As we saw previously, there are several methodologies for evaluating FLOSS projects. These methodologies provide a set of metrics and categories configurables and evaluables in order to qualify a free software project completely. However, these two methodologies do not provide a complete view and leave a great deal of information from the analysis that could be useful in FLOSS project evaluations.
The following are some metrics that could help improve the evaluation with these methodologies:
- Popularity: a major factor may be the number of projects that are using the software to evaluate, so that more projects more popular and therefore more real success cases exists. You can also take account of downloads by users, the more downloads we have greater visibility and adoption by users for the project in question and this could indicate that the project is most welcome and may involve both a priori one factor that differentiates it from others.
- Code quality: you can get statistics on the number of lines of code, so that the greater number of lines larger size of the project and therefore more difficult to maintain. Also the number of languages used in the development of the tool, so that a large number of languages indicate that is more complex to do modification in the software, this can be very important in case you want to change the tool.
- More information about the community metrics: in both methodologies explores some aspects of the community that there are about FLOSS tool, but can greatly expand these metrics, such as percentage of contribution of 20% of developers, to know community structure or the total number of developers in the community, in order to know the size of the community or the average of commits in the last 6 months to see the growth of the project.
In my opinion there are many metrics that can be added to these methods, some will be more useful for the evaluation of the project that interests us and other unnecessary. The important thing is to give each category and each metric the appropriate relevance to obtain a reliable and interesant result.