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 8<br />
Conclusions<br />
The long-term effects <strong>of</strong> evolution on s<strong>of</strong>tware systems have been studied<br />
for over three decades, however there has been little research into<br />
underst<strong>and</strong>ing how growth <strong>and</strong> change are distributed over parts <strong>of</strong><br />
s<strong>of</strong>tware systems. In our study, we analyzed s<strong>of</strong>tware metrics collected<br />
from forty non-trivial Java Open Source S<strong>of</strong>tware Systems, comprising<br />
over one thous<strong>and</strong> distinct releases in order to better underst<strong>and</strong> the<br />
nature <strong>of</strong> growth <strong>and</strong> change in evolving s<strong>of</strong>tware systems.<br />
8.1 Contributions<br />
The key contributions in this research effort are:<br />
• We found consistent support for the applicability <strong>of</strong> the following<br />
laws <strong>of</strong> s<strong>of</strong>tware evolution [175]: First law Continuing Change,<br />
third law Self Regulation, fifth law Conservation <strong>of</strong> Familiarity, <strong>and</strong><br />
the sixth law Continuing Growth. However, our analysis was not<br />
able to provide sufficient evidence to show support for the other<br />
laws.<br />
• We investigated how s<strong>of</strong>tware metric data distributions (as captured<br />
by a probability density function) change over time. We<br />
confirm that s<strong>of</strong>tware metric data exhibits highly skewed distributions,<br />
<strong>and</strong> show that the use <strong>of</strong> first order statistical summary<br />
measures (such as mean <strong>and</strong> st<strong>and</strong>ard deviation) are ineffective<br />
when working with such data.<br />
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