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Position Papers of the 18th Conference on Computer Science and Intelligence Systems

Annals of Computer Science and Information Systems, Volume 36

Comparative Analysis of Low-Code Computation Systems

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DOI: http://dx.doi.org/10.15439/2023F1990

Citation: Position Papers of the 18th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 36, pages 103–110 ()

Full text

Abstract. The paper aims to systematically compare computation platforms where the development of custom computation applications is done visually. By this, we mean platforms equipped with a visual language to define the flow of actions or data, thus allowing us to treat them as low-code systems. The chosen platforms include two mature systems: Orange and Azure Machine Learning Studio, and also a newcomer -- BalticLSC. For the purpose of the study, two sample computing tasks were created and executed on the three platforms. Based on this, the platforms were compared with each other taking into account the following characteristics: versatility, scalability, user entry barrier, cost of use, availability of documentation, maintainability and extensibility, accessibility, security, user interface friendliness, and variety of interfaces for input data.

References

  1. Azure facilities, premises, and physical security. https://learn.microsoft.-com/en-us/azure/security/fundamentals/physical-security. Accessed: 2023-03-10.
  2. Azure Machine Learning documentation. https://learn.microsoft.com/en-us/azure/machine-learning. Accessed: 2023-03-10.
  3. Orange data mining documentation. https://orangedatamining.com/docs. Accessed: 2023-03-10.
  4. Anas Bassam Al-Badareen, Mohd Hasan Selamat, Marzanah A Jabar, Jamilah Din, Sherzod Turaev, and S Malaysia. Users’ perspective of software quality. In The 10th WSEAS international conference on software engineering, parallel and distributed systems (SEPADS 2011), pages 84–89. World Scientific and Engineering Academy and Society (WSEAS) Cambridge, 2011.
  5. Meenakshi Bist, Manoj Wariya, and Amit Agarwal. Comparing delta, open stack and xen cloud platforms: A survey on open source iaas. In 2013 3rd IEEE International Advance Computing Conference (IACC), pages 96–100, 2013.
  6. C. Höfer and G. Karagiannis. Cloud computing services: Taxonomy and comparison. Journal of Internet Services and Applications, 2:81–94, 01 2010.
  7. Amna Ikram, Isma Masood, Tahira Sarfraz, and Tehmina Amjad. A review on models for software quality enhancement from user’s perspective.
  8. A. Jovic, K. Brkic, and N. Bogunovic. An overview of free software tools for general data mining. In 2014 37th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), pages 1112–1117, 2014.
  9. Sarangam Kodati and R Vivekanandam. Analysis of heart disease using in data mining tools orange and weka. Global journal of computer science and technology, Feb 2018.
  10. Charlotte Kotas, Thomas Naughton, and Neena Imam. A comparison of amazon web services and microsoft azure cloud platforms for high performance computing. In 2018 IEEE International Conference on Consumer Electronics (ICCE), pages 1–4, 2018.
  11. Madhavi Maiya, Sai Dasari, Ravi Yadav, Sandhya Shivaprasad, and Dejan Milojicic. Quantifying manageability of cloud platforms. In 2012 IEEE Fifth International Conference on Cloud Computing, pages 993–995, 2012.
  12. Junjie Peng, Xuejun Zhang, Zhou Lei, Bofeng Zhang, Wu Zhang, and Qing Li. Comparison of several cloud computing platforms. In 2009 Second International Symposium on Information Science and Engineering, pages 23–27, 2009.
  13. Niculin Prinz, Christopher Rentrop, and Melanie Huber. Low-code development platforms-a literature review. In AMCIS, 2021.
  14. Venkateswarlu Pynam, R Spanadna, and Kolli Srikanth. An extensive study of data analysis tools (Rapid Miner, Weka, R Tool, Knime, Orange). International Journal of Computer Science and Engineering, 5:4–11, 09 2018.
  15. Ritu Ratra and Preeti Gulia. Experimental evaluation of open source data mining tools (weka and orange). International Journal of Engineering Trends and Technology, 68(8):30–35, 2020.
  16. Radosław Roszczyk, Marek Wdowiak, Michał Śmiałek, Kamil Rybiński, and Krzysztof Marek. Balticlsc: A low-code hpc platform for small and medium research teams. In 2021 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), pages 1–4, 2021.
  17. Jagannath Singh and Nigussu Bitew Kassie. User’s perspective of software quality. In 2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA), pages 1958–1963, 2018.