Informatica

Quantum computing has come to stay in our lives. Companies are investing billions of dollars in it because of the potential benefits that it can achieve, providing promising applications in almost every business sector. Although quantum computing is evolving at an exponential rate, the development of tools, techniques, or frameworks for the evolution of current information systems towards quantum software systems is still proving to be a challenge. This research contributes to the evolution of current information systems towards hybrid information systems (combining the classical and quantum computing paradigm). We propose a software modernization process, by following model-driven engineering principles, adapted to the quantum paradigm, based on modified versions of standards for reverse engineering of classical, quantum software assets, and for the design of the target system. In particular, this paper focuses on the restructuring transformation from KDM to UML models, where KDM models have been generated from Q# code. This proposal has been validated through a case study involving 17 programmes. The results obtained show optimistic values regarding the complexity of the UML models generated, their expressiveness and scalability. The main implication of this research is that UML models can indeed help the software evolution of/toward hybrid information systems.

The emergence of the Semantic Web have revived the interest in knowledge engineering and ontologies. Different paradigms often share challenges and solutions, and can complement and mutually improve each other. This paper presents a simple and agile integration of ontologies and programming on a small scale, and in a down-to-Earth manner by incorporating the ontology paradigm into a mainstream programming environment. The approach is based on metaprogramming, which has been used to internalize the ontology modeling paradigm into the Clojure language. The resulting DSL, Magic Potion, is implemented in Cojure and blends ontology, functional, object-oriented and concurrent paradigms, which is suitable for general-purpose domain modeling, from technology enhanced learning to business.

The main purpose of the paper is to compare ontology‐based reuse techniques in domain engineering and enterprise engineering. It discusses attempts to combine classical domain engineering techniques with ontology‐based techniques as well as the attempts to incorporate ontologies in enterprise engineering process and demonstrates that, on the one hand, both approaches still are not mature enough to solve practical reuse problems and, on the other hand, both propose ideas that can be used to develop more mature approach. The main contribution of the paper is the detail description of the problems of ontology‐based reuse of enterprise engineering assets.

This paper presents the framework for well-understood domain analysis as a decisive stage for the successive process of domain-specific software tools building. Specific features of the well-understood domain analysis are formulated. Initial model of the tools to be built and the analysis process are described. Analysis is performed with the reusability concept in mind and as a result essential domain knowledge is extracted. The latter is defined by a term “domain knowledge template”.