Debugging procedure of the replica class errors in the production knowledge bases

Abstract

The problem of detecting errors in the production knowledge bases of knowledge - oriented information systems that arise at the stage of formation of the knowledge base by experts is considered. It was determined that such errors related to the conflicting opinions of experts and/or limited (imperfect) description of the subject area. There was analyzed approaches for their debugging. Ways to improve existing approaches for debugging static replica errors was shown. Possible ways of applying the obtained solutions to debug errors "contradiction", "redundancy", "incompleteness" was shown. Solutions for expanding the formalized definition of static error of the production network, considering the requirements for the accuracy of information was suggested. The issues of the influence of errors of the “replica” class on the results of derivation according to the rules of the production knowledge base was considered. The possibility of applying the methods of graph theory to solve the problem of error reduction of the "replica" class is proved. An algorithmic structure for detecting and debugging errors of this class has been developed. It allows, in contrast to existing solutions, to detect duplicate vertices at each rank of the graph to which the production knowledge base is reduced. Software implementation for detection and debugging of static errors of incomplete, partial, and complete duplication was developed, using recursion, which allows to reduce the requirements for preparing an array of input data for processing. The obtained solutions meet the requirements of DSTU ISO / IEC 9126, DSTU ISO / IEC 14598 and consider the requirements of the series of standards Software Quality Requirements and Evaluation as the values of the vertices of the graph of the event tree. During problem solving process specifics of the LMS operation are considered, first of all formalizing possibilities in the various aspects of knowledge (aletic, dissociative, causal, diontic) and ensuring a given level of efficiency in finding solutions.