Abstract
This study compares two automation testing tools, Robot Framework and Cypress, applied to e-commerce websites. The testing procedure is based on predefined test case flows utilizing the Black Box Testing method, which focuses exclusively on functional validation according to requirement specifications, without reference to backend systems or source code. The research aims to evaluate the efficiency and effectiveness of both tools in executing identical test scenarios and to assess user responses concerning website access speed. Robot Framework, recognized for its keyword-driven testing approach, is compared with Cypress, a JavaScript-based end-to-end testing framework. The findings indicate that Cypress outperforms Robot Framework, particularly regarding execution speed and automated report generation. Cypress’s modern architecture and real-time interaction capabilities contribute to faster and more stable test execution. Conversely, while Robot Framework offers significant flexibility and extensibility, its performance is comparatively slower in this context. User feedback suggests that the Bhinneka, Gramedia, and Uniqlo websites are generally responsive and user-friendly; however, Uniqlo is notably preferred due to its accurate stock information and efficient delivery services.
References
Alok Chakravarthy, N., & Padma, U. (2023). A Comprehensive Study of Automation Using a WebApp Tool for Robot Framework. In Intelligent Cyber Physical Systems and Internet of Things (1st ed., Vol. 2, pp. 577–586). ICoICI. https://doi.org/10.1007/978-3-031-18497-0_43
Arora, T., Chirla, S. R., Singla, N., & Gupta, L. (2023). Product Packaging by E-commerce Platforms: Impact of COVID-19 and Proposal for Circular Model to Reduce the Demand of Virgin Packaging. Circular Economy and Sustainability, 3(3), 1255–1273. https://doi.org/10.1007/s43615-022-00231-4
Batni, N. S., & Shetty, J. (2018). A Comprehensive Study on Automation using Robot Framework. International Journal of Science and Research, 9(7), 1033–1036. https://www.ijsr.net/getabstract.php?paperid=SR20710144623
Byrd, K., Fan, A., Her, E., Liu, Y., Almanza, B., & Leitch, S. (2021). Robot vs human: expectations, performances and gaps in off-premise restaurant service modes. International Journal of Contemporary Hospitality Management, 33(11), 3996–4016. https://doi.org/10.1108/IJCHM-07-2020-0721
Capitaine, L., Genuer, R., & Thiébaut, R. (2021). Random forests for high-dimensional longitudinal data. Statistical Methods in Medical Research, 30(1), 166–184. https://doi.org/10.1177/0962280220946080
Chen, H., Tian, G., Lu, F., & Liu, G. (2016). A hybrid cloud robot framework based on intelligent space. Proceedings of the World Congress on Intelligent Control and Automation (WCICA), 2016-September, 2996–3001. https://doi.org/10.1109/WCICA.2016.7578487
Ebert, C. (2011). Global Software and IT (1st ed.). Wiley. https://doi.org/10.1002/9781118135105
Firmansyah, M. D., & Herman, H. (2023). Perancangan Web E- Commerce Berbasis Website pada Toko Ida Shoes. Journal of Information System and Technology, 4(1), 361–372. https://doi.org/10.37253/joint.v4i1.6330
Goyal, S., Sergi, B. S., & Esposito, M. (2019). Literature review of emerging trends and future directions of e-commerce in global business landscape. World Review of Entrepreneurship, Management and Sustainable Development, 15(1/2), 226. https://doi.org/10.1504/WREMSD.2019.098454
Hashimoto, A., Chiu, C. W., Onda, Y., Tateishi, M., Tsuruta, K., & Gomi, T. (2023). Satellite remote sensing model for estimating canopy transpiration in cypress plantation using in situ sap flow observations and forest inventory. ISPRS Journal of Photogrammetry and Remote Sensing, 206, 258–272. https://doi.org/10.1016/j.isprsjprs.2023.11.009
Hassanvand, F., Nassiri-Mofakham, F., & Fujita, K. (2024). Automated Negotiation Agents for Modeling Single-Peaked Bidders: An Experimental Comparison. Information, 15(8), 508. https://doi.org/10.3390/info15080508
Hussein, M., Nouacer, R., Radermacher, A., Puccetti, A., Gaston, C., & Rapin, N. (2018). An end-to-end framework for safe software development. Microprocessors and Microsystems, 62, 41–49. https://doi.org/10.1016/j.micpro.2018.07.004
Jagat, R. R., Sisodia, D. S., & Singh, P. (2023). Web-S4AE: a semi-supervised stacked sparse autoencoder model for web robot detection. Neural Computing and Applications, 35(24), 17883–17898. https://doi.org/10.1007/s00521-023-08668-w
Jyolsna, J., & Anuar, S. (2022). Modern web automation with cypress. Io. Open International Journal of Informatics, 10(2), 182–196. https://oiji.utm.my/index.php/oiji/article/view/229
Malik, N., & Bilal, M. (2024). Natural language processing for analyzing online customer reviews: a survey, taxonomy, and open research challenges. PeerJ Computer Science, 10, e2203. https://doi.org/10.7717/peerj-cs.2203
Mardiani, E., Judijanto, L., Syamsuri, S., & Sufa, S. A. (2023). Online Marketing Strategy and Customer Loyalty in E-commerce-Based Asian Business: The Case of Tokopedia and Shopee. West Science Journal Economic and Entrepreneurship, 1(04), 129–136. https://doi.org/10.58812/wsjee.v1i04.389
