learnlib-0.17.0

Full changelog

Added

• Migrated the AAAR algorithm from the old closed-source LearnLib (thanks to @mtf90).
• Added Moore versions of the OP, TTT, and LStar learners (thanks to @mohbayram).
• Added the OML (optimal-MAT-learner) active learning algorithm (thanks to @fhowar).
• Added the OSTIA passive learning algorithm (thanks to @aleksander-mendoza).
• The RPNI learner now supports MooreMachines (thanks to @mtf90).
• Added new learning algorithms for procedural systems such as SPAs, SBAs, and SPMMs (thanks to @mtf90).

Changed

• Refactorings

  • Many LearnLib packages have been refactored from plural-based keywords to singular-based keywords. Some examples are

    • renamed all learning algorithm packages from de.learnlib.algorithms.* to de.learnlib.algorithm.*.
    • renamed de.learnlib.counterexamples.* to de.learnlib.counterexample.*.
    • renamed de.learnlib.drivers.* to de.learnlib.driver.*.
    • renamed de.learnlib.util.statistics.* to de.learnlib.util.statistic.*.
    • etc.

    While this may cause some refactoring, it should only affect import statements as the names of most classes remain identical.

  • Some actual re-namings concern

    • All code concerning visibly push-down automata now uses the "vpa" acronym (previously "vpda"). This includes package names, class names and (Maven) module names.
    • The "discrimination-tree" learner has been renamed to "observation-pack". This includes classes (DTLearnerDFA -> OPLearnerDFA, etc.), package names, and Maven modules. The same refactoring happened for the VPA-based version of the learner.
    • The learnlib-acex Maven module has been merged with the learnlib-counterexamples module.
    • Classes in the learnlib-api have been moved from de.learnlib.api to de.learnlib.
    • Refactored the package de.learnlib.datastructure.pta.pta.* to de.learnlib.datastructure.pta.*.
    • Refactored the package de.learnlib.driver.util.* to de.learnlib.driver.simulator.*.
    • Moved classes from the package de.learnlib.mapper.api.* to de.learnlib.sul.*.
    • Renamed PassiveLearnerVariantTICase to PassiveLearnerVariantITCase.
• AbstractTTTHypothesis has received an additional type parameter for its state type.
• AutomatonOracle#accepts no longer has a length parameter. Provide a correctly sized input iterable instead.
• Classes revolving around the ContextExecutableInputSUL have been moved from the learnlib-mapper module to the learnlib-drivers-basic module.
• The CounterOracle and JointCounterOracle have been merged. Now there only exists a single CounterOracle that counts both the number of queries and the number of symbols therein.
• The {DFA,Mealy}CacheOracles and the SULCache are no longer thread-safe because the intended pipeline of a parallel setup (as suggested by the LearnLib factory methods) consists of a single-threaded cache that delegates to parallel (non-cached) oracles. Here, the synchronization logic only adds unnecessary overhead. In case you want a shared, thread-safe cache (which was currently not possible to set up conveniently) the learnlib-parallelism module now contains the ThreadSafe{DFA,Mealy,SUL}Caches factories which allow one to construct parallel oracles (whose parameters and return types are tailored towards using our ParallelOracleBuilders factory) with a shared cache. See the in-tree ParallelismExample2 for reference.
• PTAs now read their sample inputs as IntSeqs.
• PassiveLearningAlgorithm#computeModel did not specify whether repeated calls to the method should yield identical models. It is now explicitly left open to the respective implementation to support this behavior. BlueFringeRPNI{DFA,Mealy,Moore} explicitly does not support this behavior, as the internal prefix-tree acceptor is now constructed on-the-fly as samples are added via the addSample methods. This allows to drop the previously redundant caching of samples and reduce memory pressure. BlueFringeEDSMDFA and BlueFringeMDLDFA still have to cache the samples internally and therefore still support repeated model construction.
• The Resumable semantics have changed: the returned state object no longer implements Serializable. We never fully supported the semantics of the interface and never intended to do so. In fact, the old approach failed miserably if any class was involved where we missed an "implements Serializable" statement. In order to prevent confusion by promising false contracts, implementing this markup interface has been removed. Serialization should now be done in user-land via one of the many external (and more optimizable) serialization frameworks such as FST, XStream, etc. See the in-tree ResumableExample for reference.
• The ADT class is no longer initialized with a leafSplitter but the extendLeaf and splitLeaf methods take an additional argument. This allows for a more customizable behavior.
• The automaton-specific SimulatorOracles are now generated automatically and therefore reside in the package de.learnlib.oracle.membership rather that being an inner-class of the SimulatorOracle.
• SymbolQueryCache now needs to be created via the MealyCaches factory.
• SimplePOJOTestDriver no longer uses a mapper to suppress SULExceptions but instead operates directly on the POJO with simplified inputs/outputs and propagates any exceptions thrown. To complement this change, the old SimplePOJODataMapper has been renamed to SimplePOJOExceptionMapper and only deals with mapping exceptions now. The old behavior can be restored by combining the two classes manually via SULMappers#apply.
• Switched to AutomataLib 0.11.0.

Removed

• Removed (unused) de.learnlib.datastructure.pta.pta.PropertyConflictException, de.learnlib.datastructure.observationtable.InvalidRowException.
• Removed the (protected) exposeInternalHypothesis method on AbstractAutomatonLStar. Subclasses should directly implement the getHypothesisModel method.
• Removed the EquivalenceQueries factory. All provided equivalence checkers are available via public constructors which allow for more flexible parameterization.
• Removed the Filter interface and FilterChain class. Instantiating the filters that are required for constructing a filter chain already requires setting the delegate oracles. Therefore, the only effect of this interface is that the attributes of the filters cannot be final.
• Removed LearnLogger. All code was migrated to use the native SLF4j facade and now uses the markers provided in the Category class to accentuate the different log messages and provide client code with a means to handle the different log messages (similar to the previous purpose-specific log methods).

Fixed

• Fixed a bug when adding new alphabet symbols to LStar-based learners which use a counterexample handler that requires consistency checks.

New Contributors

• @aleksander-mendoza made their first contribution in #74
• @mohbayram made their first contribution in #87