Multidisciplinary Approaches to Quality Assurance of Technological Solutions: Testing, Security, and Energy Efficiency

Authors

  • Iryna Burdeinyk-Kernyts'ka National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Ukraine

DOI:

https://doi.org/10.5281/zenodo.15482124

Keywords:

multidisciplinary, technological solutions, quality assurance, software testing, energy efficiency

Abstract

This study explores multidisciplinary approaches to ensuring the quality of technological solutions, focusing on testing, security, and energy efficiency. By integrating innovative methods such as virtual reality (VR) for software testing, machine learning for resource forecasting, and bio-identification for data protection, the research demonstrates the effectiveness of cross-disciplinary strategies in modern technological environments. The paper analyzes current trends and challenges in software testing, highlights the importance of adaptive learning for technical education, and examines the impact of biodiesel fuels on engine efficiency and environmental performance. The findings underscore the value of combining diverse scientific perspectives to achieve robust and sustainable technological outcomes.

References

Hunko, I., Muliarevych, O., Trishchuk, R., Zybin, S., & Halachev, P. (2024). The role of virtual reality in improving software testing methods and tools. Journal of Theoretical and Applied Information Technology, 102(11), 4723-4734. https://www.jatit.org/volumes/Vol102No11/6Vol102No11.pdf

Hunko, I. (2023). Software testing in 2023: New trends and challenges. Herald of Kyiv Institute of Business and Technology, 49(1-2), 25-36. https://doi.org/10.37203/kibit.2023.49.03

Drofa, D. (2024). Using Machine Learning to Forecast Resources in Long-Term Business Projects. Horizons of Innovation: Conference on Multidisciplinary Trends in Science 2024 (pp. 395-398). Futurity Research Publishing. https://futurity-publishing.com/wp-content/uploads/2025/03/Drofa-D.-2024.pdf

Drofa, D. (2023). Integrate Bio-Identification to Strengthen Data Protection in Multi-Tenant Cloud Systems. Global Innovations and Collaborative Solutions in Contemporary Science (pp. 444-447). Futurity Research Publishing. https://futurity-publishing.com/wp-content/uploads/2025/03/International_scientific_conference-.pdf#page=444

Pavlovskyi, M. (2024). The Improvement of Fuel Efficiency and Environmental Characteristics of Diesel Engine by Using Biodiesel Fuels. In: Boichenko, S., Zaporozhets, A., Yakovlieva, A., Shkilniuk, I. (eds) Modern Technologies in Energy and Transport. Studies in Systems, Decision and Control, vol 510. Springer, Cham. https://doi.org/10.1007/978-3-031-44351-0_4

Ivanchenko, K. (2022). The Role of Adaptive Learning in the Training of Electronics and Automation Engineers. Futurity Education, 2(1), 86–105. https://doi.org/10.57125/FED.2022.25.03.8

Modernizing Learning – Модернізація освіти (2022). Інформаційні технології та новітні платформи для забезпечення якості освіти. https://www.adlnet.gov/assets/uploads/Modernizing%20Learning%20-%20%D0%9C%D0%BE%D0%B4%D0%B5%D1%80%D0%BD%D1%96%D0%B7%D0%B0%D1%86%D1%96%D1%8F%20%D0%BE%D1%81%D0%B2%D1%96%D1%82%D0%B8.pdf

Модернізація вищої освіти та забезпечення якості освітньої діяльності в умовах європейської інтеграції (2024). Держ. біотехнологічний ун-т. – Харків, 2024. https://biotechuniv.edu.ua/wp-content/uploads/2024/10/conf-18-10-24-materialy.pdf

Published

2024-11-01

Issue

Section

Computer science, computing and automation