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3
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SB
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[
5
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[
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.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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I
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Vo
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4
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1
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Ju
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20
2
6
:
233
-
24
9
234
Desp
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d
d
o
es
n
o
t
lev
er
ag
e
th
e
d
y
n
a
m
ic
p
r
io
r
itizatio
n
m
ec
h
a
n
is
m
s
th
at
ch
ar
ac
ter
ize
aDy
n
aM
OSA.
As
a
r
esu
lt,
cu
r
r
en
t
s
o
lu
tio
n
s
eith
er
f
o
c
u
s
o
n
r
ed
u
cin
g
th
e
d
im
en
s
io
n
ality
o
f
t
h
e
o
b
jectiv
e
s
p
ac
e
with
o
u
t
a
d
ap
tiv
ity
o
r
ap
p
l
y
ad
ap
tiv
e
o
p
tim
izatio
n
with
o
u
t
ex
p
licitly
ad
d
r
ess
in
g
o
b
jectiv
e
r
ed
u
n
d
a
n
cy
.
T
h
e
in
te
g
r
atio
n
o
f
d
im
en
s
io
n
ality
r
ed
u
ctio
n
with
a
d
ap
tiv
e
m
an
y
-
o
b
jectiv
e
s
ea
r
ch
th
er
ef
o
r
e
r
em
ain
s
u
n
d
er
e
x
p
lo
r
e
d
.
T
o
f
ill
th
is
g
ap
,
th
is
s
tu
d
y
p
r
o
p
o
s
es
PC
A
-
aDy
n
aM
OSA,
a
n
o
v
el
ap
p
r
o
ac
h
th
at
co
m
b
i
n
es
PC
A
-
b
ased
d
im
en
s
io
n
ality
r
ed
u
ctio
n
wit
h
th
e
ad
ap
ti
v
e
m
an
y
-
o
b
jectiv
e
o
p
tim
izatio
n
f
r
am
ewo
r
k
o
f
aDy
n
aM
OSA.
B
y
em
b
ed
d
in
g
PC
A
in
to
th
e
ad
a
p
tiv
e
s
ea
r
ch
p
r
o
ce
s
s
,
th
e
p
r
o
p
o
s
ed
ap
p
r
o
ac
h
aim
s
to
s
im
u
ltan
eo
u
s
ly
m
itig
ate
o
b
jectiv
e
ex
p
lo
s
io
n
a
n
d
ex
p
l
o
it
d
y
n
am
ic
o
b
jectiv
e
p
r
io
r
iti
za
tio
n
.
T
h
is
in
teg
r
atio
n
is
ex
p
ec
ted
to
en
h
an
ce
s
ca
lab
ilit
y
an
d
s
ea
r
ch
ef
f
icie
n
cy
wh
ile
p
r
eser
v
in
g
th
e
ef
f
ec
tiv
en
ess
o
f
test
ca
s
e
g
en
er
atio
n
in
lar
g
e
-
s
ca
le,
m
an
y
-
o
b
jectiv
e
test
in
g
s
ce
n
ar
i
o
s
.
2.
RE
L
AT
E
D
WO
RK
S
Heu
r
is
tic
s
ea
r
ch
tech
n
iq
u
es
h
av
e
p
r
o
g
r
ess
iv
ely
b
en
ad
o
p
te
d
in
v
ar
io
u
s
r
esear
ch
d
o
m
ain
s
,
in
clu
d
i
n
g
au
to
m
ated
test
ca
s
e
g
en
e
r
atio
n
.
On
e
n
o
tab
le
a
p
p
r
o
ac
h
is
t
h
e
wh
o
le
test
s
u
ite
(
W
T
S)
s
tr
ateg
y
im
p
lem
e
n
ted
with
in
th
e
E
v
o
Su
ite
f
r
am
ewo
r
k
.
I
n
th
is
ap
p
r
o
ac
h
,
Fra
s
er
et
a
l.
[
7
]
r
e
f
o
r
m
u
lated
th
e
g
en
e
r
a
tio
n
o
f
test
ca
s
e
task
as
an
o
p
tim
izatio
n
with
a
m
an
y
-
o
b
jectiv
e
-
b
ased
p
r
o
b
lem
.
