WEB SITE RELIABILITY ANALYSIS USING THE PYTHON PARSING METHOD
PDF
DOI
SLIB.UZ

Keywords

Parsing, Website, Structure, Python, Manufacturing Innovation, Industrial Innovation

How to Cite

Dmytro Gurin, Svitlana Maksymova, Vladyslav Yevsieiev, & Ahmad Alkhalaileh. (2024). WEB SITE RELIABILITY ANALYSIS USING THE PYTHON PARSING METHOD. Journal of Universal Science Research, 2(5), 113–126. Retrieved from https://universalpublishings.com/index.php/jusr/article/view/5606

Abstract

This article discusses methods for analyzing the reliability of a Web site using the parsing method based on the Python language. A generalized reliability analysis algorithm is presented that allows you to assess the quality and stability of the functioning of a website. The algorithm is based on parsing structural elements of the page, such as HTML tags, links , text blocks, and analysis of their state and contents. To implement the algorithm, a Python program was developed that is capable of automatically analyzing a selected website and identifying potential problems. The experiment showed the effectiveness and accuracy of the developed approach, which allows it to be used for systematic monitoring and increasing the reliability of websites.

PDF
DOI
SLIB.UZ

References

Omarov, M., Tikhaya, T., & Lyashenko, V. (2019). Internet marketing metrics visualization methodology for related search queries. International Journal of Advanced Trends in Computer Science and Engineering, 8(5), 2277-2281.

Dadkhah, M., Lyashenko, V. V., Deineko, Z. V., Shamshirband, S., & Jazi, M. D. (2019). Methodology of wavelet analysis in research of dynamics of phishing attacks. International Journal of Advanced Intelligence Paradigms, 12(3-4), 220-238.

Vasiurenko, O., Lyashenko, V., Baranova, V., & Deineko, Z. (2020). Spatial-Temporal Analysis the Dynamics of Changes on the Foreign Exchange Market: an Empirical Estimates from Ukraine. Journal of Asian Multicultural Research for Economy and Management Study, 1(2), 1-6.

Deineko, Zh., & et al.. (2021). Features of Database Types. International Journal of Engineering and Information Systems (IJEAIS), 5(10), 73-80.

Sotnik, S., & et al.. (2023). Development Features Web-Applications. International Journal of Academic and Applied Research (IJAAR), 7(1), 79-85.

Sotnik, S. Overview: PHP and MySQL Features for Creating Modern Web Projects/ S Sotnik, V. Manakov, V. Lyashenko //International Journal of Academic Information Systems Research (IJAISR). – 2023. – Vol. 7, Issue 1. – P. 11-17.

Lyashenko, V., Kobylin, O., & Baranchykov, Y. (2018, October). Ideology of Image Processing in Infocommunication Systems. In 2018 International Scientific-Practical Conference Problems of Infocommunications. Science and Technology (PIC S&T) (pp. 47-50). IEEE.

Z. Deineko, S. Sotnik, V. Lyashenko, “Multimedia Systems in Education,” International Journal of Academic Information Systems Research (IJAISR). 2022, vol. 6 issue 7, pp. 23-28.

Kuzomin, O., & et al.. (2020). Mobile Expert System for Diagnostic Human State in Emergency Situations. International Journal of Advanced Trends in Computer Science and Engineering, 9(4), 6485-6489.

Omarov, M., Tykha, T., & Lyashenko, V. (2019). Use of Wavelet Techniques in the Study of Internet Marketing Metrics. Eskişehir Technical University Journal of Science and Technology A-Applied Sciences and Engineering, 20, 157-163.

Stetsenko, K., & et al. (2023). Exploring BEAM Robotics for Adaptive and Energy-Efficient Solutions. Multidisciplinary Journal of Science and Technology, 3(4), 193-199.

Yevsieiev, V., & et al. (2024). Using Contouring Algorithms to Select Objects in the Robots’ Workspace. Technical Science Research In Uzbekistan, 2(2), 32-42.

Shcherbyna, V., & et al. (2023). Mobile Robot for Fires Detection Development. Journal of Universal Science Research, 1(11), 17-27.

Yevsieiev, V., & et al. (2024). Active Contours Method Implementation for Objects Selection in the Mobile Robot’s Workspace. Journal of Universal Science Research, 2(2), 135-145.

Nevliudov, I., & et al. (2023). Mobile Robot Navigation System Based on Ultrasonic Sensors. In2023 IEEE XXVIII International Seminar/Workshop on Direct and Inverse Problems of Electromagnetic and Acoustic Wave Theory (DIPED),IEEE, 1, 247-251.

