Abstract
The paper describes the methodology for the automation of regulatory profiles forming software certification. It has been noted that currently, the practical evaluation for software certification at the stage of regulatory profile formation is largely a manual analysis of large volumes of normative and project documentation submitted by texts in natural language that leads to a certain subjectivity of expert assessments and reduces their completeness and reliability. The degree of automation of the procedure for the formation of a regulatory profile is analyzed. The structure of the regulatory profile, the types of regulatory profiles, as well as options for its formation are given. The typical errors that can occur when automating the procedure of regulatory profiles formation are discussed. It is substantiated that it is advisable to use the ontological environment to automate the procedure for forming a regulatory profile. A model of the compositional structure of a standard text is presented. The use of a semantic integrity kernel for the user request reflecting the relationship between subject and predicate lexical units is proposed. The results of this study can be used in the development of an intelligent decision-making dialogue system for an auditor of the certification center to improve the efficiency of the auditor’s work by automating the routine process, as well as reducing the risk of making the wrong decision due to insufficient qualification of the person making the decision.
REFERENCES
Odarushchenko, O., Strjuk, O., Bulba, Y., Leontiiev, K., Ivasyuk, A., and Kharchenko, V., Fault insertion software and hardware testing for safety PLC-based system SIL certification, IEEE 9th Int. Conf. on Dependable Systems, Services and Technologies (DESSERT), Kyiv, 2018, IEEE, 2018, pp. 202–206. https://doi.org/10.1109/DESSERT.2018.8409128
Tarasyuk, O.M., Methods and tools for metric and probabilistic assessment of software quality of information-control systems of critical application, Cand. Sci. (Eng.) Dissertation, Kharkov, 2004.
Vilkomir, S.A. and Khasrchenko, V.S., The formalized models of an evaluation of a verification process of critical software, Proc. PSAM5, Osaka, 2000, vol. 4, pp. 2383–2388.
Yasko, A., Babeshko, E., and Kharchenko, V., FMEDA-based NPP I&C systems safety assessment: Toward to minimization of experts’ decisions uncertainty, Proc. 24th Int. Conf. on Nuclear Engineering (ICONE24), Charlotte, N.C., 2016, ASME, 2016, p. ICONE24-60377. https://doi.org/10.1115/ICONE24-60377
Kharchenko, V., Gordieiev, O., and Fedoseeva, A., Profiling of software requirements for the pharmaceutical enterprise manufacturing execution system, Applications of Computational Intelligence in Biomedical Technology, Bris, R., Majernik, J., Pancerz, K., and Zaitseva, E., Eds., Studies in Computational Intelligence, vol. 606, Cham: Springer, 2016, pp. 67–92. https://doi.org/10.1007/978-3-319-19147-8_4
Andrashov, A.A., Taxonomic models of profiling requirements of information and control systems of critical application, Radioelektron. Komp’yut. Sist., 2010, no. 7, pp. 104–108.
Volochiy, B., Mulyak, O., Ozirkovskyi, L., and Kharchenko, V., Automation of quantitative requirements determination to software reliability of safety critical NPP I&C systems, Second Int. Symp. on Stochastic Models in Reliability Engineering, Life Science and Operations Management (SMRLO), Beer Sheva, Israel, 2016, IEEE, 2016, pp. 337–346. https://doi.org/10.1109/SMRLO.2016.62
Butenko, Yu.I. and Semenova, E.L., Influence of linguistic features of texts of standards on information search, Filol. Nauki. Nauchn. Dokl. Vyssh. Shkoly, 2019, no. 6, pp. 29–35. https://doi.org/10.20339/PhS.6-19.029
Loukachevitch, N., and Dobrov, B., RuThes thesaurus for natural language processing, The Palgrave Handbook of Digital Russia Studies, Gritsenko, D., Wijermars, M., and Kopotev, M., Eds., Cham: Palgrave Macmillan, 2021, pp. 319–334. https://doi.org/10.1007/978-3-030-42855-6_18
Manning, C., Understanding human language: Can NLP and deep learning help?, SIGIR ’16: Proc. 39th Int. ACM SIGIR Conf. on Research and Development in Information Retrieval, Pisa, Italy, 2016, New York: Association for Computing Machinery, 2016, p. 1. https://doi.org/10.1145/2911451.2926732
Tata, S., Potti, N., Wendt, J. B., Costa, L. B., Najork, M., and Gunel, B. 2021. Glean: Structured extractions from templatic documents, Proc. VLDB Endowment, 2021, vol. 14, no. 6, pp. 997–1005. https://doi.org/10.14778/3447689.3447703
Skatov D.S., Erekhinskaya T.N., and Okat’ev V.V., Models and methods of analysis of hierarchically structured texts, Komp’yuternaya lingvistika i intellektual’nye tekhnologii: Po materialam ezhegodnoj Mezhdunarodnoj konferencii Dialog 2009 (Computer Linguistics and Intelligent Technologies: Proc. Ann. Int. Conf. Dialogue 2009), Bekasovo, Moscow oblast, 2009, Moscow, 2009, vol. 5, pp. 458–464.
