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In this paper we present LEARN-SQL, a system conforming to the IMS QTI specification that allows on-line learning and assessment of students on SQL skills in an automatic, interactive, informative, scalable and extensible manner.

Abstract:The validation and the verification of conceptual schemas have attracted a lot of interest during the last years, and several tools have been developed to automate this process as much as possible. This is achieved, in general, by assessing whether the schema satisfies different kinds of desirable properties which ensure that the schema is correct. In this paper we describe AuRUS, a tool we have developed to analyze UML/OCL conceptual schemas and to explain their (in)correctness. When a property is satisfied, AuRUS provides a sample instantiation of the schema showing a particular situation where the property holds. When it is not, AuRUS provides an explanation for such unsatisfiability, i.e., a set of integrity constraints which is in contradiction with the property.

We extend here the Internal Events Method for change computation. This method derives a set of rules that incrementally compute the changes induced by an update, taking into account rwt only the update, but also the concept of event and the knowledge provided by the primary key integrity constraints. In this paper we further develop this idea by considering four additional integrity constraints: inclusion dependencies, exclusion dependencies, alternate keys and referential integrity constraints. We show that the knowledge provided by these integrity constraints allows us to save redundant checks and in some cases to remove whole rules. Thus, we obtain a signijicant improvement in performance. To the best of our knowledge there is no method for change computation with this capability

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Abstract. We propose a new method for database schema validation that provides an explanation when it determines that a certain desirable property of a database schema does not hold. Explanations are required to give the designer a hint about the changes of the schema that are needed to fix the problem identified. Our method is an extension of the CQC method, which has been shown successful for testing such properties, and its contribution is twofold: Firstly, it is the first method that offers an explanation when the schema is not adequately defined. Secondly, the extension proposed here provides a significant efficiency improvement as far as the run-time performance of the method is concerned.

An important amount of research has been devoted to conceptual model validation, that is, to check whether a conceptual model correctly and adequately describes the users' intended needs and requirements. In this paper we present a new approach to model validation. We define a set of desirable properties that a conceptual model should satisfy and we show how the accomplishment of all these properties can be checked in a uniform way by means of planning. Our approach is independent of any particular planning method and it extends the facilities of the methods developed so far.