Implementation for learning MMLTs, new model for collecting statistics

README.md

@@ -17,19 +17,19 @@ While certain features have been stripped for improved modularity, development h
 Currently, the following learning algorithms with respective target models are supported:
 
 
-| Algorithm (active)  | Target models               |     | Algorithm (passive)   | Models                |
-|---------------------|-----------------------------|-----|-----------------------|-----------------------|
-| AAAR                | `DFA` `Mealy` `Moore`       |     | OSTIA                 | `SST`                 |
-| ADT                 | `Mealy`                     |     | RPNI (incl. variants) | `DFA` `Mealy` `Moore` |
-| DHC                 | `Mealy`                     |     |                       |                       |
-| Kearns & Vazirani   | `DFA` `Mealy`               |     |                       |                       |
-| Lambda              | `DFA` `Mealy`               |     |                       |                       |
-| L#                  | `Mealy`                     |     |                       |                       |
-| L* (incl. variants) | `DFA` `Mealy` `Moore`       |     |                       |                       |
-| NL*                 | `NFA`                       |     |                       |                       |
-| Observation Pack    | `DFA` `Mealy` `Moore` `VPA` |     |                       |                       |
-| Procedural          | `SPA` `SBA` `SPMM`          |     |                       |                       |
-| TTT                 | `DFA` `Mealy` `Moore` `VPA` |     |                       |                       |
+| Algorithm (active)  | Target models                |     | Algorithm (passive)   | Models                |
+|---------------------|------------------------------|-----|-----------------------|-----------------------|
+| AAAR                | `DFA` `Mealy` `Moore`        |     | OSTIA                 | `SST`                 |
+| ADT                 | `Mealy`                      |     | RPNI (incl. variants) | `DFA` `Mealy` `Moore` |
+| DHC                 | `Mealy`                      |     |                       |                       |
+| Kearns & Vazirani   | `DFA` `Mealy`                |     |                       |                       |
+| Lambda              | `DFA` `Mealy`                |     |                       |                       |
+| L#                  | `Mealy`                      |     |                       |                       |
+| L* (incl. variants) | `DFA` `Mealy` `Moore` `MMLT` |     |                       |                       |
+| NL*                 | `NFA`                        |     |                       |                       |
+| Observation Pack    | `DFA` `Mealy` `Moore` `VPA`  |     |                       |                       |
+| Procedural          | `SPA` `SBA` `SPMM`           |     |                       |                       |
+| TTT                 | `DFA` `Mealy` `Moore` `VPA`  |     |                       |                       |
 
 Additionally, LearnLib offers a variety of tools to ease the practical application of automata learning on real-world systems.
 This includes drivers and mappers for interfacing software systems with the LearnLib API as well as caches and parallelization for improving the overall performance of the learning setup.

algorithms/active/adt/src/test/java/de/learnlib/algorithm/adt/it/ADTIT.java

@@ -42,6 +42,7 @@
 import de.learnlib.oracle.equivalence.MealySimulatorEQOracle;
 import de.learnlib.oracle.membership.MealySimulatorOracle;
 import de.learnlib.oracle.membership.SULAdaptiveOracle;
+import de.learnlib.statistic.Statistics;
 import de.learnlib.sul.SUL;
 import de.learnlib.testsupport.MQ2AQWrapper;
 import de.learnlib.testsupport.it.learner.AbstractMealyLearnerIT;
@@ -130,6 +131,7 @@ public void testIssue137() throws IOException, FormatException {
                     for (int seed = 0; seed < 50; seed++) {
                         long last = 0;
                         for (int iter = 0; iter < 5; iter++) {
+                            Statistics.getCollector().clear();
                             final CounterAdaptiveQueryOracle<String, String> counter =
                                     new CounterAdaptiveQueryOracle<>(aqo);
                             final ADTLearner<String, String> learner = new ADTLearner<>(alphabet,
@@ -151,7 +153,8 @@ public void testIssue137() throws IOException, FormatException {
 
                             exp.run();
 
-                            final long count = counter.getResetCounter().getCount();
+                            final long count =
+                                    Statistics.getCollector().getCount(CounterAdaptiveQueryOracle.RESET_KEY).orElse(0L);
 
                             if (iter == 0) {
                                 last = count;

algorithms/active/lstar/pom.xml

@@ -50,6 +50,10 @@ limitations under the License.
             <groupId>de.learnlib</groupId>
             <artifactId>learnlib-counterexamples</artifactId>
         </dependency>
+        <dependency>
+            <groupId>de.learnlib</groupId>
+            <artifactId>learnlib-symbol-filters</artifactId>
+        </dependency>
         <dependency>
             <groupId>de.learnlib</groupId>
             <artifactId>learnlib-util</artifactId>
@@ -124,6 +128,21 @@ limitations under the License.
             <groupId>org.testng</groupId>
             <artifactId>testng</artifactId>
         </dependency>
+        <dependency>
+            <groupId>net.automatalib</groupId>
+            <artifactId>automata-serialization-dot</artifactId>
+            <scope>test</scope>
+        </dependency>
+        <dependency>
+            <groupId>de.learnlib</groupId>
+            <artifactId>learnlib-cache</artifactId>
+            <scope>test</scope>
+        </dependency>
+        <dependency>
+            <groupId>de.learnlib</groupId>
+            <artifactId>learnlib-statistics</artifactId>
+            <scope>test</scope>
+        </dependency>
     </dependencies>
 
     <build>
@@ -134,7 +153,25 @@ limitations under the License.
                     <artifactId>maven-surefire-plugin</artifactId>
                     <configuration>
                         <!-- append to existing argLine to nicely work together with jacoco plugin -->
-                        <argLine>@{argLine} --add-reads=de.learnlib.algorithm.lstar=net.automatalib.util</argLine>
+                        <!-- allow tests access to util and statistics -->
+                        <argLine>
+                            @{argLine}
+                            --add-reads=de.learnlib.algorithm.lstar=net.automatalib.util
+                            --add-reads=de.learnlib.algorithm.lstar=de.learnlib.filter.statistic
+                        </argLine>
+                    </configuration>
+                </plugin>
+                <plugin>
+                    <groupId>org.apache.maven.plugins</groupId>
+                    <artifactId>maven-failsafe-plugin</artifactId>
+                    <configuration>
+                        <!-- append to existing argLine to nicely work together with jacoco plugin -->
+                        <!-- allow tests access to util and statistics -->
+                        <argLine>
+                            @{argLine}
+                            --add-reads=de.learnlib.algorithm.lstar=net.automatalib.util
+                            --add-reads=de.learnlib.algorithm.lstar=de.learnlib.filter.statistic
+                        </argLine>
                     </configuration>
                 </plugin>
             </plugins>