Open source

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Open source is a software similar to free software, but is more related to business.[1] It is different from other software because the source code is available to everyone. The source code is a set of instructions for the computer, written in a programming language.

Anyone can see how the source code works and can change it if they want to make it work differently. The opposite of open source is closed source. Closed source software is not available to everyone. Open source has a lot in common with free software but each has its own focus and goals.

Open source and free software have been around for decades. They became more popular with the Linux and BSD software communities. To protect the code, a special user license is used. The most common kinds of licence are the GPL, BSD and LGPL. Wikipedia uses open source too. The Open Source Movement is led by the Open Source Initiative.

The open source movement became separate from the free software movement in 1998.

Examples

Computing

Document creation

Companies making open source software

Open Source Media

References

  1. O'Mahony, Siobhan Clare (2002). "The emergence of a new commercial actor: Community managed software projects". Stanford, CA: Stanford University: 34–42. {{cite journal}}: Cite journal requires |journal= (help)
  2. Hansen, J. S. (2011). GNU Octave: Beginner's Guide: Become a Proficient Octave User by Learning this High-level Scientific Numerical Tool from the Ground Up. Packt Publishing Ltd.
  3. Eaton, J. W. (2012). GNU Octave and reproducible research. Journal of Process Control, 22(8), 1433-1438.
  4. Eaton, J. W. (2001, March). Octave: Past, present and future. In Proceedings of the 2nd International Workshop on Distributed Statistical Computing.
  5. Crawley, M. J. (2012). The R book. John Wiley & Sons.
  6. Dalgaard, P. (2008). Introductory statistics with R. Springer.
  7. Maronna, R. A., Martin, R. D., & Yohai, V. J. (2019). Robust statistics: theory and methods (with R). John Wiley & Sons.
  8. Ugarte, M. D., Militino, A. F., & Arnholt, A. T. (2008). Probability and Statistics with R. CRC Press.
  9. Bruce, P., Bruce, A., & Gedeck, P. (2020). Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python. O'Reilly Media.
  10. Kruschke, J. (2014). Doing Bayesian data analysis: A tutorial with R, JAGS, and Stan. Academic Press.
  11. Mora, Á., Galán, J. L., Aguilera, G., Fernández, Á., Mérida, E., & Rodríguez, P. (2010). Scilab and Maxima Environment: Towards Free Software in Numerical Analysis. International Journal for Technology in Mathematics Education, 17(2).
  12. Bunks, C., Chancelier, J. P., Delebecque, F., Goursat, M., Nikoukhah, R., & Steer, S. (2012). Engineering and scientific computing with Scilab. Springer Science & Business Media.
  13. Cameron, D., Rosenblatt, B., Raymond, E., & Raymond, E. S. (1996). Learning GNU Emacs. " O'Reilly Media, Inc.".
  14. Halme, H., & Heinänen, J. (1988). GNU Emacs as a dynamically extensible programming environment. Software: Practice and Experience, 18(10), 999-1009.
  15. Cameron, D., Elliott, J., Loy, M., Raymond, E. S., & Rosenblatt, B. (2005). Learning GNU Emacs. " O'Reilly Media, Inc.".
  16. Schoonover, M. A., & Schoonover, S. (1991). GNU Emacs: UNIX text editing and programming. Addison-Wesley Longman Publishing Co., Inc..
  17. Datta, D. (2017). LaTeX in 24 Hours: A Practical Guide for Scientific Writing. Springer.
  18. Robbins, A., Hannah, E., & Lamb, L. (2008). Learning the vi and vim editors. " O'Reilly Media, Inc.".
  19. Robbins, A. (2011). vi and Vim Editors Pocket Reference: Support for every text editing task. " O'Reilly Media, Inc.".
  20. Neil, D. (2015). Practical Vim: Edit Text at the Speed of Thought. Pragmatic Bookshelf.
  21. Schulz, K. (2007). Hacking Vim: a cookbook to get the most out of the latest Vim editor. Packt Publishing Ltd.
  22. Neil, D. (2018). Modern Vim: Craft Your Development Environment with Vim 8 and Neovim. Pragmatic Bookshelf.
  23. opensource.facebook.com
  24. opensource.google
  25. opensource.microsoft.com

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