T
h
ey
ap
p
lied
a
weig
h
t
ed
-
s
u
m
s
tr
ateg
y
in
wh
ich
th
e
o
v
er
all
f
itn
ess
s
co
r
e
is
co
m
p
u
ted
b
y
a
g
g
r
eg
a
tin
g
th
e
f
itn
ess
v
alu
es
ass
o
c
iated
with
m
u
ltip
le
co
v
er
ag
e
ta
r
g
ets.
Z
h
an
g
a
n
d
L
i
[
8
]
i
n
t
r
o
d
u
ce
d
a
m
an
y
-
o
b
jectiv
e
test
g
en
e
r
atio
n
ap
p
r
o
ac
h
b
ased
o
n
th
e
lo
n
g
ico
r
n
b
ee
tle
s
ea
r
ch
alg
o
r
ith
m
.
T
h
ei
r
m
eth
o
d
i
n
co
r
p
o
r
ated
a
t
o
tal
p
ath
s
im
ilar
ity
m
etr
ic
th
at
ev
alu
ates
m
u
ltip
le
ex
ec
u
tio
n
p
ath
s
in
a
r
elatio
n
t
o
a
tar
g
et
p
ath
s
et
with
in
th
e
p
r
o
g
r
a
m
.
Simi
lar
ly
,
Sah
in
et
a
l.
[
9
]
d
ev
el
o
p
ed
a
f
u
ll
test
s
u
ite
g
en
er
atio
n
tech
n
iq
u
e
u
tili
zin
g
an
ar
ch
i
v
e
-
b
as
ed
m
u
lti
-
cr
iter
ia
in
to
a
u
n
i
f
ied
f
itn
ess
ev
alu
atio
n
s
ch
em
e,
en
ab
lin
g
s
im
u
ltan
eo
u
s
o
p
tim
izatio
n
o
f
s
ev
e
r
al
o
b
jectiv
es.
T
h
e
ar
c
h
iv
e
m
ec
h
an
is
m
was
f
u
r
th
er
em
p
lo
y
ed
to
e
n
h
an
ce
s
ea
r
ch
ef
f
icien
cy
.
I
n
ad
d
r
ess
in
g
m
an
y
-
o
b
jectiv
e
o
p
tim
izatio
n
,
t
h
ey
also
ad
o
p
ted
a
weig
h
ted
-
s
u
m
m
ec
h
an
is
m
s
im
ilar
to
th
at
u
s
ed
in
th
e
wh
o
le
s
u
ite
s
tr
ateg
y
to
o
p
tim
ize
co
v
e
r
ag
e
tar
g
ets
co
n
cu
r
r
en
tly
.
Desp
ite
th
e
ad
v
an
tag
es
o
f
weig
h
ted
-
s
u
m
ap
p
r
o
ac
h
es,
in
clu
d
in
g
th
e
wh
o
le
s
u
ite
m
eth
o
d
in
h
an
d
lin
g
m
u
ltip
le
o
b
jectiv
es
m
o
r
e
ef
f
ic
ien
tly
th
an
s
in
g
le
-
o
b
jectiv
e
s
e
ar
ch
,
th
ey
e
n
co
u
n
ter
d
if
f
icu
lti
es
wh
en
n
av
ig
atin
g
non
-
c
o
n
v
e
x
s
p
ac
es,
o
f
ten
lead
in
g
to
s
u
b
o
p
tim
al
co
n
v
er
g
e
n
c
e
in
test
ca
s
e
g
en
er
atio
n
task
[
1
0
]
.
T
o
o
v
er
c
o
m
e
th
is
lim
itatio
n
s
,
Pan
ich
ella
et
a
l.
[
1
1
]
I
n
tr
o
d
u
ce
d
MO
SA,
a
p
r
ef
er
en
ce
-
b
ased
GA
d
er
iv
ed
f
r
o
m
th
e
wh
o
l
e
s
u
ite
co
n
ce
p
t.
