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Chapter 6. Change Dynamics
smells that they consider is related to excessive complexity within a
class (computed as the sum of method cyclomatic complexities [190]).
In our work, we use the Number of Branches (NOB) as the measure of
structural complexity within a class. The NOB metric that we use can
be considered to be equivalent to the cyclomatic complexity metric used
by Khomh et al. since both metrics are based on the same underlying
measure (see the NOB metric definition in Chapter 4). The findings by
Khomh et al. are similar to our own conclusions with respect to the
structural complexity of a class suggesting that structurally complex
class are change-prone during development, and post-release. We also,
identified a consistent relationship between popularity and probability
of change which was not considered within the work by Khomh et al..
In a recent study, Capiluppi et al. [36, 37] investigated the value of stability
at predicting reuse of a software module (identified as a set of
files within a source code folder) by studying evolution in 4 long-lived
open source software systems. Capiluppi et al. argue that highly stable
modules are good candidates to be tuned into independent reusable
modules. Capiluppi et al. measured stability by using Martin’s Instability
Metric [189] which uses the coupling of a module (similar to the
In Degree and Out Degree count in our work) as the basis for calculating
the stability. However as discussed in Section 6.3.3, Martin’s
instability metric does not measure actual stability of an abstraction
over time and hence cannot be considered to be a direct measure of
actual change. We also did not find any rigorous longitudinal studies
that have shown the relationship between Martin’s instability metric
and actual changes that take place within a module. In contrast, our
work shows that the new dependants place additional pressure on a
class increasing the probability of change to satisfy new clients.
A key distinction from our own study and that by Capiluppi et al. [36,37]
is the level of abstraction used in the study. We focus on changes at the
class level, while Capiluppi et al. study modules. Although, the level of
abstraction used in our study is different, a module can be treated as
a set of related classes. Therefore, if a set of classes within a module
change, we can considered the module to have changed as well and
hence our findings are likely to be similar at the module level as well.
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