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Chapter 2. Software Evolution
Dimensions of Change
Change is defined 1 as a process of transformation — to make the form
different from what it is. Some of the earliest studies that attempted to
investigate and understand the nature of change were undertaken by
Lehman et al. [168,175] as part of the work that developed the Laws of
Software Evolution. Lehman et al. were able to establish that existing
software was being adapted based on direct observation of size growth,
and confirmation from the development team that the software was
being adapted to meet changing requirements. Based on the work by
Lehman et al., Gall et al. [85] observed change by measuring the number
of program files that were added, removed and modified in each release
by analysing 20 releases of a single commercial software system. In this
study, Gall et al. showed that some modules changed more than others
and also that the rate of change, in general, decreased over time. More
recent studies have focused on observing changes by measuring the
number of functions that were modified, and also by observing how the
complexity of functions changed over time [217, 291, 310]. A common
finding in these studies of change is that they confirm the applicability
of the First Law of Software Evolution – Continuing Change. A recent
survey paper by Ramil et al. [192] that summarises empirical studies
of evolution within the context of open source software evolution also
suggests that there is consistent support for the first law.
Early work of Lehman et al., as well as following studies into software
evolution (as discussed in previous sections) have consistently found
that software is adapted as it evolves. However, they have not focused
on a more detailed analysis of the various dimensions of change. A
method to understand change more effectively was proposed by Barry
et al. [17] where they argue that volatility within software has three
distinct dimensions from which it can be studied: amplitude (size of
change), periodicity (frequency of change), and dispersion (consistency
of change). Amplitude measures the size of modification and a number
of different approaches can be applied to determine this amplitude. An
example of a method used to determine the amplitude of change in a
file (at two instances in time) can be measured as the sum of the lines
1 Oxford American Dictionary, 2005
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