public NaiveCountermeasureSelectionOptimizerWithUncertainty(KAOSModel model, double threshold)
{
_model = model;
stats = new OptimizationStatistics();
integrator = new SoftResolutionIntegrator(model);
this.threshold = threshold;
}
private double GetScore(IEnumerable <Goal> goals, IPropagator propagator, HashSet <string> selection, out IEnumerable <string> rootsSatisfied)
{
var r = _model.Resolutions().Where(x => selection.Contains(x.ResolvingGoalIdentifier));
var rootGoalsSatisfied = new HashSet <string> ();
integrator = new SoftResolutionIntegrator(_model);
Console.WriteLine("---- Computing score for " + string.Join(",", selection) + ".");
// Integrate the selection
foreach (var resolution in r)
{
Console.WriteLine("Integrate " + resolution.ResolvingGoalIdentifier);
integrator.Integrate(resolution);
}
var p2 = new BDDBasedPropagator(_model);
//var all_goals_satisfied = true;
var avg_sat_rate = 0.0;
foreach (var goal in goals)
{
var satRate = ((DoubleSatisfactionRate)p2.GetESR(goal));
avg_sat_rate += satRate.SatisfactionRate;
if (satRate.SatisfactionRate >= goal.RDS)
{
rootGoalsSatisfied.Add(goal.Identifier);
}
Console.WriteLine("Cost " + selection.Count);
Console.WriteLine("Selected cm: " + string.Join(",", selection));
Console.WriteLine($"{goal.Identifier} : {satRate.SatisfactionRate} >= {goal.RDS}.");
}
//var all_goals_satisfied = (satRate.SatisfactionRate > goal.RDS);
var cost = selection.Count();
foreach (var resolution in r)
{
integrator.Remove(resolution);
}
//if (!all_goals_satisfied)
//{
// Console.WriteLine("---- not all goal satisfied, returning score = 0");
// return 0;
//}
rootsSatisfied = rootGoalsSatisfied;
//if (satRate > goal.RDS) {
Console.WriteLine("---- returning score = " + (avg_sat_rate / goals.Count()));
return(avg_sat_rate / goals.Count());
//} else {
// return 0;
//}
}
public static void Main(string[] args)
{
Console.WriteLine("*** This is ModelChecker from KAOSTools. ***");
Console.WriteLine("*** For more information on KAOSTools see <https://github.com/ancailliau/KAOSTools> ***");
Console.WriteLine("*** Please report bugs to <https://github.com/ancailliau/KAOSTools/issues> ***");
Console.WriteLine();
Console.WriteLine("*** Copyright (c) 2017, Université catholique de Louvain ***");
Console.WriteLine("");
Init(args);
Console.WriteLine("Goals: " + model.Goals().Count());
Console.WriteLine("Root goals: " + model.RootGoals().Count());
Console.WriteLine("Leaf goals: " + model.LeafGoals().Count());
Console.WriteLine("Goal refinements: " + model.GoalRefinements().Count());
Console.WriteLine();
Console.WriteLine("Obstacles: " + model.Obstacles().Count());
Console.WriteLine("Root obstacles: " + model.RootObstacles().Count());
Console.WriteLine("Leaf obstacles: " + model.LeafObstacles().Count());
Console.WriteLine("Obstacle refinements: " + model.ObstacleRefinements().Count());
Console.WriteLine();
Console.WriteLine("Resolutions: " + model.Resolutions().Count());
Console.WriteLine();
Console.WriteLine("Contexts: " + model.Contexts().Count());
var integrator = new SoftResolutionIntegrator(model);
foreach (var resolution in model.Resolutions())
{
integrator.Integrate(resolution);
}
Console.WriteLine();
Console.WriteLine("Generated goal exceptions: " + model.Exceptions().Count());
Console.WriteLine(" (distributed over " + model.Exceptions().Select(x => x.AnchorGoalIdentifier).Distinct().Count() + " goals)");
Console.WriteLine("Generated provided assumption: " + model.ObstacleAssumptions().Count());
Console.WriteLine(" (distributed over " + model.ObstacleAssumptions().Select(x => x.AnchorGoalIdentifier).Distinct().Count() + " goals)");
}
public CECountermeasureSelectionOptimizer(KAOSModel model)
{
_model = model;
stats = new OptimizationStatistics();
integrator = new SoftResolutionIntegrator(model);
}
public static void Main(string [] args)
{
Console.WriteLine("*** This is CMIntegrator from KAOSTools. ***");
Console.WriteLine("*** For more information on KAOSTools see <https://github.com/ancailliau/KAOSTools> ***");
Console.WriteLine("*** Please report bugs to <https://github.com/ancailliau/KAOSTools/issues> ***");
Console.WriteLine();
Console.WriteLine("*** Copyright (c) 2017, Université catholique de Louvain ***");
Console.WriteLine("");
Init(args);
bool stop = false;
while (!stop)
{
try {
Console.Write("> ");
var input = Console.ReadLine().Trim();
if (input.Equals("quit") | input.Equals("exit"))
{
stop = true;
continue;
}
bool success = false;
Regex regex = new Regex(@"resolve ([a-zA-Z][a-zA-Z0-9_-]*)");
Match match = regex.Match(input);
if (match.Success)
{
success = true;
var o_identifier = match.Groups [1].Value;
