An introduction to the study of quality assurance methods is essential to understand the development of complex and reliable software. Nevertheless, the modern software industry requires the earliest possible launch of a product to the market, and the methods of formal specification and verification of programs do not find much interest among the broad mass of future programmers. In this article, the author proposes to organize a dedicated discipline and conduct seamless training in testing, test-driven development and formal verification using various methods for writing program specifications and using software tools for program checking. The purpose of discussing discipline is to redefine the attitude of future developers towards software quality, its specification and automatic checking. Within the framework of this article, the author considers his own discipline, which combines two courses -- software testing and formal verification. The proposed approach of teaching is primarily practice-oriented and includes teamwork. In accordance with the current curriculum, the discipline is held in the last semester for undergraduate students (4th course). The material of the article is based on the author's five-year experience of teaching the subject to students of the Software Engineering specialty. The article offers rather voluminous and descriptive examples of specifications and programs in model languages.

This work is dedicated to an Estonian scientist in Computer Science, Enn Tyugu (1935–2020). The article focuses on two significant events in his biography: deportation in 1941 and his interest in computers. The topic appears relevant since in the post-Soviet (the same as in the USSR) environment research on the life paths of the representatives of deported nations was scarce; we know little about their life and the life of their progeny. We will not elaborate on the issue of access of science and technology specialists (technocrats) to political power and administrative decision-making and will limit our interest to their socio-professional identities.

The work is devoted to the study of the problems of ontology automating creation of scientific subject areas using methods of automatic analysis of texts in natural language. The aim of the work is developing methods for automatic generation of lexico-syntactic patterns for extracting information and ontology augmentation based on the analysis of content ontology design patterns for scientific knowledge areas developed within the framework of the Semantic Web concept. Ontology design patterns are a structured description of top-level concepts in terms of classes, attributes and relationships, and also include competency questions in natural language that serve for understanding and correctly interpretation the properties and relationships of the concept by users. The article proposes an approach to the generation of lexico-syntactic patterns based on questions of competence assessment. The process of generating lexico-syntactic patterns includes the generation of a subject dictionary, the extraction of ontology entities and the formation of a pattern structure based on the Data Property and Object Property, and the generation of semantic, grammatical and positional constraints. Competency questions are used to identify grammatical and positional restrictions necessary for search for ontological relationships in texts. The ontology "Decision support in weakly formalized areas" and the corpus of scientific texts of the same subject area were used in the experiment. During the experiment, the following results were obtained: the degree of ambiguity of the generated templates - 1.5, the F1-measure of assessing the quality of the search for attributes and relations of objects - the F1-measure was 0.77 for attributes and 0.55 for relations, respectively. Comparison of the results obtained for patterns without grammatical restrictions and the results obtained for patterns with grammatical restrictions showed that the addition of restrictions significantly improves the quality of extraction of ontology objects.