Knowledge Based Automated Software Engineering

Katalina Grigorova · Ivan Stanev

2012-ж. мар. · Cambridge Scholars Publishing

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The process of developing big information systems is less effective and more resource consuming than software developers expect. The most widely disseminated software engineering methods and tools applied through the life cycle of this process are characterised with a low level of process automation, insufficient component reusability and dissatisfactory final product flexibility.

The efficiency of the software development process can be improved with the application of hi-tech IT instruments as: (1) non-formal business model specifications, (2) automated verification and modification of the non-formal specifications related to predefined standardised knowledge bases both for the domain and IT areas, (3) automated generation of the final software product from the verified business model, and (4) incorporation of components set for real time monitoring and tuning within the generated software.

This book presents the authors’ views on Knowledge Based Automated Software Engineering (KBASE). It involves the domain scope, the implemented research methods, tools and applications. The KBASE products presented in the book are addressed to the needs of scientists, practitioners and students working in the areas of software engineering, computer science, knowledge representation, artificial intelligence, manufacturing engineering, and education.

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Автор жөнүндө

Ivan Stanev, from the Department of Informatics and Information Technologies at the University of Ruse, is a Researcher in Software Engineering and Automated Programming. He is a manager of two Bulgarian eGovernment programs, and a leader of software teams working on the development of knowledge based tools for automated programming.

Prof. Katalina Grigorova, from the Department of Informatics and Information Technologies at the University of Ruse, is a Researcher in Business Architectures Modelling and Data Bases. She is a leader of research projects on Knowledge Based Business Process Generators and a winner of the IBM Faculty Award (2005).

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