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
|
/*******************************************************************************
* Copyright (c) 2010-2016, Andras Szabolcs Nagy, Zoltan Ujhelyi and Daniel Varro
* This program and the accompanying materials are made available under the
* terms of the Eclipse Public License v. 2.0 which is available at
* http://www.eclipse.org/legal/epl-v20.html.
*
* SPDX-License-Identifier: EPL-2.0
*******************************************************************************/
package org.eclipse.viatra.dse.api.strategy.impl;
import java.util.Collection;
import java.util.Iterator;
import java.util.Random;
import java.util.concurrent.atomic.AtomicBoolean;
import org.apache.log4j.Logger;
import org.eclipse.viatra.dse.api.DSEException;
import org.eclipse.viatra.dse.api.strategy.interfaces.IStrategy;
import org.eclipse.viatra.dse.base.ThreadContext;
import org.eclipse.viatra.dse.objectives.Fitness;
/**
* A depth-first search algorithm implementation, that
* <ul>
* <li>can work with multiple threads,</li>
* <li>randomly traverses the search space,</li>
* <li>saves all states (trajectories) as solutions that fulfill all the hard objectives,</li>
* <li>can have a depth limit,</li>
* <li>will backtrack when a model satisfies the hard objectives (after saving it as a solution), which can be modified
* by calling {@link #continueIfHardObjectivesFulfilled()}</li>
* </ul>
*
* @author Andras Szabolcs Nagy
*
*/
public class DepthFirstStrategy implements IStrategy {
private int maxDepth;
private AtomicBoolean isInterrupted = new AtomicBoolean(false);
private ThreadContext context;
private Logger logger = Logger.getLogger(IStrategy.class);
private Random random = new Random();
private boolean backTrackIfSolution = true;
/**
* Creates a new depth-first search algorithm without depth limit.
*/
public DepthFirstStrategy() {
this.maxDepth = Integer.MAX_VALUE;
}
/**
* Creates a new depth-first search algorithm with depth limit.
*
* @param maxDepth
* A negative <code>maxDepth</code> means no depth limit, zero means the checking of the initial state.
*/
public DepthFirstStrategy(int maxDepth) {
if (maxDepth < 0) {
this.maxDepth = Integer.MAX_VALUE;
} else {
this.maxDepth = maxDepth;
}
}
/**
* If called, the algorithm will not backtrack after the hard objectives are fulfilled, instead it goes deeper in
* the search space.
*/
public DepthFirstStrategy continueIfHardObjectivesFulfilled() {
backTrackIfSolution = false;
return this;
}
@Override
public void initStrategy(ThreadContext context) {
this.context = context;
if (context.getSharedObject() == null) {
context.setSharedObject(new Object());
logger.info("Depth-first exploration strategy is initied.");
startThreads();
}
}
private void startThreads() {
context.startAllThreads(() -> new DepthFirstStrategy(maxDepth));
}
@Override
public void explore() {
mainloop: do {
boolean globalConstraintsAreSatisfied = context.checkGlobalConstraints();
if (!globalConstraintsAreSatisfied) {
boolean isSuccessfulUndo = context.backtrack();
if (!isSuccessfulUndo) {
logger.info("Global contraint is not satisifed and cannot backtrack.");
break;
} else {
logger.debug("Global contraint is not satisifed, backtrack.");
continue;
}
}
Fitness fitness = context.calculateFitness();
if (fitness.isSatisifiesHardObjectives()) {
context.newSolution();
if (backTrackIfSolution) {
boolean isSuccessfulUndo = context.backtrack();
if (!isSuccessfulUndo) {
logger.info("Found a solution but cannot backtrack.");
break;
} else {
logger.debug("Found a solution, backtrack.");
continue;
}
}
}
if (context.getDepth() >= maxDepth) {
boolean isSuccessfulUndo = context.backtrack();
if (!isSuccessfulUndo) {
logger.info("Reached max depth but cannot bactrack.");
break;
} else {
logger.debug("Reached max depth, bactrack.");
continue;
}
}
if (isInterrupted.get()) {
logger.info("Interrupted, stop exploration.");
break;
}
Object activationId = null;
Collection<Object> activationIds;
do {
activationIds = context.getUntraversedActivationIds();
if (activationIds.isEmpty()) {
boolean isSuccessfulUndo = context.backtrack();
if (!isSuccessfulUndo) {
logger.info("No more transitions from current state and cannot backtrack.");
break mainloop;
} else {
logger.debug("No more transitions from current state, backtrack.");
continue;
}
}
} while (activationIds.isEmpty());
int index = random.nextInt(activationIds.size());
Iterator<Object> iterator = activationIds.iterator();
while (index-- > 0) {
iterator.next();
}
activationId = iterator.next();
context.executeAcitvationId(activationId);
boolean loopInTrajectory = context.isCurrentStateInTrajectory();
if (loopInTrajectory) {
boolean isSuccessfulUndo = context.backtrack();
if (!isSuccessfulUndo) {
throw new DSEException("The new state is present in the trajectoy but cannot bactkrack. Should never happen!");
} else {
logger.info("The new state is already visited in the trajectory, backtrack.");
}
}
} while (true);
logger.info("Terminated.");
}
@Override
public void interruptStrategy() {
isInterrupted.set(true);
}
}
|