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IncrementalProgram.cs
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IncrementalProgram.cs
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using System;
using System.Collections.Generic;
using System.IO;
using System.Diagnostics;
using System.Linq;
using NMF.Models.Repository;
using NMF.Utilities;
using TTC2016.ArchitectureCRA.ArchitectureCRA;
using NMF.Expressions;
using NMF.Expressions.Linq;
namespace ClassDiagramOptimization
{
class IncrementalProgram
{
static void Main(string[] args)
{
var stopwatch = new Stopwatch();
stopwatch.Start();
var repository = new ModelRepository();
var model = repository.Resolve(args[0]);
var classModel = model.RootElements[0] as ClassModel;
stopwatch.Stop();
Console.WriteLine("Loading model took {0}ms", stopwatch.ElapsedMilliseconds);
var dataDependencyCounts = new Dictionary<IAttribute, List<Method>>();
var functionalDependencyCounts = new Dictionary<IMethod, List<Method>>();
stopwatch.Restart();
foreach (var feature in classModel.Features.OfType<Method>())
{
var featureClass = new Class()
{
Name = "C" + feature.Name
};
featureClass.Encapsulates.Add(feature);
classModel.Classes.Add(featureClass);
foreach (var dataDependency in feature.DataDependency)
{
List<Method> methods;
if (!dataDependencyCounts.TryGetValue(dataDependency, out methods))
{
methods = new List<Method>();
dataDependencyCounts.Add(dataDependency, methods);
}
methods.Add(feature);
}
foreach (var functionalDependency in feature.FunctionalDependency)
{
List<Method> methods;
if (!functionalDependencyCounts.TryGetValue(functionalDependency, out methods))
{
methods = new List<Method>();
functionalDependencyCounts.Add(functionalDependency, methods);
}
methods.Add(feature);
}
if (!functionalDependencyCounts.ContainsKey(feature)) functionalDependencyCounts.Add(feature, new List<Method>());
}
foreach (var attribute in classModel.Features.OfType<IAttribute>())
{
List<Method> dependingMethods;
if (dataDependencyCounts.TryGetValue(attribute, out dependingMethods))
{
if (dependingMethods.Count == 1)
{
dependingMethods[0].IsEncapsulatedBy.Encapsulates.Add(attribute);
continue;
}
}
else
{
dependingMethods = new List<Method>();
dataDependencyCounts.Add(attribute, dependingMethods);
}
var featureClass = new Class()
{
Name = "C" + attribute.Name
};
featureClass.Encapsulates.Add(attribute);
classModel.Classes.Add(featureClass);
}
var combinationCount = new Func<int, int>(i => i * (i - 1));
var divideOrZero = new Func<double, double, double>((a, b) => b == 0 ? 0 : a / b);
var M = new MemoizedFunc<IClass, int>(cl => cl == null ? 0 : cl.Encapsulates.OfType<Method>().Count());
var A = new MemoizedFunc<IClass, int>(cl => cl == null ? 0 : cl.Encapsulates.OfType<IAttribute>().Count());
var MAI = new MemoizedFunc<IClass, IClass, double>((cl_i, cl_j) =>
cl_i == null || cl_j == null ? 0 :
cl_i.Encapsulates.OfType<Method>()
.Sum(m => m.DataDependency.Intersect(cl_j.Encapsulates).Count()));
var MMI = new MemoizedFunc<IClass, IClass, double>((cl_i, cl_j) =>
cl_i == null || cl_j == null ? 0 :
cl_i.Encapsulates.OfType<Method>()
.Sum(m => m.FunctionalDependency.Intersect(cl_j.Encapsulates).Count()));
var dataDependingClassesCoupling = new ObservingFunc<IClass, IClass, double>(
