None of the material we used
to recruit participants mentioned
refactoring or gave specifics of the
concepts we would be asking about.
Consequently, unlike other studies,
rather than include only developers known to refactor, there should
have been no obvious bias for or
against the use of refactoring. We recruited through personal contacts,
word of mouth, and social media,
supported by our website http://se-
folklore.com and a You Tube video.
The demographic data we collected
reflected a variety of experience,
roles, languages, level of qualification, and type of development.
We set a high bar in assessing
whether a participant would agree
with placing a limit on number of
methods or class depth or would still
refactor when that limit is exceeded.
Different choices would change the
distribution of the frequencies in the
different categories somewhat, but
the same trends would be evident.
Our wording of the possible responses might have affected what responses participants chose, but the
barriers we identified came from
the free-text commentary, which
was unlikely to be affected by such
concerns. Even those who would
refactor mentioned some of the
same concerns (as reported in Table
3 “Yes” columns). Participants from
all demographics provided comments, so there is no obvious bias
due to background, as was also the
case with our target group—those
who would limit number of methods
or depth of inheritance.
We conducted the survey more
than eight years ago and IDEs have
since improved, so perhaps we would
get different results today. However,
little has changed in refactoring sup-
port, and we are not aware of any re-
search directly addressing the issues
our survey identified. More recent
surveys have identified similar issues.
For example, Kim et al.
concerns regarding lack of adequate
test suites. Chen et al.
3 noted 21% of
participants reported lack of support
from management as a reason for not
refactoring and 12.4% did no plan-
ning regarding refactoring. However,
these studies surveyed developers
who were already committed to refac-
tor, whereas ours included those who
chose not to refactor. That these more
recent surveys report findings simi-
lar to ours suggests there has been
little change in barriers to refactoring
since our survey .
We used two metrics to identify
potential design-quality issues based
on published theories. It is possible
the theories are wrong. However,
our conclusions are based on comments by participants who (rightly or
wrongly) believed the theories.
There are significant barriers preventing developers from refactoring
to remove software design-quality
issues, no matter how they are identified. Reducing or even eliminating
the barriers has the potential to significantly improve software quality.
One means is to provide refactoring
support that is goal-directed rather
than operations-directed. Another
is to provide better quantification
of the benefits, thus better informing the decision as to whether or
not to refactor.
We thank our survey participants,
many of whom made the extra effort
to provide the comments we included
and discussed here. We also thank the
anonymous reviewers for their valuable comments and suggestions.
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Ewan Tempero ( firstname.lastname@example.org) is
an associate professor of computer science at the
University of Auckland, Auckland, New Zealand.
Tony Gorschek ( email@example.com) is a
professor of software engineering at the Blekinge
Institute of Technology, Karlskrona, Sweden.
Lefteris Angelis ( firstname.lastname@example.org) is a professor of
statistics and information systems in the Department
of Informatics at Aristotle University of Thessaloniki,
©2017 ACM 0001-0782/17/10
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