Un
lik
e
tr
a
d
itio
n
al
ev
o
lu
tio
n
ar
y
alg
o
r
ith
m
s
th
at
em
p
h
asize
p
o
p
u
lar
ity
d
iv
er
s
ity
,
MO
SA
p
r
io
r
itizes
in
d
iv
id
u
als
wh
o
s
e
f
itn
e
s
s
v
alu
es
ap
p
r
o
ac
h
ze
r
o
,
as
th
e
u
ltima
te
o
b
jectiv
e
in
te
s
t
g
en
er
atio
n
is
to
s
atis
f
y
co
v
er
ag
e
tar
g
ets co
m
p
l
etely
.
A
s
ig
n
if
ican
t
ch
allen
g
e
in
m
an
y
-
o
b
jectiv
e
s
ea
r
ch
-
b
ased
te
s
tin
g
lies
in
th
e
ex
p
lo
s
io
n
o
f
co
v
er
ag
e
o
b
jectiv
es,
wh
ich
ca
n
d
eg
r
a
d
e
s
ea
r
ch
ef
f
icein
c
y
an
d
h
i
n
d
e
r
th
e
g
en
er
atio
n
o
f
h
ig
h
-
co
v
e
r
ag
e
test
ca
s
es.
T
o
ad
d
r
ess
th
is
is
s
u
e,
Pan
ich
ella
et
a
l.
[
1
2
]
Pr
o
p
o
s
ed
Dy
n
a
MO
SA,
an
ex
ten
s
io
n
o
f
M
OSA
th
at
en
h
an
ce
s
p
er
f
o
r
m
an
ce
th
r
o
u
g
h
d
y
n
a
m
ic
tar
g
et
s
elec
tio
n
.
I
n
p
r
ac
tice,
co
v
er
ag
e
tar
g
ets
with
in
a
class
ar
e
o
f
te
n
in
ter
d
ep
en
d
en
t.
Fo
r
i
n
s
tan
ce
,
in
a
s
in
g
le
m
eth
o
d
,
ce
r
tain
b
r
an
ch
es
ca
n
n
o
t
b
e
e
x
ec
u
ted
u
n
less
p
r
ec
en
d
in
g
b
r
an
ch
es
h
av
e
al
r
ea
d
y
b
ee
n
t
r
an
v
er
s
ed
,
f
o
lo
win
g
th
e
t
o
p
-
d
o
wn
ex
ec
u
tio
n
o
r
d
e
r
o
f
th
e
c
o
d
e.
Fu
r
th
er
m
o
r
e,
s
o
m
e
o
b
jectiv
es
ar
e
h
ier
ar
ch
ia
lly
d
ep
e
n
d
en
t
o
n
d
o
m
in
a
n
t
b
r
a
n
ch
es.
Dy
n
aM
OSA
m
an
ag
es t
h
ese
d
ep
en
d
en
cies
b
y
ex
p
lo
r
in
g
c
o
v
er
ag
e
tar
g
e
ts
with
in
a
co
n
t
r
o
l
d
ep
en
d
e
n
cy
g
r
ap
h
,
wh
er
e
o
n
ly
d
o
m
in
an
t
o
r
cu
r
r
en
tly
r
ea
ch
ab
le
o
b
jectiv
es
ar
e
co
n
s
id
er
ed
.
T
a
r
g
ets
ar
e
r
em
o
v
e
d
f
r
o
m
th
e
g
r
ap
h
o
n
ce
th
ey
h
av
e
b
ee
n
s
u
cc
ess
f
u
ll
y
co
v
er
ed
.
B
y
d
y
n
am
ically
lim
itin
g
th
e
s
et
o
f
ac
h
iev
e
o
b
jectiv
es,
Dy
n
aM
OSA
r
ed
u
ce
d
th
e
d
im
e
n
s
io
n
ality
o
f
th
e
o
p
tim
izatio
n
p
r
o
b
lem
,
th
er
eb
y
im
p
r
o
v
i
n
g
s
ea
r
ch
ef
f
ec
tiv
en
ess
.
B
u
ild
in
g
u
p
o
n
th
is
f
r
am
ewo
r
k
,
Pan
ich
ella,
et
a
l.