(cl_i, cl_j) =>
(from att in cl_i.Encapsulates.OfType<IAttribute>().Concat(cl_j.Encapsulates.OfType<IAttribute>())
from meth in dataDependencyCounts[att]
select meth.IsEncapsulatedBy).Distinct().Sum(ck =>
ck == cl_i || ck == cl_j ? 0
: (divideOrZero(MAI[ck, cl_i], M[ck] * A[cl_i]) +
divideOrZero(MAI[ck, cl_j], A[cl_j] * M[ck]) -
divideOrZero(MAI[ck, cl_i] + MAI[ck, cl_j], (A[cl_i] + A[cl_j]) * M[ck]))
));
var dataDependingClassesCouplingMemo = new MemoizedFunc<IClass, IClass, INotifyValue<double>>(
(cl_i, cl_j) => dataDependingClassesCoupling.Observe(cl_i, cl_j));
var functionalDependingClassesCoupling = new ObservingFunc<IClass, IClass, double>(
(cl_i, cl_j) =>
(from m2 in cl_i.Encapsulates.OfType<Method>().Concat(cl_j.Encapsulates.OfType<Method>())
from meth in functionalDependencyCounts[m2]
select meth.IsEncapsulatedBy).Distinct().Sum(ck =>
ck == cl_i || ck == cl_j ? 0
: (divideOrZero(MMI[ck, cl_i], (M[cl_i] - 1) * M[ck]) +
divideOrZero(MMI[ck, cl_j], (M[cl_j] - 1) * M[ck]) -
divideOrZero(MMI[ck, cl_i] + MMI[ck, cl_j], (M[cl_i] + M[cl_j] - 1) * M[ck]))
));
var functionalDependingClassesCouplingMemo = new MemoizedFunc<IClass, IClass, INotifyValue<double>>(
(cl_i, cl_j) => functionalDependingClassesCoupling.Observe(cl_i, cl_j));
var dataDependentClassesCoupling = new ObservingFunc<IClass, IClass, double>(
(cl_i, cl_j) =>
(from meth in cl_i.Encapsulates.OfType<Method>().Concat(cl_j.Encapsulates.OfType<Method>())
from dataDep in meth.DataDependency
select dataDep.IsEncapsulatedBy).Distinct().Sum(ck =>
divideOrZero(MAI[cl_i, ck], M[cl_i] * A[ck]) +
divideOrZero(MAI[cl_j, ck], M[cl_j] * A[ck]) -
divideOrZero(MAI[cl_i, ck] + MAI[cl_j, ck], (M[cl_i] + M[cl_j]) * A[ck])
));
var dataDependentClassesCouplingMemo = new MemoizedFunc<IClass, IClass, INotifyValue<double>>(
(cl_i, cl_j) => dataDependentClassesCoupling.Observe(cl_i, cl_j));
var functionalDependentClassesCoupling = new ObservingFunc<IClass, IClass, double>(
(cl_i, cl_j) =>
(from meth in cl_i.Encapsulates.OfType<Method>().Concat(cl_j.Encapsulates.OfType<Method>())
from functionalDep in meth.FunctionalDependency
select functionalDep.IsEncapsulatedBy).Distinct().Sum(ck =>
ck == cl_i || ck == cl_j ? 0
: divideOrZero(MMI[cl_i, ck], M[cl_i] * M[ck]) +
divideOrZero(MMI[cl_j, ck], M[cl_j] * M[ck]) -
divideOrZero(MMI[cl_i, ck] + MMI[cl_j, ck], (M[cl_i] + M[cl_j]) * M[ck])
));
var functionalDependentClassesCouplingMemo = new MemoizedFunc<IClass, IClass, INotifyValue<double>>(
(cl_i, cl_j) => functionalDependingClassesCoupling.Observe(cl_i, cl_j));
var Effect = new Func<IClass, IClass, double>((cl_i, cl_j) =>
{
var M_i = M[cl_i];
var M_j = M[cl_j];
var A_i = A[cl_i];
var A_j = A[cl_j];
var MAI_i = MAI[cl_i, cl_i];
var MAI_j = MAI[cl_j, cl_j];
var MAI_ij = MAI[cl_i, cl_j];
var MAI_ji = MAI[cl_j, cl_i];
var MMI_i = MMI[cl_i, cl_i];
var MMI_j = MMI[cl_j, cl_j];
var MMI_ij = MMI[cl_i, cl_j];
var MMI_ji = MMI[cl_j, cl_i];
var deltaCohesionDataDep = // Delta of Cohesion based on data dependencies
divideOrZero(MAI_i + MAI_ij + MAI_ji + MAI_j, (M_i + M_j) * (A_i + A_j)) - divideOrZero(MAI_i, M_i * A_i) - divideOrZero(MAI_j, M_j * A_j);
var deltaCohesionFunctionalDep = // Delta of Cohesion based on functional dependencies
