АНАЛІЗ ЕФЕКТИВНОСТІ ТЕХНОЛОГІЙ ТЕСТУВАННЯ ПРОГРАМНОГО ЗАБЕЗПЕЧЕННЯ ІНФОРМАЦІЙНИХ СИСТЕМ

Natalia Brynza; Kyrylo Lobanov; Natalia Brynza; Kyrylo Lobanov

doi:10.30888/2663-5712.2026-35-01-043

Authors

Natalia Brynza Simon Kuznets Kharkiv National University of Economics, Kharkiv National University of Radio Electronics https://orcid.org/0000-0002-0229-2874
Kyrylo Lobanov Kharkiv National University of Radio Electronics https://orcid.org/0009-0000-1986-304X

DOI:

https://doi.org/10.30888/2663-5712.2026-35-01-043

Keywords:

testing, software, modeling, automated testing, information technologies, intelligent testing, analysis, efficiency, manual testing

Abstract

The purpose of this work is to analyze the effectiveness of software testing. Modern approaches to software testing are analyzed, and their advantages, limitations, and areas of practical application are identified. To conduct a computational experiment,

References

Software Testing Process Guide: Types of Testing, Stages, and Best Practices. URL: https://testfort.com/blog/software-qa-testing-process-overview-types-and-process-stages.

Chatzipetrou, E., & Varvaropoulos, K. (2024). Managerial Digitalisation Cost in the Hotel Sector: The Case of Northern Greece. Administrative Sciences, 14(3), 52.

Jorgensen P. C. (2014). Software Testing: A Craftsman's Approach (4th ed.). Boca Raton: Auerbach Pub. 527 p.

Going Deeper into the Page Object Model. URL: https://medium.com/@blakenorrish/going-deeper-into-the-page-object-model-4aee634d9c98.

Дуда, О., Шаклеіна, І., & Лучкевич, М. (2025). Підвищення ефективності devops за рахунок використання штучного інтелекту та машинного навчання. Herald of Khmelnytskyi National University. Technical Sciences, 351(3.1), pp. 143-149. https://doi.org/10.31891/2307-5732-2025-351-17.

Khankhoje R. (2023). Quantifying Success: Measuring ROI in Test Automation. Journal of Technology and Systems, 5, pp. 1–14. https://doi.org/10.47941/jts.1512.

Haug, Michael, Eric W. Olsen, and Luisa Consolini, eds. Software quality approaches: testing, verification, and validation: software best practice 1. Vol. 1. Springer Science & Business Media, 2001.

Zaidi, Hijab Zehra, et al. "Machine Learning Approaches for Software Defect Prediction." Applied Computational Intelligence and Soft Computing 2025.1 (2025): 7933078. https://doi.org/10.1155/acis/7933078.

ANALYSIS OF THE EFFECTIVENESS OF SOFTWARE TESTING TECHNOLOGIES FOR INFORMATION SYSTEMS

Authors

DOI:

Keywords:

Abstract

References

Downloads

Published

How to Cite

Issue

Section

License

Language