thesis - Faculty of Information and Communication Technologies ...

Chapter 2. Software Evolution
More recent work by Purushothaman et al. [228] has provided some
insight into the size of change. Purushotham et al., based on an analysis
of the source code revision control system logs conclude that most
of the changes are very small based on the observation that 95% of
the changes required a modification of less than 50 lines of code. A key
weakness of this study is that it was based on a single large commercial
software system, and hence lacks sufficient generalizability. Another
study that investigated the size of change was undertaken by Mockus
et al. [201] who observed that the size of change was very small for
defect corrections. The study by Mockus et al. however does not provide
any further insight into the dimensions of change beyond defect
corrections.
Wu et al. [304, 305] in a release-based study investigated the nature of
change in 3 open-source software systems. They found that projects
alternate between periods of localised small incremental changes and
periods of deep architectural changes (which impacted a large number
of modules). The studies by Wu et al. focused on a comparatively small
data set, and investigated only architectural changes by analysing how
incoming and outgoing dependencies for each object file change over
time.
Anton et al. [3, 4] investigated change in the set of functionality offered
by the telephone network to end-users over a 50 year period. Anton et al.
showed that different change drivers apply at different times and that
functional evolution takes place in discrete bursts followed by gradual
enhancement giving rise to a “punctuated equilibrium” pattern [14]. Interestingly,
this is the pattern that Wu et al. also identified in their work
even though the granularity and perspectives of these two studies are
vastly different. Although the study by Anton et al. is interesting, their
findings are helpful to review and understand long-term strategy rather
than in directly helping developers understand the nature of changes
within the software system at a local level over a relatively shorter time
interval.
A different perspective to understanding dimensions of change in the
context of object-oriented software systems has been driven by researchers
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