The ORM Foundation

I'm loading a very large sample population. Is there any error checking of the sample population data for compliance with any of the ring constraints? I'm particularly interested in the asymmetric/antisymmetric constraints, that should be easy to validate.

Skip,

NORMA Tutorials 5 and 6 describe the sample population features and some limited aspects of error checking.

Matt will probably have additional comments.

Ken

Wow! Thanks for the quick response. Based on my experience so far, it looks like NORMA detects and flags violations of mandatory and uniqueness contraints in the sample population data, but not more. I put an antisymmetric constraint on two roles and loaded two samples that basically said 'A is greater than B' and 'B is greater than A', but there was no sign of complaint from the verbalizer.

Thanks for your question about sample data checking in NORMA. Currently the only sample population errors we check are those listed in the Error Filter dialog. To access that dialog, click the ... button at the right of the ErrorDisplay field in the Properties sheet. Unfortunately, these do yet not include any ring constraints. Full support for ring constraint checking actually involves quite a bit of work, as we allow ring constraints over roles from different predicates that are connected via join paths. Perhaps we could support the simple cases (roles from one predicate) first. However, we want to first complete full verbalization of all constraints, including those over join paths (join versions of subset, exclusion, equality, ring etc.). We are very close to completing this long term goal. Once that is done, we can turn to other improvements such as extending the range of constraint checking for sample populations. Cheers Terry

Skip,

Terry's suggest to see what is currently checked is a good idea. That list shows that we validate mandatory constraints (simple and disjunctive) and uniqueneness constraints, although this is somewhat misleading because only the single-column uniqueness is validated right now.

Obviously, we would like to do as much constraint evaluation as possible in the tool. What is less clear is how much we can keep reasonably performant as data sets grow in size. The tool is designed primarily to hold meta-data about the model, not be a repository for the data itself. It might make more sense architecturally to generate a sample repository with enforced constraints external to the model and allow the repository itself to do the data validation. However, the full implementation of this is unfortunately a long ways off as there are a number of other higher priority items before it.

We are always interested in how you are using our tool, so if you could share more about your scenarios--such as why you need so much sample data--that might be very useful information.

-Matt