Maric, B., Mutka, A., & Orsag, M. (2020). Collaborative Human-Robot Framework for Delicate Sanding of Complex Shape Surfaces. IEEE Robotics and Automation Letters, 5(2), 2848–2855. https://doi.org/10.1109/LRA.2020.2969951
Mobaraya, F., & Ali, S. (2019). Technical Analysis of Selenium and Cypress as Functional Automation Framework for Modern Web Application Testing. 9th International Conference on Computer Science, Engineering and Applications (ICCSEA 2019), 27–46. https://doi.org/10.5121/csit.2019.91803
Nagalingam, S., Wang, H., Kim, S., & Guenther, A. (2024). Unexpectedly strong heat stress induction of monoterpene, methylbutenol, and other volatile emissions for conifers in the cypress family (Cupressaceae). Science of the Total Environment, 956, 177336. https://doi.org/10.1016/j.scitotenv.2024.177336
Nielsen, J. (2012). Usability 101: Introduction to usability. Nielsen Norman Group. https://www.nngroup.com/articles/usability-101-introduction-to-usability/
Patwardhan, A., & Davison, A. J. (2024). A Distributed Multi-Robot Framework for Exploration, Information Acquisition and Consensus. Proceedings - IEEE International Conference on Robotics and Automation, 12062–12068. https://doi.org/10.1109/ICRA57147.2024.10610185
Peldszus, S., Akopian, N., & Berger, T. (2023). RobotBT: Behavior-Tree-Based Test-Case Specification for the Robot Framework. ISSTA 2023 - Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis, 1503–1506. https://doi.org/10.1145/3597926.3604924
Pelivani, E., & Cico, B. (2021). A comparative study of automation testing tools for web applications. 2021 10th Mediterranean Conference on Embedded Computing (MECO), 1–6. https://doi.org/10.1109/MECO52532.2021.9460242
Powers, M. A., Bardsley, J., Cypress, M., Duker, P., Funnell, M. M., Fischl, A. H., Maryniuk, M. D., Siminerio, L., & Vivian, E. (2016). Diabetes self-management education and support in type 2 diabetes: A joint position statement of the American Diabetes Association, the American Association of diabetes educators, and the Academy of nutrition and dietetics. Clinical Diabetes, 34(2), 70–80. https://doi.org/10.2337/diaclin.34.2.70
Psujek, M., Radzik, A., & Kozieł, G. (2021). Comparative analysis of solutions used in Automated Testing of Internet Applications. Journal of Computer Sciences Institute, 18, 7–14. https://doi.org/10.35784/jcsi.2373
Santoso, S., Sitanggang, I. A., & Melisa, G. (2022). Perancangan Perancangan Website E-Commerce Ineed. Id. Jurnal Teknik Informatika, 14(1), 19–23. https://ejurnal.ulbi.ac.id/index.php/informatika/article/view/1915
Sarhan, A. A., Elmagrhi, M. H., & Elkhashen, E. M. (2024). Corruption prevention practices and tax avoidance: The moderating effect of corporate board characteristics. Journal of International Accounting, Auditing and Taxation, 55, 100615. https://doi.org/10.1016/j.intaccaudtax.2024.100615
Silitonga, G., Alim, M. S., Prabowo, H., & Sriwidadi, T. (2023). Online Customer Intention to Purchase Local Brand Shoes: The Role of Website Quality. 2023 8th International Conference on Business and Industrial Research, ICBIR 2023 - Proceedings, 1041–1046. https://doi.org/10.1109/ICBIR57571.2023.10147508
Strizhakov, E., & Nescoromniy, S. (2019). Combined processes of environmentally friendly technology for magnetic-pulse welding. E3S Web of Conferences, 110, 01008. https://doi.org/10.1051/e3sconf/201911001008
Taufique, K. M. R., Sabbir, M. M., Quinton, S., & Andaleeb, S. S. (2024). The different impact of utilitarian and hedonic attributes on web-based retail shopping behaviour through the lens of extended technology acceptance model. International Journal of Retail and Distribution Management, 52(4), 443–460. https://doi.org/10.1108/IJRDM-08-2023-0505
Tuppo, L., Alessandri, C., Giangrieco, I., Ciancamerla, M., Rafaiani, C., Tamburrini, M., Ciardiello, M. A., & Mari, A. (2019). Isolation of cypress gibberellin-regulated protein: Analysis of its structural features and IgE binding competition with homologous allergens. Molecular Immunology, 114, 189–195. https://doi.org/10.1016/j.molimm.2019.07.023
Walker, J. T. (2020). Software Test Automation with Robot Framework. International Journal of Computer Applications, 175(25), 8–14. https://doi.org/10.5120/ijca2020920784
Yu, T., Dai, J., & Wang, C. (2023). Adoption of blended learning: Chinese university students’ perspectives. Humanities and Social Sciences Communications, 10(1), 390. https://doi.org/10.1057/s41599-023-01904-7
Yuliansyah, Y., Rammal, H. G., Maryani, M., Mohamed Jais, I. R., & Mohd-Sanusi, Z. (2021). Organizational learning, innovativeness and performance of financial service firms in an emerging market: examining the mediation effects of customer-focused strategy. Business Process Management Journal, 27(4), 1126–1141. https://doi.org/10.1108/BPMJ-10-2020-0454
Zhang, G., Pan, P., Yang, Z., Niu, H., Liu, J., Zhang, C., Meng, J., Song, Y., Bao, Q., Wei, J., Li, G., & Liao, Z. (2020). Rapid synthesis of cypress-like CuO nanomaterials and CuO/MWCNTs composites for ultra-high sensitivity electrochemical sensing of nitrite. Microchemical Journal, 159, 105439. https://doi.org/10.1016/j.microc.2020.105439

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Copyright (c) 2025 Mutiara Ayu Rizky, Antoni Wibowo