Yevsieiev, V., & et al. (2024). Object Recognition and Tracking Method in the Mobile Robot’s Workspace in Real Time. Technical Science Research In Uzbekistan, 2(2), 115-124.

Basiuk, V., & et al. (2023). Mobile Robot Position Determining Using Odometry Method. Multidisciplinary Journal of Science and Technology, 3(3), 227-234.

Yevsieiev, V., & et al. (2024). The Canny Algorithm Implementation For Obtaining the Object Contour in a Mobile Robot’s Workspace in Real Time. Journal of Universal Science Research, 2(3), 7-19.

Yevsieiev, V., & et al. (2022). A robotic prosthetic a control system and a structural diagram development. Collection of scientific papers «ΛΌГOΣ», Zurich, Switzerland, 113-114.

Alfadel, M., & et al. (2023). Empirical analysis of security vulnerabilities in python packages. Empirical Software Engineering, 28(3), 59.

Utami, I. S., & Setiadi, H. (2021). Analysis the effect of website quality on user satisfaction with the WebQual 4.0 method and importance-performance analysis (IPA)(case study: SPMB Sebelas Maret University’s Website). In Journal of Physics: Conference Seriesб IOP Publishing, 1842(1), p. 012003.

Syahputri, K., & et al. (2021). Analysis of website service quality with webqual 4.0 integration method. In IOP Conference Series: Materials Science and Engineering, IOP Publishing, 1122(1), p. 012035.

Nguyen, H. T. T., & et al. (2020). Development and validation of a scale measuring hotel website service quality (HWebSQ). Tourism Management Perspectives, 35, 100697.

Gunawan, T. S., & et al. (2020). Social network analysis using python data mining. In 2020 8th international conference on cyber and IT service management (CITSM), IEEE, 1-6.

Wu, H., & et al. (2020). Data analysis and crawler application implementation based on python. In 2020 International Conference on Computer Network, Electronic and Automation (ICCNEA), IEEE, 389-393.

Nevliudov, I., Yevsieiev, V., Baker, J. H., Ahmad, M. A., & Lyashenko, V. (2020). Development of a cyber design modeling declarative Language for cyber physical production systems. J. Math. Comput. Sci., 11(1), 520-542.

Nevliudov, I., & et al.. (2020). Method of Algorithms for Cyber-Physical Production Systems Functioning Synthesis. International Journal of Emerging Trends in Engineering Research, 8(10), 7465-7473.

Abu-Jassar, A. T., Attar, H., Yevsieiev, V., Amer, A., Demska, N., Luhach, A. K., & Lyashenko, V. (2022). Electronic User Authentication Key for Access to HMI/SCADA via Unsecured Internet Networks. Computational intelligence and neuroscience, 2022, 5866922.

Al-Sherrawi, M. H., Lyashenko, V., Edaan, E. M., & Sotnik, S. (2018). Corrosion as a source of destruction in construction. International Journal of Civil Engineering and Technology, 9(5), 306-314.

Lyashenko, V. V., Deineko, Z. V., & Ahmad, M. A. Properties of wavelet coefficients of self-similar time series. In other words, 9, 16.

Nevliudov, I., Yevsieiev, V., Lyashenko, V., & Ahmad, M. A. (2021). GUI Elements and Windows Form Formalization Parameters and Events Method to Automate the Process of Additive Cyber-Design CPPS Development. Advances in Dynamical Systems and Applications, 16(2), 441-455.

Mustafa, S. K., Yevsieiev, V., Nevliudov, I., & Lyashenko, V. (2022). HMI Development Automation with GUI Elements for Object-Oriented Programming Languages Implementation. SSRG International Journal of Engineering Trends and Technology, 70(1), 139-145.

Kuzomin, O., Ahmad, M. A., Kots, H., Lyashenko, V., & Tkachenko, M. (2016). Preventing of technogenic risks in the functioning of an industrial enterprise. International Journal of Civil Engineering and Technology, 7(3), 262-270.

Al-Sharo, Y. M., Abu-Jassar, A. T., Sotnik, S., & Lyashenko, V. (2023). Generalized Procedure for Determining the Collision-Free Trajectory for a Robotic Arm. Tikrit Journal of Engineering Sciences, 30(2), 142-151.

Lyashenko, V., Laariedh, F., Ayaz, A. M., & Sotnik, S. (2021). Recognition of Voice Commands Based on Neural Network. TEM Journal: Technology, Education, Management, Informatics, 10(2), 583-591.

Maksymova, S., Matarneh, R., & Lyashenko, V. V. (2017). Software for Voice Control Robot: Example of Implementation. Open Access Library Journal, 4, e3848.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.