Accuracy info for numerical results is computed and stored during model checking. For now,
it is always the worst-case accuracy over all states for which results are computed. The
information is stored in a class prism.Accuracy, instances of which are created in a
consistent fashion using prism.AccuracyFactory. Accuracy info is stored in the
prism.Result class.
Accuracy information is generated for all 4 main engines (sparse/hybrid/MTBDD/explicit),
and attached to the Result object when model checking the filter that is wrapped around a
property (currently, just for the default "state" filter). The accuracy is printed with
the main result at the end of model checking. e.g.:
Result: 0.1666666865348816 (+/- 1.1920928955078125E-7; rel err 7.152556520395694E-7)
For now, accuracy info is generated for the majority of properties for DTMCs and MDPs
(no support yet for multi-objective model checking). For methods like value iteration,
where a guaranteed error bound is not generated, convergence information is used, but
reported as being only an estimate.
Test mode has been updated (code in prism.ResultTesting) to use the reported accuracy of
a result to check correctness against a reference result. If it is missing, or only
estimated, the old approach of using default check of 1e-5 with relative error is used.
For the explicit engine, accuracy info is stored in explicit.ModelCheckerResult, returned
by most numerical computation methods i.e. those in the explicit.ModelChecker and
explicit.IterationMethod (sub)classes. At a higher level, the accuracy info is then stored
in explicit.StateValues, when this created from ModelCheckerResult in
explicit.ProbModelChecker.
For symbolic (sparse/hybrid/MTBDD) engines, the error bound info from C++ code is stored
in a variable last_error_bound that be accessed (or reset) from prism.PrismNative, using
the methods getLastErrorBound() and resetModelCheckingInfo(). At a higher level, this is
then stored in subclasses of prism.StateValues, which are created in the
prism.*ModelChecker classes from the results of computations.
Technically, using 'plain' delete for deleting objects allocated with
new[] is undefined behaviour. In practice, this didn't appear to be a
problem.
git-svn-id: https://www.prismmodelchecker.org/svn/prism/prism/trunk@11787 bbc10eb1-c90d-0410-af57-cb519fbb1720
- better catching of memory-out errors
- improved clarity of memory usage output
- removed various memory leaks
- now consistently use new/delete, no malloc/free
git-svn-id: https://www.prismmodelchecker.org/svn/prism/prism/trunk@899 bbc10eb1-c90d-0410-af57-cb519fbb1720
Dave Parker