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Chapter 4. Measuring Evolving Software
Our approach can be contrasted with the Hismo meta-model proposed
by Girba et al. [93] which also models history as an ordered set of versions.
However, in contrast to Hismo, we do not explicitly create abstractions
for various type of histories, for example, the inheritance
history or the package history. In our method, we achieve a similar
outcome by constructing a set of reports (for example, size evolution
report or an inheritance history report) by processing the information
captured in our three main entities. Our technique allows us to construct
dynamic reports as needed to answer various research questions,
rather than building a larger static model.
4.4 Measuring Time
Studies into software evolution typically use two different measures of
time: Release Sequence Number (RSN) and Calendar time. In this section,
we present a discussion of these two types of measures and motivate
our method for measuring time. In particular, we argue that
calendar time is a more appropriate measure of time.
4.4.1 Release Sequence Number (RSN)
The measure of RSN is considered to be a pseudo-time measure [58]
since it treats the time interval between two releases to be constant and
it is independent of elapsed time. The RSN measure has the advantage
of being able to directly reflect a specific version and hence corresponds
to a well defined unit in the release history of a software system [283].
The key limitation to the use of RSN arises when attempting to compare
aspects like growth rates in different software systems [17, 217, 277]
since the time interval between releases in different software systems
cannot be assumed to be the same constant value. Furthermore, since
the time interval between releases does not correspond to a more intuitive
measure of real elapsed time, models that use RSN have to be
carefully interpreted.
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