) of {anomalies_found, Anomalies} -> AnomalyData = record_anomalies(Anomalies, PatternData), UpdatedStats = increment_stat(anomalies_detected, AnomalyData#reflection_data.reflection_statistics), {next_state, adaptation_planning, AnomalyData#reflection_data{reflection_statistics = UpdatedStats}}; no_anomalies -> {next_state, continuous_monitoring, PatternData} end; pattern_recognition(EventType, Event, Data) -> handle_common_events(EventType, Event, Data). adaptation_planning(enter, _OldState, Data) -> PlanData = formulate_adaptation_plan(Data), case should_apply_adaptations(PlanData) of true -> {next_state, behavior_modification, PlanData}; false -> {next_state, validation, PlanData} end; adaptation_planning(EventType, Event, Data) -> handle_common_events(EventType, Event, Data). behavior_modification(enter, _OldState, Data) -> ModificationData = apply_behavioral_adaptations(Data), UpdatedStats = increment_stat(adaptations_applied, ModificationData#reflection_data.reflection_statistics), {next_state, validation, ModificationData#reflection_data{reflection_statistics = UpdatedStats}}; behavior_modification(EventType, Event, Data) -> handle_common_events(EventType, Event, Data). validation(enter, _OldState, Data) -> ValidationData = validate_adaptations(Data), case ValidationData#reflection_data.continuous_mode of true -> {next_state, continuous_monitoring, ValidationData}; false -> {next_state, reporting, ValidationData} end; validation(EventType, Event, Data) -> handle_common_events(EventType, Event, Data). continuous_monitoring(enter, _OldState, Data) -> case Data#reflection_data.continuous_mode of true -> {keep_state, Data, [{state_timeout, Data#reflection_data.monitoring_interval, monitor_cycle}]}; false -> {next_state, reporting, Data} end; continuous_monitoring(state_timeout, monitor_cycle, Data) -> {next_state, introspection, initiate_introspection_session(Data)}; continuous_monitoring({call, From}, disable_continuous_reflection, Data) -> {next_state, reporting, Data#reflection_data{continuous_mode = false}, [{reply, From, ok}]}; continuous_monitoring(EventType, Event, Data) -> handle_common_events(EventType, Event, Data). deep_analysis(enter, _OldState, Data) -> DeepAnalysisData = perform_deep_system_analysis(Data), OptimizationData = identify_optimization_opportunities(DeepAnalysisData), LearningData = perform_meta_learning(OptimizationData), {next_state, reporting, LearningData}; deep_analysis(EventType, Event, Data) -> handle_common_events(EventType, Event, Data). reporting(enter, _OldState, Data) -> ReportData = generate_reflection_report(Data), notify_observers(ReportData), case Data#reflection_data.continuous_mode of true -> {next_state, idle, ReportData}; false -> {keep_state, ReportData} end; reporting({call, From}, get_reflection_report, Data) -> Report = compile_comprehensive_report(Data), {keep_state, Data, [{reply, From, {ok, Report}}]}; reporting(EventType, Event, Data) -> handle_common_events(EventType, Event, Data). terminate(_Reason, _State, _Data) -> ok. code_change(_Vsn, State, Data, _Extra) -> {ok, State, Data}. initiate_introspection_session(Data) -> Context = capture_current_context(), PreviousContexts = [Data#reflection_data.current_context | Data#reflection_data.previous_contexts], Data#reflection_data{ session_id = make_ref(), current_context = Context, previous_contexts = lists:sublist(PreviousContexts, 10), start_time = erlang:timestamp() }. perform_system_introspection(Data) -> SystemState = analyze_current_system_state(), ProcessRegistry = inspect_process_registry(Data#reflection_data.introspection_scope), MessagePatterns = analyze_message_patterns(), PerformanceMetrics = collect_performance_metrics(), ErrorHistory = gather_error_history(), UpdatedContext = Data#reflection_data.current_context#reflection_context{ system_state = SystemState, process_registry = ProcessRegistry, message_patterns = MessagePatterns, performance_metrics = PerformanceMetrics, error_history = ErrorHistory, timestamp = erlang:timestamp() }, Data#reflection_data{current_context = UpdatedContext}. conduct_comprehensive_analysis(Data) -> Context = Data#reflection_data.current_context, BehavioralAnalysis = analyze_behavioral_trends(Context, Data#reflection_data.previous_contexts), PerformanceAnalysis = analyze_performance_trends(Context, Data#reflection_data.performance_baselines), _SystemHealthAnalysis = assess_system_health(Context), _ResourceUtilizationAnalysis = analyze_resource_utilization(Context), EnhancedContext = Context#reflection_context{ behavioral_patterns = BehavioralAnalysis, performance_metrics = maps:merge(Context#reflection_context.performance_metrics, PerformanceAnalysis) }, Data#reflection_data{current_context = EnhancedContext}. recognize_behavioral_patterns(Data) -> Context = Data#reflection_data.current_context, PatternLibrary = Data#reflection_data.pattern_library, _RecognizedPatterns = apply_pattern_recognition(Context, PatternLibrary), NewPatterns = discover_new_patterns(Context, Data#reflection_data.previous_contexts), UpdatedPatternLibrary = update_pattern_library(PatternLibrary, NewPatterns), UpdatedStats = increment_stat(patterns_learned, Data#reflection_data.reflection_statistics), Data#reflection_data{ pattern_library = UpdatedPatternLibrary, reflection_statistics = UpdatedStats }. detect_anomalies(Data) -> Context = Data#reflection_data.current_context, AnomalyDetector = Data#reflection_data.anomaly_detector, Baselines = Data#reflection_data.performance_baselines, PerformanceAnomalies = detect_performance_anomalies(Context#reflection_context.performance_metrics, Baselines), BehavioralAnomalies = detect_behavioral_anomalies(Context#reflection_context.behavioral_patterns, AnomalyDetector), SystemAnomalies = detect_system_anomalies(Context#reflection_context.system_state), AllAnomalies = PerformanceAnomalies ++ BehavioralAnomalies ++ SystemAnomalies, case AllAnomalies of [] -> no_anomalies; Anomalies -> {anomalies_found, Anomalies} end. formulate_adaptation_plan(Data) -> Context = Data#reflection_data.current_context, Strategy = Data#reflection_data.adaptation_strategy, Rules = Data#reflection_data.adaptation_rules, AdaptationPlan = generate_adaptation_strategies(Context#reflection_context.anomalies, Strategy, Rules), RiskAssessment = assess_adaptation_risks(AdaptationPlan), PrioritizedPlan = prioritize_adaptations(AdaptationPlan, RiskAssessment), Data#reflection_data{adaptation_rules = [PrioritizedPlan | Rules]}. apply_behavioral_adaptations(Data) -> AdaptationPlan = hd(Data#reflection_data.adaptation_rules), AppliedAdaptations = execute_adaptations(AdaptationPlan), AdaptationHistory = [AppliedAdaptations | Data#reflection_data.current_context#reflection_context.adaptation_history], UpdatedContext = Data#reflection_data.current_context#reflection_context{ adaptation_history = AdaptationHistory }, Data#reflection_data{current_context = UpdatedContext}. validate_adaptations(Data) -> Context = Data#reflection_data.current_context, RecentAdaptations = hd(Context#reflection_context.adaptation_history), ValidationResults = validate_adaptation_effectiveness(RecentAdaptations, Context), UpdatedLearningModel = update_learning_model(ValidationResults, Data#reflection_data.learning_model), Data#reflection_data{learning_model = UpdatedLearningModel}. perform_deep_system_analysis(Data) -> Context = Data#reflection_data.current_context, ArchitecturalAnalysis = analyze_system_architecture(Context), CommunicationAnalysis = analyze_inter_process_communication(Context), ResourceAnalysis = perform_deep_resource_analysis(Context), SecurityAnalysis = analyze_security_posture(Context), ComprehensiveContext = Context#reflection_context{ system_state = maps:merge(Context#reflection_context.system_state, #{ architectural_analysis => ArchitecturalAnalysis, communication_analysis => CommunicationAnalysis, resource_analysis => ResourceAnalysis, security_analysis => SecurityAnalysis }) }, Data#reflection_data{current_context = ComprehensiveContext}. identify_optimization_opportunities(Data) -> Context = Data#reflection_data.current_context, PerformanceOptimizations = identify_performance_optimizations(Context), ResourceOptimizations = identify_resource_optimizations(Context), ArchitecturalOptimizations = identify_architectural_optimizations(Context), AllOptimizations = PerformanceOptimizations ++ ResourceOptimizations ++ ArchitecturalOptimizations, UpdatedStats = increment_stat(optimizations_found, Data#reflection_data.reflection_statistics), UpdatedContext = Context#reflection_context{ optimization_opportunities = AllOptimizations }, Data#reflection_data{ current_context = UpdatedContext, reflection_statistics = UpdatedStats }. perform_meta_learning(Data) -> ReflectionHistory = Data#reflection_data.previous_contexts, LearningModel = Data#reflection_data.learning_model, MetaPatterns = extract_meta_patterns(ReflectionHistory), UpdatedModel = incorporate_meta_learning(MetaPatterns, LearningModel), MetaReflectionData = generate_meta_reflection_insights(UpdatedModel), Data#reflection_data{ learning_model = UpdatedModel, meta_reflection_data = MetaReflectionData }. generate_reflection_report(Data) -> Report = compile_comprehensive_report(Data), Data#reflection_data{ meta_reflection_data = maps:put(latest_report, Report, Data#reflection_data.meta_reflection_data) }. should_apply_adaptations(Data) -> Strategy = Data#reflection_data.adaptation_strategy, Anomalies = Data#reflection_data.current_context#reflection_context.anomalies, case {Strategy, length(Anomalies)} of {conservative, Count} when Count > 3 -> true; {aggressive, Count} when Count > 0 -> true; {experimental, _} -> true; _ -> false end. record_anomalies(Anomalies, Data) -> Context = Data#reflection_data.current_context, UpdatedContext = Context#reflection_context{anomalies = Anomalies}, Data#reflection_data{current_context = UpdatedContext}. notify_observers(Data) -> Report = compile_comprehensive_report(Data), lists:foreach(fun(Observer) -> Observer ! {reflection_report, Data#reflection_data.session_id, Report} end, Data#reflection_data.observers). compile_comprehensive_report(Data) -> #{ session_id => Data#reflection_data.session_id, timestamp => erlang:timestamp(), current_context => Data#reflection_data.current_context, analysis_depth => Data#reflection_data.analysis_depth, introspection_scope => Data#reflection_data.introspection_scope, adaptation_strategy => Data#reflection_data.adaptation_strategy, reflection_statistics => Data#reflection_data.reflection_statistics, meta_reflection_data => Data#reflection_data.meta_reflection_data, continuous_mode => Data#reflection_data.continuous_mode }. capture_current_context() -> #reflection_context{ system_state = #{}, process_registry = #{}, message_patterns = [], performance_metrics = #{}, error_history = [], adaptation_history = [], behavioral_patterns = #{}, anomalies = [], optimization_opportunities = [], timestamp = erlang:timestamp() }. increment_stat(Stat, Stats) -> maps:update_with(Stat, fun(X) -> X + 1 end, 1, Stats). handle_common_events({call, From}, get_reflection_report, Data) -> Report = compile_comprehensive_report(Data), {keep_state, Data, [{reply, From, {ok, Report}}]}; handle_common_events({call, From}, {adapt_behavior, Strategy}, Data) -> {keep_state, Data#reflection_data{adaptation_strategy = Strategy}, [{reply, From, ok}]}; handle_common_events(_EventType, _Event, _Data) -> {keep_state_and_data, [postpone]}. analyze_current_system_state() -> #{}. inspect_process_registry(_Scope) -> #{}. analyze_message_patterns() -> []. collect_performance_metrics() -> #{}. gather_error_history() -> []. analyze_behavioral_trends(_Context, _Previous) -> #{}. analyze_performance_trends(_Context, _Baselines) -> #{}. assess_system_health(_Context) -> ok. analyze_resource_utilization(_Context) -> #{}. apply_pattern_recognition(_Context, _Library) -> #{}. discover_new_patterns(_Context, _Previous) -> []. update_pattern_library(Library, _NewPatterns) -> Library. detect_performance_anomalies(_Metrics, _Baselines) -> []. detect_behavioral_anomalies(_Patterns, _Detector) -> []. detect_system_anomalies(_State) -> []. generate_adaptation_strategies(_Anomalies, _Strategy, _Rules) -> []. assess_adaptation_risks(_Plan) -> low. prioritize_adaptations(Plan, _Risk) -> Plan. execute_adaptations(_Plan) -> []. validate_adaptation_effectiveness(_Adaptations, _Context) -> #{}. update_learning_model(_Results, Model) -> Model. analyze_system_architecture(_Context) -> #{}. analyze_inter_process_communication(_Context) -> #{}. perform_deep_resource_analysis(_Context) -> #{}. analyze_security_posture(_Context) -> #{}. identify_performance_optimizations(_Context) -> []. identify_resource_optimizations(_Context) -> []. identify_architectural_optimizations(_Context) -> []. extract_meta_patterns(_History) -> []. incorporate_meta_learning(_Patterns, Model) -> Model. generate_meta_reflection_insights(_Model) -> #{}. initialize_pattern_library() -> #{}. initialize_adaptation_rules() -> []. initialize_learning_model() -> #{}. initialize_anomaly_detector() -> #{}. establish_performance_baselines() -> #{}.