if (o_identifier.Equals("all"))
{
var integrator = new SoftResolutionIntegrator(model);
foreach (var resolution in model.Resolutions())
{
integrator.Integrate(resolution);
}
continue;
}
Obstacle o;
if ((o = model.Obstacle(o_identifier)) != null)
{
var resolutions = o.Resolutions().ToArray();
for (int i = 0; i < resolutions.Length; i++)
{
Console.WriteLine($"[{i}] " + resolutions [i].ResolvingGoal().FriendlyName);
}
Console.Write("Select the countermeasure goal to integrate: ");
int index = -1;
do
{
var input_index = Console.ReadLine();
if (int.TryParse(input_index, out index))
{
if (index < resolutions.Length)
{
var integrator = new SoftResolutionIntegrator(model);
integrator.Integrate(resolutions [index]);
}
else
{
index = -1;
}
}
} while (index < 0);
continue;
}
else
{
Console.WriteLine($"Obstacle '{o_identifier}' not found");
}
}
regex = new Regex(@"export ([a-zA-Z0-9_\.-]+)");
match = regex.Match(input);
if (match.Success)
{
success = true;
if (File.Exists(match.Groups [1].Value))
{
Console.Write($"Do you want to overwrite '{match.Groups [1].Value}' (yes/no)? ");
var input_resp = Console.ReadLine().Trim();
if (input_resp.Equals("yes"))
{
File.Delete(match.Groups [1].Value);
}
else
{
continue;
}
}
var e = new KAOSFileExporter(model);
File.WriteAllText(match.Groups [1].Value, e.Export());
Console.WriteLine("Model exported to " + match.Groups [1].Value);
continue;
}
regex = new Regex(@"export_diagram ([a-zA-Z0-9_\.-]+)");
match = regex.Match(input);
if (match.Success)
{
success = true;
if (File.Exists(match.Groups [1].Value))
{
Console.Write($"Do you want to overwrite '{match.Groups [1].Value}' (yes/no)? ");
var input_resp = Console.ReadLine().Trim();
if (input_resp.Equals("yes"))
{
File.Delete(match.Groups [1].Value);
}
else
{
continue;
}
}
Document document = OmnigraffleMainClass.ExportModel(model);
OmniGraffleGenerator.Export(document, match.Groups [1].Value);
Console.WriteLine("Model exported to " + match.Groups [1].Value);
continue;
}
if (!success)
{
Console.WriteLine("Command not recognized.");
}
} catch (Exception e) {
PrintError(e.Message);
Console.Write("Print more? (yes/no)");
var input_resp = Console.ReadLine().Trim();
if (!input_resp.Equals("yes"))
{
continue;
}
else
{
PrintError("An error occured during the computation. (" + e.Message + ").\n"
+ "Please report this error to <https://github.com/ancailliau/KAOSTools/issues>.\n"
+ "----------------------------\n"
+ e.StackTrace
+ "\n----------------------------\n");
}
}
}
}
public static void Main(string[] args)
{
Console.WriteLine("*** This is Monitor from KAOSTools. ***");
Console.WriteLine("*** For more information on KAOSTools see <https://github.com/ancailliau/KAOSTools> ***");
Console.WriteLine("*** Please report bugs to <https://github.com/ancailliau/KAOSTools/issues> ***");
Console.WriteLine();
Console.WriteLine("*** Copyright (c) 2017, Université catholique de Louvain ***");
Console.WriteLine("");
string rootname = "root";
options.Add("roots=", "Specify the roots goal for which to compute the satisfaction rate. (Default: root)", v => rootname = v);
string outfile = null;
options.Add("outfile=", "Specify the output file for the satisfaction rates", v => outfile = v);
Init(args);
optimization_model = BuildModel();
roots = rootname.Split(',').Select(x => model.Goal(x)).ToHashSet();
if (roots.Count() == 0 || roots.Any(x => x == null))
{
PrintError("A root goal among '" + rootname + "' was not found");
}
try {
modelMonitor = new ModelMonitor(model, roots);
modelMonitor.SetOutputFile(outfile);
_active_resolutions = new HashSet <Resolution>();
_integrator_model = new SoftResolutionIntegrator(model);
//optimizer = new MOCECountermeasureSelectionOptimizer(optimization_model);
//optimization_model.satisfactionRateRepository = modelMonitor._model_running.satisfactionRateRepository;
var commands = new List <ICommand>();
commands.Add(new GetSatisfactionRateCommand(model, roots, modelMonitor));
commands.Add(new ExportModelCommand(model));
commands.Add(new PrintDebugCommand(model, roots, modelMonitor));
stop = false;
Listen();
Optimize();
while (!stop)
{
Console.Write("> ");
var input = Console.ReadLine();
if (input.Equals("quit") | input.Equals("exit"))
{
stop = true;
continue;
}
foreach (var command in commands)
{
command.Execute(input);
}
}
Console.WriteLine("Exiting...");
modelMonitor.Stop();
} catch (Exception e) {
PrintError("An error occured during the computation. (" + e.Message + ").\n"
+ "Please report this error to <https://github.com/ancailliau/KAOSTools/issues>.\n"
+ "----------------------------\n"
+ e.StackTrace
+ "\n----------------------------\n");
}
}