In this article the relevance of using test methods of pattern recognition while developing intelligent systems for decision making support for various problem areas is discussed. The advantage of fault-tolerant diagnostic tests used in intelligent systems is shown, namely, a tool for registering and processing different kinds of errors in databases and knowledge bases. The results of testing two algorithms for constructing the nonredundant matrix of implications are compared; the technical particulars of program implementation are discussed such as synchronization means, test environment, test-program structure, and bottlenecks of program implementation; methods of their elimination, and further development of parallel algorithms.