thesis - Faculty of Information and Communication Technologies ...
thesis - Faculty of Information and Communication Technologies ...
thesis - Faculty of Information and Communication Technologies ...
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Chapter 5. Growth Dynamics<br />
measure for the frequency <strong>of</strong> state changes in data containers within<br />
a system. Number <strong>of</strong> Branches, on the other h<strong>and</strong>, records all branch<br />
instructions <strong>and</strong> is used to measure the structural complexity at class<br />
level. This measure is equivalent to Weighted Method Count (WMC) as<br />
proposed by Chidamber <strong>and</strong> Kemerer [46] if a weight <strong>of</strong> 1 is applied for<br />
all methods <strong>and</strong> the complexity measure used is cyclomatic complexity<br />
[190]. We use the measures <strong>of</strong> Fan-Out Count <strong>and</strong> Type Construction<br />
Count to obtain insight into the dynamics <strong>of</strong> the s<strong>of</strong>tware systems. The<br />
former <strong>of</strong>fers a means to document the degree <strong>of</strong> delegation, whereas<br />
the latter can be used to count the frequency <strong>of</strong> object instantiations.<br />
The remaining metrics provide structural size <strong>and</strong> complexity measures.<br />
In-Degree Count <strong>and</strong> Out-Degree Count reveal the coupling <strong>of</strong> classes<br />
within a system. As discussed in Chapter 4, these measures are extracted<br />
from the type dependency graph that we construct for each analyzed<br />
system. The vertices in this graph are classes, whereas the edges<br />
are directed links between classes. We associate popularity (i.e., the<br />
number <strong>of</strong> incoming links) with In-Degree Count <strong>and</strong> usage or delegation<br />
(i.e., the number <strong>of</strong> outgoing links) with Out-Degree Count. Number<br />
<strong>of</strong> Methods, Public Method Count, <strong>and</strong> Number <strong>of</strong> Attributes define typical<br />
object-oriented size measures <strong>and</strong> provide insights into the extent<br />
<strong>of</strong> data <strong>and</strong> functionality encapsulation.<br />
5.3.2 Metric Correlation<br />
A natural consequence <strong>of</strong> selecting a range <strong>of</strong> metrics is to see if a<br />
smaller sub-set <strong>of</strong> these metrics would be sufficient. That is, do the selected<br />
measures all represent independent characterizing properties?<br />
We need to examine, therefore, all selected metrics more closely <strong>and</strong><br />
check whether there exists a relationship between any <strong>of</strong> them. If we<br />
discover a consistent <strong>and</strong> strong relationship between two measures,<br />
we may be able to eliminate one metric when it does not provide additional<br />
insights.<br />
In order to reduce the number <strong>of</strong> metrics needed, we use the technique<br />
<strong>of</strong> checking collinearity as recommended by Succi et al. [265] for sim-<br />
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