One question was always of my interest right since I started working as a Open Source Data Analyst at SAP Labs,
| Language | Percentage |
| Java | 18.6 |
| C++ | 17.3 |
| C | 16.0 |
| PHP | 13.2 |
| Perl | 6.1 |
| Python | 5.0 |
| C# | 3.8 |
| JavaScript | 3.5 |
| Visual Basic | 2.1 |
| Delphi/Kylix | 2.0 |
| Unix Shell | 1.9 |
| Assembly | 1.5 |
| PL/SQL | 1.1 |
| Others | 7.8 |
Then I thought that this metric is not a fair metric for evaluation. First reason is that the projects are not of the same size in terms of Lines of Code and secondly there are is large variation among the number of developers for an open source project. Then I rank ordered the languages by the total number of lines of code for a particular language. The results are as follows.
| Name | Ratio |
| C/C++ | 47.29% |
| Java | 26.90% |
| PHP | 7.63% |
| C# | 5.17% |
| JavaScript | 3.44% |
| Python | 3.00% |
| Perl | 2.22% |
| Pascal | 1.15% |
| Ruby | 0.93% |
| shell script | 0.75% |
| Tcl | 0.75% |
| Objective C | 0.51% |
| Emacs Lisp | 0.17% |
| Erlang | 0.07% |
| Scheme | 0.02% |
Here we can see that C/C++ has much more impact than Java. This can be contributed to large projects in C/C++ like Linux where there is a lot of effort involved. On the other hand even though Java has larger number of projects they are smaller in size and effort.
1 comment:
I like this a lot. Thank you for sharing. I'm always looking for upcycles like this. In the end, you don't know it was a shipping pallet to begin with!
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