What is Open source?
'''Open source''' is a software similar to [[free software]], but is more related to [[business]].<ref>{{Cite journal| publisher = Stanford University| last = O'Mahony| first = Siobhan Clare| title = The emergence of a new commercial actor: Community managed software projects| location = Stanford, CA| date = 2002|pages=34–42}}</ref> 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 [[decade]]s. They became more popular with the [[Linux]] and [[BSD]] software [[community|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=== * [[GNU Octave]]<ref>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.</ref><ref>Eaton, J. W. (2012). GNU Octave and reproducible research. Journal of Process Control, 22(8), 1433-1438.</ref><ref>Eaton, J. W. (2001, March). Octave: Past, present and future. In Proceedings of the 2nd International Workshop on Distributed Statistical Computing.</ref> * [[R (programming language)|R]]<ref>Crawley, M. J. (2012). The R book. John Wiley & Sons.</ref><ref>Dalgaard, P. (2008). Introductory statistics with R. Springer.</ref><ref>Maronna, R. A., Martin, R. D., & Yohai, V. J. (2019). Robust statist