Data Visualization Analytic for Understanding the Dynamics of Operating System Using Programming Language Paradigm

Adeagbo Moruf Adedeji (1) , Agbaje Halimah Adebimpe (2) , Kasali Abdulwakil Adekunle (3)
(1) Department of Computer Science, First Technical University, Ibadan, Nigeria
(2) Beijing School of Aronautics and Astronautics, Beihang University, Beijing, China
(3) Innovation Technology Center, The Federal Polytechnic Ede, Ede, Nigeria
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Evolution of Programming Languages lead to the emergence of new one while the old one slowly fade away. The choice of most developer on Operating System depends on the Programming Language to execute a project. This infer that there is a connection between Programming Languages and Operating System. Hence, this study proposes a data visualization analytic to observe the trend of programming language usages over the years and their effects on Operating Systems. Dataset containing the usage of Programming Languages and Operating System were retrieved from GitHub, Flourish and Stack overflow using text mining that employed regex techniques and Python was used to implement data analytic and visualization. Considering the first ten popular Programming Languages from 330,936 instances, our result similar to the result of other research output with Python leading the Programing Languages. The result of change over time of Operating System shows that Window OS is tending toward negative path while Linux OS and Mac OS are tending toward positive path. Also, Java and JavaScript are mostly used on Window OS, Objective C and Swift are mostly used on Mac OS and Python is mostly used on Linux. The overall results over the years showed that programmers are consistently shifting from Window OS to Linux OS and Mac OS

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How to Cite
A. Moruf Adedeji, A. H. Adebimpe, and K. A. Adekunle, “Data Visualization Analytic for Understanding the Dynamics of Operating System Using Programming Language Paradigm”, Int. J. Data. Science., vol. 3, no. 1, pp. 19-24, Jun. 2022.


K. Gunnarsson and O. Herber, “The Most Popular Programming Languages of GitHub ’ s Trending Repositories,” KTH Vetenskap OCH Konst, 2020.

C. Darwin, “On the Origin of Species.” John Muray, p. 502, 1859.

K. R. Chowdhary, “On the Evolution of Programming Languages,” no. June, 2020.

S. Kabiraj, S. K. Chandra, and A. Gupta, “Operating System a Case Study,” Int. J. Trend Sci. Res. Dev., vol. Volume-2, no. Issue-3, pp. 166–175, 2018, doi: 10.31142/ijtsrd10780.

K. Tsvetkov, “Operating Systems. The Past, Present and Future,” 2020. doi: DOI: 10.13140/RG.2.2.36259.07202., “Best Operating Systems,” 2021. .

Y. Chen, R. Dios, A. Mili, L. Wu, and K. Wang, “An empirical study of programming language trends,” IEEE Softw., vol. 22, no. 3, pp. 72–79, 2005, doi: 10.1109/MS.2005.55.

P. Kumar, “Best Programming Languages to Learn in 2020,” 2019. .

T. F. Bissyande, F. Thung, D. Lo, L. Jiang, and L. Reveillere, “Popularity, interoperability, and impact of programming languages in 100,000 open source projects,” in International Computer Software and Applications Conference, 2013, pp. 303–312, doi: 10.1109/COMPSAC.2013.55.

L. A. Meyerovich and A. S. Rabkin, “Empirical analysis of programming language adoption,” in Proceedings of the 2013 ACM SIGPLAN International Conference on Object Oriented Programming Systems Languages & Applications, 2013, vol. 48, no. 10, pp. 1–18, doi: 10.1145/2544173.2509515.

P. Carbonnelle, “PYPL PopularitY of Programming Language,” PYPL index, 2021. .

TIOBE Software, “TIOBE Index for May 2021,” TIOBE, 2021. .

S. Paul, L. Jolla, and S. Barbara, “from short time series R eports R eports,” Ecology, vol. 96, no. 5, pp. 1174–1181, 2015.