We present a system that computes for a query that may be incomplete, complete approximations from above and from below. We assume a setting where queries are posed over a partially complete database, that is, a database that is generally incomplete, but is known to contain complete information about specific aspects of its application domain. Which parts are complete, is described by a set of so-called table-completeness statements. Previous work led to a theoretical framework and an implementation that allowed one to determine whether in such a scenario a given conjunctive query is guaranteed to return a complete set of answers or not. With the present demonstrator we show how to reformulate the original query in such a way that answers are guaranteed to be complete. If there exists a more general complete query, there is a unique most specific one, which we find. If there exists a more specific complete query, there may even be infinitely many. In this case, we find the least specific specializations whose size is bounded by a threshold provided by the user. Generalizations are computed by a fixpoint iteration, employing an answer set programming engine. Specializations are found leveraging unification from logic programming.

Specification models recovered from existing software applications can support developers in comprehending and checking the applications during maintenance and evolution operations. Often, in fact, a huge amount of business knowledge is embedded in the application implementation while documentation is not available or not aligned with the actual software implementation. In order to (re)acquire and preserve the business knowledge, specifications recovery techniques are adopted. In this paper we present reBPMN, a tool that recovers business process models from execution traces of target applications. It recovers the process exposed by means of Web interfaces and it applies a multi-objective process reduction technique, which minimizes at the same time process complexity, non-conformances, and loss of business content. This allows us to obtain processes having high readability by decreasing their structural complexity, while preserving the completeness of the described business and domain-specific information. A case study shows the effectiveness of reBPMN in recovering readable and business-meaningful processes.