[
1
3
]
later
i
n
tr
o
d
u
ce
d
a
m
u
lti
-
cr
ite
r
ia
ex
t
en
s
io
n
th
at
allo
ws
s
im
u
ltan
e
o
u
s
o
p
tim
izatio
n
o
f
m
u
ltip
le
co
v
er
a
g
e
m
etr
ics,
s
u
ch
as
b
r
an
c
h
co
v
er
ag
e
a
n
d
lin
e
co
v
er
a
g
e
with
in
a
u
n
if
ied
s
e
ar
ch
p
r
o
ce
s
s
.
Mo
r
e
r
ec
en
tly
,
r
esear
ch
h
as
ex
ten
d
ed
s
ea
r
ch
-
b
ased
test
ca
s
e
g
en
er
atio
n
to
in
co
r
p
o
r
ate
n
o
n
-
f
u
n
ctio
n
a
l
p
r
o
p
er
ties
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
A
u
to
-
g
e
n
era
ted
u
n
it testi
n
g
u
s
in
g
P
C
A
-
a
Dyn
a
MOS
A
(
Ma
d
e
R
a
ja
A
d
i
S
u
r
ya
S
a
p
u
tr
a
)
235
Fo
r
ex
am
p
le,
Gr
a
n
o
,
et
a
l.
[
6
]
Pro
p
o
s
ed
aDy
n
aM
OSA
wh
ich
au
g
m
e
n
ts
th
e
o
b
jectiv
e
s
p
ac
e
b
y
in
clu
d
i
n
g
ex
ec
u
tio
n
tim
e
a
n
d
m
em
o
r
y
c
o
n
s
u
m
p
tio
n
as a
d
d
itio
n
al
o
p
ti
m
izatio
n
cr
iter
ia.
3.
M
E
T
H
O
D
I
n
th
is
s
tu
d
y
,
th
e
aDy
n
aM
OSA
is
ad
o
p
ted
as
th
e
b
ase
alg
o
r
ith
m
f
o
r
g
e
n
er
atin
g
an
a
u
to
m
atic
test
ca
s
e.
W
h
ile
aDy
n
aM
OSA
ef
f
ec
tiv
ely
m
itig
ates
th
e
s
ca
lab
ilit
y
is
s
u
e
o
f
m
an
y
-
o
b
jectiv
e
o
p
tim
izatio
n
b
y
d
y
n
am
ically
m
an
ag
i
n
g
tar
g
et
o
b
jectiv
es,
its
p
er
f
o
r
m
an
ce
m
ay
s
till
d
eg
r
a
d
e
wh
en
th
e
n
u
m
b
er
o
f
o
b
jectiv
es
g
r
o
ws
ex
ce
s
s
iv
ely
,
as
co
m
m
o
n
ly
o
b
s
er
v
e
d
in
co
m
p
lex
s
o
f
twar
e
s
y
s
tem
s
with
d
en
s
e
co
n
tr
o
l
f
l
o
w
an
d
n
u
m
er
o
u
s
co
v
er
ag
e
tar
g
ets.
T
o
ad
d
r
ess
th
is
lim
itatio
n
,
th
is
r
esear
ch
in
tr
o
d
u
ce
s
a
d
im
e
n
s
io
n
ality
-
r
ed
u
ctio
n
-
b
ased
o
b
je
ctiv
e
a
g
g
r
e
g
atio
n
te
ch
n
iq
u
e
u
s
in
g
PC
A
th
at
is
in
s
p
ir
ed
f
r
o
m
p
r
ev
io
u
s
s
tu
d
y
b
y
Li
et
a
l.
[
1
4
]
.
PC
A
h
as
b
ee
n
s
u
cc
ess
f
u
lly
ap
p
lied
in
p
r
io
r
w
o
r
k
to
r
ed
u
ce
r
ed
u
n
d
an
cy
an
d
co
r
r
elatio
n
am
o
n
g
co
v
er
ag
e
o
b
jectiv
es
wh
ile
p
r
eser
v
in
g
ess
en
tial o
p
ti
m
izatio
n
in
f
o
r
m
atio
n
.
