Goran Banjac

The paper presents SpeeD - the first online speech-based tool for automated database design. SpeeD enables automatic derivation of conceptual database models from offline (previously recorded) speech, as well as from online (real-time recorded) speech, whereby several different natural languages are supported. Once upon conceptual design is finished, SpeeD enables automated subsequent steps of forward database engineering for several contemporary database management systems.

The article presents an approach to the automatic derivation of conceptual database models from heterogeneous source artifacts. The approach is based on the integration of conceptual database models that are derived from source artifacts of one single type by already existing tools, whereby those models possess limited certainty given their limited completeness and correctness. The uncertainty of the automatically derived models from specific source artifacts is expressed and managed through the effectiveness measure of the generation of specific concepts of the input conceptual database models. The approach is implemented by the DBomnia tool ? the first online web-based tool enabling automatic derivation of conceptual database models from heterogeneous source artifacts (business process models and textual specifications). DBomnia employs other pre-existing tools to derive conceptual models from sources of the same type and then integrates those models. The case study-based evaluation proves that the implemented approach enables effective automatic derivation of the conceptual database model from a set of heterogeneous source artifacts. Moreover, the automatic derivation of the conceptual database model from a set of heterogeneous source artifacts is more effective than each independent automatic derivation of the conceptual database model from sources of one single type only.

The article presents an approach aimed at automatically deriving the initial conceptual database model from a set of business process models. The approach proposes the incremental synthesis of the target model by iteratively composing the partial conceptual database models that are derived from the models contained in the source set. The approach is implemented by the AMADEOS tool, which is the first online web-based tool enabling the automatic derivation of the conceptual database model from a set of business process models. The experimental evaluation proves that the implemented approach enables effective automatic derivation of the initial conceptual database model.

Existing approaches to business process model-driven synthesis of data models are characterized by a direct synthesis of a target model based on source models represented by concrete notations, where the synthesis is supported by monolithic (semi)automatic transformation programs. This article presents an approach to automated two-phase business process model-driven synthesis of conceptual database models. It is based on the introduction of a domain specific language (DSL) as an intermediate layer between different source notations and the target notation, which splits the synthesis into two phases: (i) automatic extraction of specific concepts from the source model and their DSL-based representation, and (ii) automated generation of the target model based on the DSL-based representation of the extracted concepts. The proposed approach enables development of modular transformation tools for automatic synthesis of the target model based on business process models represented by different concrete notations. In this article we present an online generator, which implements the proposed approach. The generator is implemented as a web-based, service-oriented tool, which enables automatic generation of the initial conceptual database model represented by the UML class diagram, based on business models represented by two concrete notations.