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. Conclusions<br />
predicting future climate scenarios [115], <strong>and</strong> the economics simulation<br />
models are being developed to help avoid another severe financial<br />
crisis [33, 76].<br />
Although the long-term effects <strong>of</strong> evolution on s<strong>of</strong>tware systems have<br />
been studied now for over three decades, there has been no widely accepted<br />
scientific theory that explains this phenomenon, <strong>and</strong> we are yet<br />
to formally identify the long term impact <strong>of</strong> decisions that developers<br />
routinely make [169]. Creating an agent-based model <strong>of</strong> the s<strong>of</strong>tware<br />
development lifecycle where developers are represented <strong>and</strong> modelled as<br />
simulated agents may identify some <strong>of</strong> the key drivers <strong>and</strong> certainly may<br />
allow us to estimate the likely impact <strong>of</strong> a certain category <strong>of</strong> decisions.<br />
Such an undertaking will require close feedback between simulation,<br />
testing, data collection <strong>and</strong> will be an important step in the eventual<br />
development <strong>of</strong> the theory <strong>of</strong> s<strong>of</strong>tware evolution.<br />
This field <strong>of</strong> research also dem<strong>and</strong>s a multi-disciplinary collaboration<br />
ideally between s<strong>of</strong>tware engineers, psychologists, <strong>and</strong> social scientists<br />
in order to properly identify the variable that need to be within the<br />
simulation. These evolution simulations can be tuned <strong>and</strong> improved<br />
by making use <strong>of</strong> the results from our study as we describe real-world<br />
evolution, <strong>and</strong> a good computational s<strong>of</strong>tware evolution model should<br />
produce output that is similar to the patterns that we find in actual<br />
s<strong>of</strong>tware systems.<br />
S<strong>of</strong>tware engineering literature provides us with a diverse set <strong>of</strong> techniques<br />
<strong>and</strong> methods on how to build s<strong>of</strong>tware. Over the past few decades<br />
we have seen the process <strong>of</strong> s<strong>of</strong>tware construction developing from a<br />
collection <strong>of</strong> ad-hoc rules towards an engineering discipline based on<br />
sound, quantifiable principles. However, despite a wealth <strong>of</strong> knowledge<br />
in how to construct s<strong>of</strong>tware, relatively little deep knowledge is available<br />
on what s<strong>of</strong>tware looks like <strong>and</strong> how its internal structure changes over<br />
time. By providing a deeper insight into how successful s<strong>of</strong>tware systems<br />
evolve, this <strong>thesis</strong> contributes towards closing this gap <strong>and</strong> aids<br />
in the progress <strong>of</strong> the discipline <strong>of</strong> s<strong>of</strong>tware engineering.<br />
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