Hovorushchenko, T. and Pomorova, O., Information technology of evaluating the sufficiency of information on quality in the software requirements specifications, CEUR Workshop Proc., 2018, vol. 2104, pp. 555–570.
Lipaev, V.V., Nadezhnost’ i funktsional’naya bezopasnost’ kompleksov programm real’nogo vremeni (Reliability and functional safety of real-time software complexes), Moscow: Inst. Sistemnogo Programmirovaniya Ross. Akad. Nauk, 2013.
Butenko, I.I., Ontology approach to normative profiles forming at critical software certification, AIP Conf. Proc., 2019, vol. 2171, p. 110002. https://doi.org/10.1063/1.5133236
Hovorushchenko, T. and Pavlova, O., Evaluating the software requirements specifications using ontology-based intelligent agent, IEEE 13th Int. Sci. and Tech. Conf. on Computer Sciences and Information Technologies (CSIT), Lviv, Ukraine, 2018, IEEE, 2018, pp. 215–218. https://doi.org/10.1109/STC-CSIT.2018.8526730
Butenko, Yu.I., Model of the text of the standard in the information search in the collection of documents of the regulatory framework, Vestn. Komp’yut. Inf. Tekhnol., 2020, vol. 17, no. 11, pp. 23–32. https://doi.org/10.14489/vkit.2020.11.pp.023-032
Wang, Y., Yin, F., Liu, J., and Tosato, M., Automatic construction of domain sentiment lexicon for semantic disambiguation, Multimedia Tools Appl., 2020, vol. 79, pp. 22355–22373. https://doi.org/10.1007/s11042-020-09030-1
Loukachevitch, N. and Dobrov, B., Ontologies for natural language processing: Case of Russian, Third Int. Conf. on Computational Linguistics, Sofia, Bulgaria, 2018, pp. 93–103.
Gavrilova, T.A. and Leshcheva, I.A., Ontology design and individual cognitive peculiarities: A pilot study, Expert Syst. Appl., 2015, vol. 42, no. 8, pp. 3883–3892. https://doi.org/10.1016/j.eswa.2015.01.008
Globa, L., Kovalskyi, M., and Stryzhak, O., Increasing web services discovery relevancy in the multi-ontological environment, Soft Computing in Computer and Information Science, Wiliński, A., Fray, I., and Pejaś, J., Eds., Advances in Intelligent and Soft Computing, vol. 342, Cham: Springer, 2015, pp. 335–344. https://doi.org/10.1007/978-3-319-15147-2_28
Smirnov, A., Levashova, T., and Shilov, N., Patterns for context-based knowledge fusion in decision support, Inf. Fusion, 2015, vol. 21, pp. 114–129. https://doi.org/10.1016/j.inffus.2013.10.010
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
The author declares that she has no conflicts of interest.
Additional information
Translated by L. Solovyova
About this article
Cite this article
Butenko, I.I. Ontology Application in Automating Regulatory Profile Forming for Software Certification. Sci. Tech. Inf. Proc. 49, 408–415 (2022). https://doi.org/10.3103/S0147688222060028
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.3103/S0147688222060028