T
h
is
r
esear
ch
p
r
o
p
o
s
es
s
o
m
e
p
r
o
b
lem
f
o
r
m
u
latio
n
s
:
3
.
1
.
Sin
g
le
-
o
bje
ct
i
v
e
o
ptim
iz
a
t
io
n
T
h
e
o
p
tim
izatio
n
p
r
o
ce
s
s
b
eg
i
n
s
b
y
g
en
er
atin
g
ca
n
d
i
d
ate
test
s
u
ites
co
m
p
o
s
ed
with
f
lex
ib
le
n
u
m
b
er
o
f
in
d
iv
id
u
al
test
ca
s
es.
E
ac
h
test
ca
s
e
co
n
s
is
ts
o
f
a
s
eq
u
en
ce
o
f
m
eth
o
d
in
v
o
ca
tio
n
s
th
at
m
ay
v
ar
y
in
s
tr
u
ctu
r
al
co
m
p
o
s
itio
n
.
T
h
e
f
itn
ess
ev
alu
atio
n
ass
ess
es
th
e
ex
ten
t
to
w
h
ich
a
ca
n
d
i
d
ate
s
u
ites
s
atis
f
ie
s
th
e
p
r
ed
ef
in
e
d
co
v
er
a
g
e
o
b
jectiv
es.
T
h
er
ef
o
r
e,
id
e
n
tify
in
g
a
n
ap
p
r
o
p
r
iate
test
s
u
ite
T
r
eq
u
ir
es
f
u
lf
illi
n
g
all
s
p
ec
if
ied
test
in
g
tar
g
ets,
wh
ich
ar
e
d
e
f
in
ed
as f
o
llo
ws:
min
(
)
=
∑
(
,
)
∈
(
1
)
(
,
)
:
T
h
e
m
in
im
u
m
v
alu
e
o
f
th
e
d
is
tan
ce
m
ea
s
u
r
e
ass
o
ciate
d
with
tar
g
et
u
u
n
d
er
th
e
d
ef
i
n
ed
d
is
tan
ce
f
u
n
ctio
n
.
T
h
e
f
u
n
ctio
n
is
d
esig
n
ed
to
r
ed
u
ce
th
e
d
is
tan
ce
m
etr
ic
d
s
u
ch
th
at
(
,
)
=
0
in
d
icate
s
co
m
p
lete
co
v
er
ag
e
o
f
tar
g
et
u
b
y
th
e
ex
ec
u
tio
n
o
f
test
s
u
ite
T
.
Var
iatio
n
s
in
co
v
er
ag
e
cr
iter
ia
lead
to
d
if
f
er
en
t
d
ef
in
itio
n
s
o
f
th
e
d
is
tan
ce
f
u
n
ctio
n
,
wh
ich
m
ea
s
u
r
es
th
e
d
eg
r
ee
to
wh
ich
th
e
ex
ec
u
tio
n
tr
ac
e
ap
p
r
o
ac
h
es
f
u
lf
illme
n
t o
f
t
h
e
o
b
jectiv
e
u
.
W
h
en
co
n
s
id
er
i
n
g
b
r
an
c
h
co
v
er
ag
e,
ea
ch
co
n
d
itio
n
al
b
r
an
ch
in
th
e
clas
s
u
n
d
er
te
s
t
(
C
UT
)
r
ep
r
esen
ts
a
d
is
tin
ct
co
v
er
ag
e
o
b
jectiv
e
.
T
h
u
s
,
th
e
p
r
o
b
lem
ca
n
b
e
m
o
d
u
led
as
id
e
n
tify
in
g
a
test
s
u
ite
ca
p
ab
le
o
f
co
v
er
ig
n
g
all
s
u
ch
b
r
an
c
h
es.
