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• KNOWLEDGE ENGINEERING USE FOR THE INTELLECTUAL SUPPORT OF MODELS’ TRANSLATION

  M. Y. Polenov, A. O. Kurmaleev

  2021-01-19

  Abstract ▼

  In the work the problem of reuse of earlier developed software models in complex systems
  and their components, arising before researchers in case of necessity of transition to new modeling
  tools, is considered. As a solution to this problem, a Multitranslator software environment was
  developed, which made it possible to implement multilanguage translation of models' source codes
  into the required format of the target modeling environment using the created translation modules.
  Then, based on the Multitranslator, a client-server application was developed – a Distributed
  models library, which, along with the models translation function, performed the function of their
  network storage and access, providing a distributed implementation of the approach. The development
  of the approach and the Distributed models library was carried out in the direction of
  translation automation and resolving exceptional cases that occur during model translation
  caused by insufficient input data or uncertainty in model conversion decisions that occur when
  there are too many outcomes during parsing. To solve this problem, it was proposed to use an
  expert system with a knowledge base. Knowledge engineering is considered as the main process of
  synthesis of necessary knowledge for the knowledge base. The following sources of knowledge
  acquisition during the development of the expert system are proposed: the translation module of
  Multitranslator; technical documentation of input/output languages for describing models for
  translation; extended and additional publications on describing these languages; experts on languages
  for describing models for translation. The main stages of knowledge engineering are considered
  next: defining a knowledge acquisition strategy; identifying knowledge elements; creating
  a knowledge classification system; developing a detailed functional layout; pre-planning of control
  transfer processes; and defining system requirements. The results obtained will allow expanding
  the functionality of the Distributed models library when translating models using an expert
  system and efficient processing of uncertainties that arise during translation.