/// <summary>
/// Try to find a configuration with low weight.
/// </summary>
/// <param name="sortedRanking">A list of binary options and their weight ordered by their weight.</param>
/// <param name="cache">A sat solver cache instance that already contains the constraints of
/// size and disallowed features.</param>
/// <param name="vm">The variability model of the given system.</param>
/// <returns>A configuration that has a small weight.</returns>
public static List <BinaryOption> getSmallWeightConfig(List <KeyValuePair <List <BinaryOption>, int> > sortedRanking,
Z3Cache cache, VariabilityModel vm)
{
KeyValuePair <List <BinaryOption>, int>[] ranking = sortedRanking.ToArray();
Microsoft.Z3.Solver solver = cache.GetSolver();
Context z3Context = cache.GetContext();
for (int i = 0; i < ranking.Length; i++)
{
List <BinaryOption> candidates = ranking[i].Key;
solver.Push();
solver.Assert(forceFeatures(candidates, z3Context, cache.GetOptionToTermMapping()));
if (solver.Check() == Status.SATISFIABLE)
{
Model model = solver.Model;
solver.Pop();
return(Z3VariantGenerator.RetrieveConfiguration(cache.GetVariables(), model,
cache.GetTermToOptionMapping()));
}
solver.Pop();
}
return(null);
}
private void ReAssertDecisionAssumptions()
{
_solver.Pop();
_solver.Push();
foreach (Assumption assumption in _decisionAssumptions.Values)
{
AssertValueAssumption(assumption);
}
}
/// <summary>
/// Generates all valid combinations of all configuration options in the given model.
/// </summary>
/// <param name="vm">the variability model containing the binary options and their constraints</param>
/// <param name="optionsToConsider">the options that should be considered. All other options are ignored</param>
/// <returns>Returns a list of <see cref="Configuration"/></returns>
public List <Configuration> GenerateAllVariants(VariabilityModel vm, List <ConfigurationOption> optionsToConsider)
{
List <Configuration> allConfigurations = new List <Configuration>();
List <BoolExpr> variables;
Dictionary <BoolExpr, BinaryOption> termToOption;
Dictionary <BinaryOption, BoolExpr> optionToTerm;
Tuple <Context, BoolExpr> z3Tuple = Z3Solver.GetInitializedBooleanSolverSystem(out variables, out optionToTerm, out termToOption, vm, this.henard);
Context z3Context = z3Tuple.Item1;
BoolExpr z3Constraints = z3Tuple.Item2;
Microsoft.Z3.Solver solver = z3Context.MkSolver();
// TODO: The following line works for z3Solver version >= 4.6.0
//solver.Set (RANDOM_SEED, z3RandomSeed);
Params solverParameter = z3Context.MkParams();
solverParameter.Add(RANDOM_SEED, z3RandomSeed);
solver.Parameters = solverParameter;
solver.Assert(z3Constraints);
while (solver.Check() == Status.SATISFIABLE)
{
Model model = solver.Model;
List <BinaryOption> binOpts = RetrieveConfiguration(variables, model, termToOption, optionsToConsider);
Configuration c = new Configuration(binOpts);
// Check if the non-boolean constraints are satisfied
if (vm.configurationIsValid(c) && !VariantGenerator.IsInConfigurationFile(c, allConfigurations) && VariantGenerator.FulfillsMixedConstraints(c, vm))
{
allConfigurations.Add(c);
}
solver.Push();
solver.Assert(Z3Solver.NegateExpr(z3Context, Z3Solver.ConvertConfiguration(z3Context, binOpts, optionToTerm, vm)));
}
solver.Push();
solver.Pop(Convert.ToUInt32(allConfigurations.Count() + 1));
return(allConfigurations);
}
/// <summary>
/// Generates all valid combinations of all configuration options in the given model.
