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Research Article

Comparative Analysis of Program Execution Time Required by Python, R and Julia Compiler

Bhaveshbhai Rameshbhai Maheshwari1
Assistant Professor, Department of Computer Science, Narmada College of Science and Commerce, Bharuch –Gujarat, India.

Published Online: January-April 2024

Pages: 25-27

References

1. Kuhlman, Dave. "A Python Book: Beginning Python, Advanced Python, and Python Exercises". Section 1.1.
2. R language and environment, Hornik, Kurt, The Comprehensive R Archive R Core Team (2016). R: A language and environment for
statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/
3. Bryant, Avi (15 October 2012). "Matlab, R, and Julia: Languages for data analysis". O'Reilly Strata. Archived from the original on 26
April 2014.
4. Singh, Vicky (23 August 2015). "Julia Programming Language – A True Python Alternative". Technotification.
5. Krill, Paul (18 April 2012). "New Julia language seeks to be the C for scientists". InfoWorld.
6. Finley, Klint (3 February 2014). "Out in the Open: Man Creates One Programming Language to Rule Them All". Wired.
7. Hotelling, H. (1943). Some new methods in matrix calculation. The Annals of Mathematical Statistics, 14(1), 1-34.
8. Garg, D. (2021). Dynamizing Dijkstra: A solution to dynamic shortest path problem through retroactive priority queue. Journal of King
Saud University-Computer and Information Sciences, 33(3), 364-373.
9. Bonate, P. L. (2001). A brief introduction to Monte Carlo simulation. Clinical pharmacokinetics, 40, 15-22.
10. Yujian, L., & Bo, L. (2007). A normalized Levenshtein distance metric. IEEE transactions on pattern analysis and machine intelligence,
29(6), 1091-1095.
11. Liu, B., Zhang, Y., & Chen, L. (2005). The dynamical behaviors of a Lotka–Volterra predator–prey model concerning integrated pest
management. Nonlinear Analysis: Real World Applications, 6(2), 227-243

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