A fine-grained taxonomy of code review feedback in TypeScript projects
Empirical Software Engineering,
Journal Year:
2025,
Volume and Issue:
30(2)
Published: Jan. 14, 2025
Language: Английский
SmellDSL: A domain-specific language to assist developers in specifying code smell patterns
Information and Software Technology,
Journal Year:
2025,
Volume and Issue:
unknown, P. 107760 - 107760
Published: May 1, 2025
Language: Английский
D-ACT: Towards Diff-Aware Code Transformation for Code Review Under a Time-Wise Evaluation
2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER),
Journal Year:
2023,
Volume and Issue:
unknown
Published: March 1, 2023
Code
review
is
a
software
quality
assurance
practice,
yet
remains
time-consuming
(e.g.,
due
to
slow
feedback
from
reviewers).
Recent
Neural
Machine
Translation
(NMT)-based
code
transformation
approaches
were
proposed
automatically
generate
an
approved
version
of
changed
methods
for
given
submitted
patch.
The
existing
could
change
tokens
in
any
area
method.
However,
not
all
need
be
changed.
Intuitively,
the
method
should
paid
more
attention
than
others
as
they
are
prone
defective.
In
this
paper,
we
present
NMT-based
Diff-Aware
Transformation
approach
(DACT)
by
leveraging
token-level
information
enable
NMT
models
better
focus
on
We
evaluate
our
D-ACT
and
baseline
based
time-wise
evaluation
(that
ignored
work)
with
5,758
methods.
Under
scenario,
results
show
that
(1)
can
correctly
transform
107
-
245
methods,
which
at
least
62%
higher
approaches;
(2)
performance
drops
57%
94%
when
ignored;
(3)
improved
17%
82%
average
29%
considering
information.
Our
suggest
evaluated
under
evaluation;
substantially
improve
NMTbased
review.
Language: Английский
Do code reviews lead to fewer code smells?
Journal of Systems and Software,
Journal Year:
2024,
Volume and Issue:
215, P. 112101 - 112101
Published: May 20, 2024
Language: Английский
How social interactions can affect Modern Code Review
Paolo Ciancarini,
No information about this author
Artem Kruglov,
No information about this author
Aygul Malikova
No information about this author
et al.
Frontiers in Computer Science,
Journal Year:
2023,
Volume and Issue:
5
Published: May 11, 2023
Introduction
Modern
Code
Review
(MCR)
is
a
multistage
process
where
developers
evaluate
source
code
written
by
others
to
enhance
the
software
quality.
Despite
numerous
studies
conducted
on
effects
of
MCR
quality,
non-technical
issues
in
have
not
been
extensively
studied.
This
study
aims
investigate
social
problems
and
find
possible
ways
prevent
them
improve
overall
quality
process.
Methodology
To
achieve
research
objectives,
we
applied
grounded
theory
shaped
GQM
approach
collect
data
attitudes
from
different
teams
toward
MCR.
We
interviews
with
25
13
companies
obtain
information
necessary
how
interactions
affect
reviewing
Results
Our
findings
show
that
interpersonal
relationships
within
team
can
significant
consequences
also
received
list
strategies
overcome
these
problems.
Discussion
provides
new
perspective
process,
which
has
studied
before.
The
this
help
development
address
their
products.
Conclusion
valuable
insights
into
them.
Future
could
explore
effectiveness
identified
addressing
Language: Английский
Security Defect Detection via Code Review: A Study of the OpenStack and Qt Communities
Published: Oct. 26, 2023
Background:
Despite
the
widespread
use
of
automated
security
defect
detection
tools,
software
projects
still
contain
many
defects
that
could
result
in
serious
damage.
Such
tools
are
largely
context-insensitive
and
may
not
cover
all
possible
scenarios
testing
potential
issues,
which
makes
them
susceptible
to
missing
complex
defects.
Hence,
thorough
entails
a
synergistic
cooperation
between
these
human-intensive
techniques,
including
code
review.
Code
review
is
widely
recognized
as
crucial
effective
practice
for
identifying
Aim:
This
work
aims
empirically
investigate
through
Method:
To
this
end,
we
conducted
an
empirical
study
by
analyzing
comments
derived
from
four
OpenStack
Qt
communities.
Through
manually
checking
20,995
obtained
keyword-based
search,
identified
614
security-related.
