// // Copyright (C) 2006 United States Government as represented by the // Administrator of the National Aeronautics and Space Administration // (NASA). All Rights Reserved. // // This software is distributed under the NASA Open Source Agreement // (NOSA), version 1.3. The NOSA has been approved by the Open Source // Initiative. See the file NOSA-1.3-JPF at the top of the distribution // directory tree for the complete NOSA document. // // THE SUBJECT SOFTWARE IS PROVIDED "AS IS" WITHOUT ANY WARRANTY OF ANY // KIND, EITHER EXPRESSED, IMPLIED, OR STATUTORY, INCLUDING, BUT NOT // LIMITED TO, ANY WARRANTY THAT THE SUBJECT SOFTWARE WILL CONFORM TO // SPECIFICATIONS, ANY IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR // A PARTICULAR PURPOSE, OR FREEDOM FROM INFRINGEMENT, ANY WARRANTY THAT // THE SUBJECT SOFTWARE WILL BE ERROR FREE, OR ANY WARRANTY THAT // DOCUMENTATION, IF PROVIDED, WILL CONFORM TO THE SUBJECT SOFTWARE. // package gov.nasa.jpf.search.heuristic; import java.util.ArrayList; import java.util.List; import gov.nasa.jpf.Config; import gov.nasa.jpf.search.Search; import gov.nasa.jpf.vm.VM; /** * a search strategy class that computes all immediate successors of a given * state, puts them into a priority queue (the priority is provided by a * Heuristic strategy object), and processes states in the sequence of * highest priorities. Note that the queue can be search-global, i.e. we might hop * between search levels. */ public abstract class HeuristicSearch extends Search { static final String DEFAULT_HEURISTIC_PACKAGE = "gov.nasa.jpf.search.heuristic."; protected HeuristicState parentState; protected List<HeuristicState> childStates; protected boolean isPathSensitive = false; /* * do we use A* adaptation of state priorities, i.e. have a * distance + cost heuristic (in this context, we just use the * path length as the "distance") */ protected boolean useAstar; /* * a beam search is a HeuristicSearch with a state queue that is reset at each * search level (i.e. it doesn't hop between search levels when fetching the * next state from the queue) */ protected boolean isBeamSearch; public HeuristicSearch (Config config, VM vm) { super(config, vm); useAstar = config.getBoolean("search.heuristic.astar"); isBeamSearch = config.getBoolean("search.heuristic.beam_search"); } // add the current state to the queue protected abstract HeuristicState queueCurrentState (); // return the next queued state, which becomes the new parentState // implementors can also reset or modify the queue protected abstract HeuristicState getNextQueuedState (); public abstract int getQueueSize(); public abstract boolean isQueueLimitReached(); public HeuristicState getParentState() { return parentState; } public List<HeuristicState> getChildStates() { return childStates; } public void setPathSensitive (boolean isPathSensitive) { this.isPathSensitive = isPathSensitive; } void backtrackToParent () { backtrack(); depth--; notifyStateBacktracked(); } /* * generate the set of all child states for the current parent state * * overriding methods can use the return value to determine if they * have to process the childStates, e.g. to compute priorities * that require the whole set * * @returns false if this is cut short by a property termination or * explicit termination request */ protected boolean generateChildren () { childStates = new ArrayList<HeuristicState>(); while (!done) { if (!forward()) { notifyStateProcessed(); return true; } depth++; notifyStateAdvanced(); if (currentError != null){ notifyPropertyViolated(); if (hasPropertyTermination()) { return false; } // note that we don't store the error state anymore, which means we // might encounter it along different paths. However, this is probably // what we want for search.multiple_errors. } else { if (!isEndState() && !isIgnoredState()) { boolean isNewState = isNewState(); if (isNewState && depth >= depthLimit) { // we can't do this before we actually generated the VM child state // since we don't want to report DEPTH_CONSTRAINTs for parents // that have only visited or end state children notifySearchConstraintHit("depth limit reached: " + depthLimit); } else if (isNewState || isPathSensitive) { if (isQueueLimitReached()) { notifySearchConstraintHit("queue limit reached: " + getQueueSize()); } HeuristicState newHState = queueCurrentState(); if (newHState != null) { childStates.add(newHState); notifyStateStored(); } } } else { // end state or ignored transition } } backtrackToParent(); } return false; } private void restoreState (HeuristicState hState) { vm.restoreState(hState.getVMState()); // note we have to query the depth from the VM because the state is taken from the queue // and we have no idea when it was entered there depth = vm.getPathLength(); notifyStateRestored(); } public void search () { queueCurrentState(); notifyStateStored(); // kind of stupid, but we need to get it out of the queue, and we // don't have to restore it since it's the first one parentState = getNextQueuedState(); done = false; notifySearchStarted(); if (!hasPropertyTermination()) { generateChildren(); while (!done && (parentState = getNextQueuedState()) != null) { restoreState(parentState); generateChildren(); } } notifySearchFinished(); } public boolean supportsBacktrack () { // we don't do multi-level backtracks, but automatically do backtrackToParent() // after each child state generation return false; } }