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Chapter 6
Change Dynamics
It is a widely accepted fact that evolving software systems change and
grow [166]. However, it is less well-understood how change is distributed
over time, specifically in object oriented software systems. The
patterns and techniques presented in the previous chapter permit developers
to identify specific releases where significant change took place
as well as to inform them of the longer term trend in the distribution
profile. This knowledge assists developers in recording systemic and
substantial changes to a release, as well as to provide useful information
as input into a potential release retrospective. However, the analysis
methods presented in the previous chapters can only be applied
after a mature release of the code has been developed. But in order
to manage the evolution of complex software systems effectively, it is
important to identify change-prone classes as early as possible. Specifically,
developers need to know where they can expect change, the likelihood
of a change, and the magnitude of these modifications in order to
take proactive steps and mitigate any potential risks arising from these
changes.
Previous research into change-prone classes has identified some common
aspects, with different studies suggesting that complex and large
classes tend to undergo more changes [20,28,31,63,130,177,213,266,
314,318], and classes that changed recently are likely to undergo modifications
in the near future [93, 94]. Though the guidance provided is
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