Results:
Our
results
show
(1)
prevalently
discussed
review,
(2)
more
than
half
reviewers
provided
explicit
fixing
strategies/solutions
help
developers
fix
defects,
(3)
tend
follow
reviewers'
suggestions
action
changes,
(4)
Not
worth
now
Disagreement
developer
reviewer
main
causes
resolving
Conclusions:
research
demonstrate
practices
should
combine
manual
with
achieving
comprehensive
coverage
addressing
promoting
appropriate
standardization
practitioners'
behaviors
during
remains
necessary
enhancing
security.
Language: Английский
Do Code Reviews Lead to Fewer Code Smells?
Published: Jan. 1, 2024
Context:
The
code
review
process
is
conducted
by
software
teams
with
various
motivations.
Among
other
goals,
reviews
act
as
a
gatekeeper
for
quality.
Objective:
In
this
study,
we
explore
whether
have
an
impact
on
one
specific
aspect
of
quality,
maintainability.
We
further
extend
our
investigation
analyzing
quality
influences
Method:
investigate
smells
in
the
are
related
to
that
was
reviewed
using
correlation
analysis.
augment
quantitative
analysis
focus
group
study
learn
practitioners'
opinions.
Results:
Our
investigations
revealed
level
neither
increases
nor
decreases
8
out
10
reviews,
regardless
Contrary
intuition,
found
little
no
smells.
identified
potential
reasons
behind
counter-intuitive
results
data.
Furthermore,
practitioners
still
believe
help
improving
Conclusion:
imply
community
should
update
goals
practices
and
reevaluate
those
align
them
more
relevant
modern
realities.
Language: Английский
Experimental evaluation and comparison of anti-pattern detection tools by the gold standard
Published: Nov. 17, 2022
Every
symptom
in
the
source
code
or
design
of
software
that
violates
object-oriented
principles
such
as
maintainability,
reusability,
and
integrity
is
called
an
anti-pattern.
Poor
programming
development
process
can
lead
to
anti-patterns
may
cause
further
problems
maintenance,
so
they
should
be
removed
by
refactoring.
The
first
most
crucial
step
refactoring
anti-pattern
detection.
Different
approaches
tools
have
been
proposed
do
this,
which
provide
different
results
same
program
due
informal
definition
anti-patterns.
In
this
paper,
four
antipattern
detection
compared,
namely
Checkstyle,
PMD,
iPlasma,
Jspirit.
These
are
implemented
on
opensource
systems
presented
a
gold
standard
previous
studies
field.
three
compared:
Large
Class,
Long
Method,
Feature
Envy.
By
comparing
output
standard,
we
sure
our
calculated
precision
recall
values
correct.
Language: Английский
Understanding, Analysis, and Handling of Software Architecture Erosion
Published: Nov. 21, 2023
Architecture
erosion
occurs
when
a
software
system's
implemented
architecture
diverges
from
the
intended
over
time.
Studies
show
impacts
development,
maintenance,
and
evolution
since
it
accumulates
imperceptibly.
Identifying
early
symptoms
like
architectural
smells
enables
managing
through
refactoring.
However,
research
lacks
comprehensive
understanding
of
erosion,
unclear
which
are
most
common,
detection
methods.
This
thesis
establishes
an
landscape,
investigates
symptoms,
proposes
identification
approaches.
A
mapping
study
covers
definitions,
causes,
consequences.
Key
findings:
1)
"Architecture
erosion"
is
used
term,
with
four
perspectives
on
definitions
respective
symptom
types.
2)
Technical
non-technical
reasons
contribute
to
negatively
impacting
quality
attributes.
Practitioners
can
advocate
addressing
prevent
failures.
3)
Detection
correction
approaches
categorized,
consistency
evolution-based
commonly
mentioned.An
empirical
explores
practitioner
communities,
surveys,
interviews.
Findings
reveal
associated
practices
code
review
tools
identify
while
collected
measures
address
during
implementation.
Studying
comments
analyzes
in
practice.
One
reveals
violations,
duplicate
functionality,
cyclic
dependencies
frequent.
Symptoms
decreased
time,
indicating
increased
stability.
Most
were
addressed
after
review.
second
violation
projects,
identifying
10
categories.
Refactoring
removing
some
disregarded.Machine
learning
classifiers
using
pre-trained
word
embeddings
reviews.
SVM
word2vec
achieved
highest
performance.
fastText
worked
well.
200-dimensional
outperformed
100/300-dimensional.
4)
Ensemble
classifier
improved
5)
found
results
valuable,
confirming
potential.An
automated
recommendation
system
identifies
qualified
reviewers
for
violations
similarity
file
paths
comments.
Experiments
common
methods
perform
well,
outperforming
baseline
approach.
Sampling
techniques
impact
Language: Английский