/src/main/java/net/finmath/montecarlo/automaticdifferentiation/backward/alternative/RandomVariableDifferentiableAADPathwise.java
independents.remove( getID( ) , getOperatorTreeNode( ) ) ;
independents.put ( getID ( ) , getOperatorTreeNode ( ) ) ;
} @Override public Map<Long, RandomVariable> getGradient(final Set<Long> independentIDs) { final Map<Long, RandomVariable> derivatives = new HashMap<>(); derivatives.put(getID(), new RandomVariableFromDoubleArray(1.0)); final TreeMap<Long, OperatorTreeNode> independents = new TreeMap<>(); <extra_id_0> while(independents.size() > 0) { final Map.Entry<Long, OperatorTreeNode> independentEntry = independents.lastEntry(); final Long id = independentEntry.getKey(); final OperatorTreeNode independent = independentEntry.getValue(); final List<OperatorTreeNode> arguments = independent.arguments; if(arguments != null && arguments.size() > 0) {