/// </summary>
/// <param name="vm">the variability model containing the binary options and their constraints</param>
/// <param name="optionsToConsider">the options that should be considered. All other options are ignored</param>
/// <returns>Returns a list of <see cref="Configuration"/></returns>
public List <Configuration> GenerateAllVariants(VariabilityModel vm, List <ConfigurationOption> optionsToConsider)
{
List <Configuration> allConfigurations = new List <Configuration>();
List <Expr> variables;
Dictionary <Expr, ConfigurationOption> termToOption;
Dictionary <ConfigurationOption, Expr> optionToTerm;
Tuple <Context, BoolExpr> z3Tuple = Z3Solver.GetInitializedSolverSystem(out variables, out optionToTerm, out termToOption, vm);
Context z3Context = z3Tuple.Item1;
BoolExpr z3Constraints = z3Tuple.Item2;
Microsoft.Z3.Solver solver = z3Context.MkSolver();
solver.Set(RANDOM_SEED, z3RandomSeed);
solver.Assert(z3Constraints);
while (solver.Check() == Status.SATISFIABLE)
{
Model model = solver.Model;
Tuple <List <BinaryOption>, Dictionary <NumericOption, double> > confOpts = RetrieveConfiguration(variables, model, termToOption, optionsToConsider);
Configuration c = new Configuration(confOpts.Item1, confOpts.Item2);
// Check if the non-boolean constraints are satisfied
bool configIsValid = vm.configurationIsValid(c);
bool isInConfigurationFile = !VariantGenerator.IsInConfigurationFile(c, allConfigurations);
bool fulfillsMixedConstraintrs = VariantGenerator.FulfillsMixedConstraints(c, vm);
if (configIsValid && isInConfigurationFile && fulfillsMixedConstraintrs)
{
allConfigurations.Add(c);
}
solver.Push();
solver.Assert(Z3Solver.NegateExpr(z3Context, Z3Solver.ConvertConfiguration(z3Context, confOpts.Item1, optionToTerm, vm, numericValues: confOpts.Item2)));
}
solver.Push();
solver.Pop(Convert.ToUInt32(allConfigurations.Count() + 1));
return(allConfigurations);
}
// Constructor
public SolverContext(Modelling.BLOs.Model model)
{
// Create an empty z3 context
Dictionary <string, string> configSettings = new Dictionary <string, string>();
configSettings["MODEL"] = "true";
configSettings["MACRO_FINDER"] = "true";
_context = new Context(configSettings);
_context.PrintMode = Z3_ast_print_mode.Z3_PRINT_SMTLIB2_COMPLIANT;
// Setup the z3 context and solver
_solver = _context.MkSolver();
// Setup custom conversion method BoolToInt (boolean -> integer)
FuncDecl boolToInt = _context.MkFuncDecl("BoolToInt", _context.MkBoolSort(), _context.MkIntSort());
Expr i = _context.MkConst("i", _context.MkBoolSort());
Expr fDef = _context.MkITE(_context.MkEq(i, _context.MkTrue()), _context.MkInt(1), _context.MkInt(0)); // x == true => 1, x == false => 0
Expr fStatement = _context.MkForall(new Expr[] { i }, _context.MkEq(_context.MkApp(boolToInt, i), fDef));
_solver.Assert(fStatement as BoolExpr);
_functions.Add("BoolToInt", new Function(boolToInt));
// Create the static part (constants and constraints)
model.Features.ForEach(feature =>
{
string featureSID = GenerateFeatureSID(feature.Identifier);
AddFeature_Constant(feature.Identifier);
feature.Attributes.ForEach(attribute => AddAttribute_Constant(attribute.Identifier, feature.Identifier, attribute.AttributeDataType));
});
model.Relations.ForEach(relation =>
{
AddRelation_Constraint(relation.RelationType, relation.ParentFeature.Identifier, relation.ChildFeature.Identifier);
});
model.GroupRelations.ForEach(groupRelation =>
{
string[] childFeatureIDs = groupRelation.ChildFeatures.Select(feature => feature.Identifier).ToArray();
AddGroupRelation_Constraint(groupRelation.GroupRelationType, groupRelation.ParentFeature.Identifier, childFeatureIDs,
groupRelation.UpperBound ?? default(int), groupRelation.LowerBound ?? default(int));
});
model.CompositionRules.ForEach(compRule =>
{
AddCompositionRule_Constraint(compRule.CompositionRuleType, compRule.FirstFeature.Identifier, compRule.SecondFeature.Identifier);
});
// Create initial point
_solver.Push();
}
/// <summary>
/// Demonstrate how to use <code>Push</code>and <code>Pop</code>to
/// control the size of models.
/// </summary>
/// <remarks>Note: this test is specialized to 32-bit bitvectors.</remarks>
public static void CheckSmall(Context ctx, Solver solver, BitVecExpr[] to_minimize)
{
Sort bv32 = ctx.MkBitVecSort(32);
int num_Exprs = to_minimize.Length;
UInt32[] upper = new UInt32[num_Exprs];
UInt32[] lower = new UInt32[num_Exprs];
BitVecExpr[] values = new BitVecExpr[num_Exprs];
for (int i = 0; i < upper.Length; ++i)
{
upper[i] = UInt32.MaxValue;
lower[i] = 0;
}
bool some_work = true;
int last_index = -1;
UInt32 last_upper = 0;
while (some_work)
{
solver.Push();
bool check_is_sat = true;
while (check_is_sat && some_work)
{
// Assert all feasible bounds.
