/
Program.cs
227 lines (213 loc) · 12.3 KB
/
Program.cs
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
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;
namespace ClassDiagramOptimization
{
class Program
{
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 Func<IClass, int>(cl => cl.Encapsulates.OfType<Method>().Count());
var A = new Func<IClass, int>(cl => cl.Encapsulates.OfType<IAttribute>().Count());
var MAI = new Func<IClass, IClass, double>((cl_i, cl_j) =>
cl_i.Encapsulates.OfType<Method>()
.Sum(m => m.DataDependency.Intersect(cl_j.Encapsulates).Count()));
var MMI = new Func<IClass, IClass, double>((cl_i, cl_j) =>
cl_i.Encapsulates.OfType<Method>()
.Sum(m => m.FunctionalDependency.Intersect(cl_j.Encapsulates).Count()));
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 classIAttributes = cl_i.Encapsulates.OfType<IAttribute>();
var classJAttributes = cl_j.Encapsulates.OfType<IAttribute>();
var classIMethods = cl_i.Encapsulates.OfType<Method>();
var classJMethods = cl_j.Encapsulates.OfType<Method>();
var dataDependingClasses = (from att in classIAttributes.Concat(classJAttributes)
from meth in dataDependencyCounts[att]
select meth.IsEncapsulatedBy).Distinct();
var functionalDependingClasses = (from m2 in classIMethods.Concat(classJMethods)
from meth in functionalDependencyCounts[m2]
select meth.IsEncapsulatedBy).Distinct();
var deltaCouplingFromOthers = // Coupling from other classes
dataDependingClasses.Sum(ck =>
{
if (ck == cl_i || ck == cl_j) return 0;
var mai_ki = MAI(ck, cl_i);
var mai_kj = MAI(ck, cl_j);
var m_k = M(ck);
return (divideOrZero(mai_ki, m_k * A_i) + divideOrZero(mai_kj, A_j * m_k) - divideOrZero(mai_ki + mai_kj, (A_i + A_j) * m_k));
})
+
functionalDependingClasses.Sum(ck =>
{
if (ck == cl_i || ck == cl_j) return 0;
var mmi_ki = MMI(ck, cl_i);
var mmi_kj = MMI(ck, cl_j);
var m_k = M(ck);
return (divideOrZero(mmi_ki, (M_i - 1) * m_k) + divideOrZero(mmi_kj, (M_j - 1) * m_k) - divideOrZero(mmi_ki + mmi_kj, (M_i + M_j - 1) * m_k));
});
var dataDependentClasses = (from meth in classIMethods.Concat(classJMethods)
from dataDep in meth.DataDependency
select dataDep.IsEncapsulatedBy).Distinct();
var FunctionalDependentClasses = (from meth in classIMethods.Concat(classJMethods)
from funDep in meth.FunctionalDependency
select funDep.IsEncapsulatedBy).Distinct();
var deltaCouplingToOthers = dataDependentClasses.Sum(ck =>
{
var mai_ik = MAI(cl_i, ck);
var mai_jk = MAI(cl_j, ck);
var a_k = A(ck);
return (divideOrZero(mai_ik, M_i * a_k) + divideOrZero(mai_jk, M_j * a_k) - divideOrZero(mai_ik + mai_jk, (M_i + M_j) * a_k));
})
+
FunctionalDependentClasses.Sum(ck =>
{
if (ck == cl_i || ck == cl_j) return 0;
var mmi_ik = MMI(cl_i, ck);
var mmi_jk = MMI(cl_j, ck);
var m_k = M(ck) - 1;
return (divideOrZero(mmi_ik, M_i * m_k) + divideOrZero(mmi_jk, M_j * m_k) - divideOrZero(mmi_ik + mmi_jk, (M_i + M_j) * m_k));
});
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("Normal;{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);
}
}
}