In this method, the parameter to be measured is magnetic permeability, because it changes at the time of defect nucleation.
The life time of defect clusters in nanotwinned Cu is very different from that in its coarse grained counterpart.
For the ovariectomised group II, BMD decreased from baseline values (T1: 0 weeks, 515.90 ± 70.4 mgHA/mm³) by 31% at the time of defect creation (T2: 5 weeks; 354.50 ± 43.2 mgHA/mm³) and by 52% at the time of sacrifice (T3: 13 weeks) (247.18 ± 30.2 mgHA/mm³).
This test evaluates whether past changes to a given time series of source code metrics can be used to forecast changes in a time series of defects.
For this purpose, we relied on the Granger Causality Test to evaluate whether past changes to a given time series of source code metrics can be used to forecast changes in a time series of defects.
In a second step, for each class, the tool created eleven time series of source code metrics (for each metric in Table 1) and one time series of defects.
P2: The values in the time series of defects must not be all equal to zero.
P3: The time series of defects must be stationary, which is a precondition required by the Granger Test (Fuller 1995).
The BugMaps-Granger tool extracts time series of defects from such systems and allows the visualization of different bug measures, including the source code properties that Granger-caused bugs.
To create the time series of defects for each class, the module receives as input a CSV file containing the bugs (IDs and creation dates) collected from the bug tracking platforms (e.g., Bugzilla, Jira, Mantis, etc).. Basically, the module maps the bugs to their respective commits, using the mapping strategy presented in details in (Couto et al. 2012; Couto et al. 2014).
