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Run-Time Class Generation: Algorithm for Decomposition of Homogeneous Classes

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Information and Software Technologies (ICIST 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1283))

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Abstract

An ability to change the internal structure and to correct the behaviour adapting to such change of the working environment as heterogeneity of data is an important feature of modern knowledge-based systems. One of the approaches for achieving the goal is to develop tools for dynamic analysis, modification and generation of knowledge structures and program codes as structural parts of intelligent systems. Therefore, analysis of the class structure in object-oriented programming as well as in object-oriented knowledge representation is presented in the paper. The main result of the paper is developed algorithm for dynamic creation of new classes of objects via decomposition of homogeneous classes of objects to the subclasses. The algorithm performs the decomposition of homogeneous classes of objects creating the set of their semantically correct subclasses via solving corresponding constraint satisfaction problem. It can be adapted and integrated into particular knowledge representation model or programming language.

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Authors and Affiliations

  1. Taras Shevchenko National University of Kyiv, Kyiv, 03022, Ukraine

    Dmytro O. Terletskyi

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  1. Dmytro O. Terletskyi
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Correspondence to Dmytro O. Terletskyi .

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Editors and Affiliations

  1. Kaunas University of Technology, Kaunas, Lithuania

    Audrius Lopata

  2. Kaunas University of Technology, Kaunas, Lithuania

    Rita Butkienė

  3. Kaunas University of Technology, Kaunas, Lithuania

    Daina Gudonienė

  4. Kaunas University of Technology, Kaunas, Lithuania

    Vilma Sukackė

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Terletskyi, D.O. (2020). Run-Time Class Generation: Algorithm for Decomposition of Homogeneous Classes. In: Lopata, A., Butkienė, R., Gudonienė, D., Sukackė, V. (eds) Information and Software Technologies. ICIST 2020. Communications in Computer and Information Science, vol 1283. Springer, Cham. https://doi.org/10.1007/978-3-030-59506-7_20

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  • DOI: https://doi.org/10.1007/978-3-030-59506-7_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-59505-0

  • Online ISBN: 978-3-030-59506-7

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