From Maisqual Private Wiki
This is the milestone for the month of August, 2012.
We don't want to be dependent on a specific model for quality and practices assessment, which would introduce a bias in the correlation. For that reason, we decided to gather and analysis many different base measures, and to build different practices and quality models from them afterwards.
 Gathering data
Detection of practices and evolution of quality needs a fine sampling frequency. Example frequencies are per-version, or time-based (e.g. per month, per week, per day). For small samples, we get more precise information but face a huge-volume problem. Furthermore, the estimated delay for changes to occur after an action is around a few weeks. We decided to build two indexes, one for rough picturing of evolution of the project (per version), and another for fine analysis (per week).
Retrieval of data heavily depends on the tools used by the project.
We defined a standard format for our data.
Projects that do not provide some information are included with NA's as missing values.
 Analysis of data
Once all metrics are put in a standardised format, we are able to apply a (mostly) automated process of analysis to all projects.
These processes are described in this section.
 Types of data
The sources for our input data are the following:
- Code metrics, extracted via SQuORE.
- Mailing lists and Forums, as means of communication between the team members.
- Configuration Management
 Code metrics
It is important to understand what are the metrics gathered, and their so-far known consequences. They have been described on the public maisqual wiki.
There are two axes for the code metrics: the metrics for all files that belong to a build, and the evolution of the application metrics across versions.
R scripts have been written for automatic generation of graphics
 Apache Ant
We wrote an article to describe analysis of Ant with R.
- ↑ We basically want to correlate actions and results, not the way we measure quality.