divideOrZero(MMI_i + MMI_ij + MMI_ji + MMI_j, combinationCount(M_i + M_j)) - divideOrZero(MMI_i, combinationCount(M_i)) - divideOrZero(MMI_j, combinationCount(M_j));
var deltaCouplingij = // Delta of Coupling between C_i and C_j
divideOrZero(MAI_ij, M_i * A_j) + divideOrZero(MAI_ji, M_j * A_i) + divideOrZero(MMI_ij, M_i * (M_j - 1)) + divideOrZero(MMI_ji, M_j * (M_i - 1));
var deltaCouplingFromOthers = // Coupling from other classes
dataDependingClassesCouplingMemo[cl_i, cl_j].Value + functionalDependingClassesCouplingMemo[cl_i, cl_j].Value;
var deltaCouplingToOthers = dataDependentClassesCouplingMemo[cl_i, cl_j].Value + functionalDependentClassesCouplingMemo[cl_i, cl_j].Value;
return deltaCohesionDataDep + deltaCohesionFunctionalDep + deltaCouplingij + deltaCouplingToOthers + deltaCouplingFromOthers;
});
var allClasses = false;
var prioritizedMerges = (from cl_i in classModel.Classes
where allClasses || cl_i.Encapsulates.All(f => f is IAttribute)
from cl_j in classModel.Classes
where cl_i.Name.CompareTo(cl_j.Name) < 0
select new
{
Cl_i = cl_i,
Cl_j = cl_j,
Effect = Effect(cl_i, cl_j)
}).OrderByDescending(m => m.Effect);
var nextMerge = prioritizedMerges.FirstOrDefault();
var classCounter = 1;
while (nextMerge != null && nextMerge.Effect > 0)
{
Console.WriteLine("Now merging {0} and {1}, should have effect {2}", nextMerge.Cl_i.Name, nextMerge.Cl_j.Name, nextMerge.Effect);
// We need to save the features from these classes as they will be dropped as soon as we delete the encapsulating classes
var newFeatures = nextMerge.Cl_i.Encapsulates.Concat(nextMerge.Cl_j.Encapsulates).ToList();
classModel.Classes.Remove(nextMerge.Cl_i);
classModel.Classes.Remove(nextMerge.Cl_j);
var newClass = new Class() { Name = "C" + (classCounter++).ToString() };
newClass.Encapsulates.AddRange(newFeatures);
classModel.Classes.Add(newClass);
nextMerge = prioritizedMerges.FirstOrDefault();
}
allClasses = true;
nextMerge = prioritizedMerges.FirstOrDefault();
while (nextMerge != null && nextMerge.Effect > 0)
{
Console.WriteLine("Now merging {0} and {1}, should have effect {2}", nextMerge.Cl_i.Name, nextMerge.Cl_j.Name, nextMerge.Effect);
// We need to save the features from these classes as they will be dropped as soon as we delete the encapsulating classes
var newFeatures = nextMerge.Cl_i.Encapsulates.Concat(nextMerge.Cl_j.Encapsulates).ToList();
classModel.Classes.Remove(nextMerge.Cl_i);
classModel.Classes.Remove(nextMerge.Cl_j);
var newClass = new Class() { Name = "C" + (classCounter++).ToString() };
newClass.Encapsulates.AddRange(newFeatures);
classModel.Classes.Add(newClass);
nextMerge = prioritizedMerges.FirstOrDefault();
}
stopwatch.Stop();
Console.WriteLine("Model optimization took {0}ms", stopwatch.ElapsedMilliseconds);
using (var writer = File.AppendText("results.csv"))
{
writer.WriteLine("Incremental;{0};{1}", stopwatch.ElapsedMilliseconds, args[0]);
}
Console.WriteLine("Output contains {0} classes", classModel.Classes.Count);
stopwatch.Restart();
classModel.Name = "Optimized Class Model";
repository.Save(classModel, Path.ChangeExtension(args[0], ".Output.xmi"));
stopwatch.Stop();
Console.WriteLine("Serializing result model took {0}ms", stopwatch.ElapsedMilliseconds);
}
}
}