thesis - Faculty of Information and Communication Technologies ...

Chapter 4. Measuring Evolving Software
Days Since Previous Release
0 50 100 150
Azureus Bittorrent Client
0 10 20 30 40 50
Release Sequence Number
Days Since Previous Release
0 50 100 150 200
Hibernate ORM Framework
0 10 20 30 40 50
Release Sequence Number
Days Since Previous Release
0 20 40 60 80 100
Kolmafia Game
0 10 20 30 40 50
Release Sequence Number
Days Since Previous Release
0 50 100 150
Spring Framework
0 10 20 30 40 50
Release Sequence Number
Figure 4.2: Time intervals (measured in days) between releases is erratic.
four software systems from our data set. If developers release software
at regular intervals the scatter plots (cf. Figure 4.2) would show
substantially less variability. Further, given the variability in the data,
we are also unable to derive a generalizable, and sufficiently strong linear
relationship between RSN and “Days between Consecutive Releases”
which is necessary for RSN measure to be considered an interval scale
measure [260]. Though, the intervals are erratic, interestingly in approximately
70% of the releases (across our entire data set) we noticed
that the gap between consecutive releases is less than 90 days (see Figure
4.3). This observation indicates that there exists some pressure on
the development team that compels them to release software at reasonable
intervals, potentially to ensure ongoing community support.
Since we treat RSN as an ordinal scale measure, we apply only the
set of mathematical operations that are valid for the ordinal scale. This
restriction implies that we do not use RSN in any parametric regression
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