ElixirScope.AI.Predictive.ExecutionPredictor (elixir_scope v0.0.1)
Predicts execution paths, resource usage, and concurrency impacts based on historical execution data and code analysis.
This module implements machine learning models to:
- Predict likely execution paths for function calls
- Estimate resource requirements (memory, CPU, I/O)
- Analyze concurrency bottlenecks and scaling factors
- Identify edge cases and rarely-executed code paths
Summary
Functions
Analyzes concurrency impact for a function signature.
Returns a specification to start this module under a supervisor.
Gets current model statistics and performance metrics.
Performs batch predictions for multiple contexts.
Predicts the execution path for a given function call.
Predicts resource usage for a given execution context.
Starts the ExecutionPredictor GenServer.
Trains the prediction models with historical data.
Functions
Analyzes concurrency impact for a function signature.
Examples
iex> ExecutionPredictor.analyze_concurrency_impact({:handle_call, 3})
{:ok, %{
bottleneck_risk: 0.7,
recommended_pool_size: 10,
scaling_factor: 0.85,
contention_points: [:database_access, :file_io]
}}
Returns a specification to start this module under a supervisor.
See Supervisor
.
Gets current model statistics and performance metrics.
Performs batch predictions for multiple contexts.
Predicts the execution path for a given function call.
Returns a prediction with confidence scores and alternative paths.
Examples
iex> ExecutionPredictor.predict_path(MyModule, :my_function, [arg1, arg2])
{:ok, %{
predicted_path: [:entry, :condition_check, :main_logic, :exit],
confidence: 0.85,
alternatives: [
%{path: [:entry, :error_handling, :exit], probability: 0.15}
],
edge_cases: [
%{type: :nil_input, probability: 0.02}
]
}}
Predicts resource usage for a given execution context.
Examples
iex> context = %{function: :process_data, input_size: 1000}
iex> ExecutionPredictor.predict_resources(context)
{:ok, %{
memory: 2048, # KB
cpu: 15.5, # percentage
io: 100, # operations
execution_time: 250 # milliseconds
}}
Starts the ExecutionPredictor GenServer.
Trains the prediction models with historical data.