for (int i = 0; i < num_Exprs; ++i)
{
solver.Assert(ctx.MkBVULE(to_minimize[i], ctx.MkBV(upper[i], 32)));
}
check_is_sat = Status.SATISFIABLE == solver.Check();
if (!check_is_sat)
{
if (last_index != -1)
{
lower[last_index] = last_upper + 1;
}
break;
}
Console.WriteLine("{0}", solver.Model);
// narrow the bounds based on the current model.
for (int i = 0; i < num_Exprs; ++i)
{
Expr v = solver.Model.Evaluate(to_minimize[i]);
UInt64 ui = ((BitVecNum)v).UInt64;
if (ui < upper[i])
{
upper[i] = (UInt32)ui;
}
Console.WriteLine("{0} {1} {2}", i, lower[i], upper[i]);
}
// find a new bound to add
some_work = false;
last_index = 0;
for (int i = 0; i < num_Exprs; ++i)
{
if (lower[i] < upper[i])
{
last_upper = (upper[i] + lower[i]) / 2;
last_index = i;
solver.Assert(ctx.MkBVULE(to_minimize[i], ctx.MkBV(last_upper, 32)));
some_work = true;
break;
}
}
}
solver.Pop();
}
}
/// <summary>
/// Generates up to n solutions of the given variability model.
/// Note that this method could also generate less than n solutions if the variability model does not contain sufficient solutions.
/// Moreover, in the case that <code>n < 0</code>, all solutions are generated.
/// </summary>
/// <param name="vm">The <see cref="VariabilityModel"/> to obtain solutions for.</param>
/// <param name="n">The number of solutions to obtain.</param>
/// <returns>A list of configurations, in which a configuration is a list of SELECTED binary options.</returns>
public List <List <BinaryOption> > GenerateUpToNFast(VariabilityModel vm, int n)
{
// Use the random seed to produce new random seeds
Random random = new Random(Convert.ToInt32(z3RandomSeed));
List <BoolExpr> variables;
Dictionary <BoolExpr, BinaryOption> termToOption;
Dictionary <BinaryOption, BoolExpr> optionToTerm;
Tuple <Context, BoolExpr> z3Tuple = Z3Solver.GetInitializedBooleanSolverSystem(out variables, out optionToTerm, out termToOption, vm, this.henard, random.Next());
Context z3Context = z3Tuple.Item1;
BoolExpr z3Constraints = z3Tuple.Item2;
List <BoolExpr> excludedConfigurations = new List <BoolExpr>();
List <BoolExpr> constraints = Z3Solver.lastConstraints;
List <List <BinaryOption> > configurations = new List <List <BinaryOption> >();
Microsoft.Z3.Solver s = z3Context.MkSolver();
// TODO: The following line works for z3Solver version >= 4.6.0
//solver.Set (RANDOM_SEED, z3RandomSeed);
Params solverParameter = z3Context.MkParams();
if (henard)
{
solverParameter.Add(RANDOM_SEED, NextUInt(random));
}
else
{
solverParameter.Add(RANDOM_SEED, z3RandomSeed);
}
s.Parameters = solverParameter;
s.Assert(z3Constraints);
s.Push();
Model model = null;
while (s.Check() == Status.SATISFIABLE && (configurations.Count < n || n < 0))
{
model = s.Model;
List <BinaryOption> config = RetrieveConfiguration(variables, model, termToOption);
configurations.Add(config);
if (henard)
{
BoolExpr newConstraint = Z3Solver.NegateExpr(z3Context, Z3Solver.ConvertConfiguration(z3Context, config, optionToTerm, vm));
excludedConfigurations.Add(newConstraint);
Dictionary <BoolExpr, BinaryOption> oldTermToOption = termToOption;
// Now, initialize a new one for the next configuration
z3Tuple = Z3Solver.GetInitializedBooleanSolverSystem(out variables, out optionToTerm, out termToOption, vm, this.henard, random.Next());
z3Context = z3Tuple.Item1;
z3Constraints = z3Tuple.Item2;
s = z3Context.MkSolver();
//s.Set (RANDOM_SEED, NextUInt (random));
solverParameter = z3Context.MkParams();
solverParameter.Add(RANDOM_SEED, NextUInt(random));
s.Parameters = solverParameter;
constraints = Z3Solver.lastConstraints;
excludedConfigurations = Z3Solver.ConvertConstraintsToNewContext(oldTermToOption, optionToTerm, excludedConfigurations, z3Context);
constraints.AddRange(excludedConfigurations);
s.Assert(z3Context.MkAnd(Z3Solver.Shuffle(constraints, new Random(random.Next()))));
s.Push();
}
else
{
s.Add(Z3Solver.NegateExpr(z3Context, Z3Solver.ConvertConfiguration(z3Context, config, optionToTerm, vm)));
}
}
return(configurations);
}