thesis - Faculty of Information and Communication Technologies ...

Chapter 7. Implications
overall structure and shape of the distribution. We found no evidence
that developers actively measure the metric distribution and aim to fit
within it, as there is no traces of this type of behaviour in the change
logs, development process documents or release notes that we studied.
The interesting aspect is that developers have no direct knowledge of
the overall distribution, yet the set of choices they make ensure that the
overall profile is highly consistent. This suggests that feedback operates
at the local level rather than at the system level. That is, developers notice
that a certain class is too complex and take steps to correct that.
Similarly, refactoring efforts [81] in most cases are likely to be choices
made with local information.
This behaviour of developers relying on localised feedback is indicative
of software maintenance being a stochastic process that generates an
emergent pattern when observed at the system level. We define emergence
in this context as a process that drives a system to acquire a
spatial, functional and temporal structure without specific directed interference
from outside. By specific, we mean that the structure or
functioning is not the result of directed and planned actions, rather
the system achieves its structure via a series of autonomous actions
that are taken at random intervals for a range of purposes. Interestingly,
software is not unique in this emergent behaviour as this pattern
has also been identified in human engineered, social and natural systems
[111].
What are the set of causal factors that cause this observed phenomenon?
We do not have a direct answer yet of the causal factors, but the consistency
of the observations gives rise to the speculation that developer
decisions are driven by some form of cognitive preference that makes developers
choose solutions with certain typical profiles. It appears that
there exists an acceptable range of complexity for programmers and this
range is domain-independent since the Gini coefficients across all analyzed
systems fall within a tightly-bounded interval and is independent
of the Java language semantics as well as development-environment
neutral. The Java programming language does not, in any way, limit
developers to choose between design alternatives or forces them to construct
software with the observed distribution profiles and hence the
184