T
h
e
co
v
er
a
g
e
s
tatu
s
o
f
ea
ch
b
r
an
ch
is
q
u
an
tifie
d
u
s
in
g
th
e
d
is
tan
ce
f
u
n
ctio
n
d
,
d
ef
in
ed
as f
o
llo
ws:
min
(
)
=
|
|
−
|
|
+
∑
(
,
)
∈
(
2
)
|
|
: T
o
tal
n
u
m
b
e
r
o
f
m
et
h
o
d
s
.
|
|
: N
u
m
b
er
o
f
ex
ec
u
ted
m
eth
o
u
s
ed
to
s
ea
r
ch
f
o
r
th
e
u
n
ex
ec
u
te
d
m
eth
o
d
b
y
.
(
,
)
: N
o
r
m
alize
d
b
r
an
ch
d
is
tan
ce
f
o
r
b
r
an
ch
∈
.
T
er
m
in
o
lo
g
y
o
f
|
|
−
|
|
d
escr
ib
es
th
e
n
u
m
b
e
r
o
f
m
eth
o
d
m
in
u
s
b
y
n
u
m
b
er
e
x
ec
u
ted
m
eth
o
d
s
th
at
u
s
ed
to
f
in
d
th
e
u
n
e
x
ec
u
ted
m
eth
o
d
s
b
y
T
.
T
h
e
m
in
i
m
u
m
n
o
r
m
alize
d
b
r
an
c
h
d
is
tan
ce
f
o
r
ea
ch
b
r
an
ch
∈
is
d
ef
in
ed
as f
o
llo
ws:
(
,
)
=
{
0
1
(
∈
,
)
(
∈
,
)
+
1
(
3
)
(
∈
,
)
:
R
ep
r
esen
ts
th
e
u
n
n
o
r
m
alize
d
b
r
a
n
ch
d
is
tan
ce
o
v
e
r
all
tes
t
ca
s
es
∈
.
T
h
e
f
u
n
ctio
n
r
e
p
r
esen
ts
th
e
r
aw
b
r
an
ch
d
is
tan
ce
co
m
p
u
ted
ac
c
o
r
d
in
g
to
t
h
e
s
elec
ted
d
is
tan
ce
ev
alu
atio
n
s
ch
em
e,
q
u
a
n
tify
in
g
h
o
w
clo
s
e
th
e
p
r
ed
icate
co
n
tr
o
llin
g
b
r
an
ch
b
is
to
b
ei
n
g
s
atis
f
ied
d
u
r
in
g
ex
ec
u
tio
n
.
I
n
s
tr
o
n
g
m
u
tatio
n
co
v
er
ag
e,
ea
ch
test
in
g
tar
g
et
co
r
r
s
p
o
n
d
s
to
a
m
o
d
if
ied
v
er
s
io
n
o
f
t
h
e
o
r
ig
i
n
al
class
,
o
b
tain
ed
b
y
in
tr
o
d
u
cin
g
an
ar
tific
ial
ch
an
g
e
t
h
at
s
im
u
lates
a
p
o
ten
tial
f
au
lt.
T
h
e
o
b
jectiv
e
is
to
co
n
s
tr
u
ct
a
test
s
u
ite
ca
p
ab
le
o
f
d
etec
tin
g
all
s
u
ch
m
u
ta
n
ts
,
i.e
.
,
k
illi
n
g
ev
er
y
in
jecte
d
m
u
tatio
n
.
A
m
u
tan
t
is
co
n
s
id
er
ed
k
illed
b
y
a
test
ca
s
e
if
ex
ec
u
tin
g
th
e
o
r
ig
in
al
an
d
m
u
tated
v
er
s
io
n
s
u
n
d
er
th
e
s
a
m
e
in
p
u
t
p
r
o
d
u
ce
s
d
if
f
er
en
t
o
b
s
er
v
ab
le
b
eh
av
io
r
s
,
eith
er
in
ter
m
s
o
f
r
etu
r
n
e
d
v
alu
es
o
r
ex
ter
n
ally
v
is
ib
le
o
b
ject
s
tates.
I
n
p
r
ac
tice,
th
is
d
is
tin
ctio
n
is
v
er
if
ied
th
r
o
u
g
h
au
to
m
ated
ass
er
tio
n
s
th
at
co
m
p
ar
e
th
e
o
b
s
er
v
a
b
le
o
p
u
tp
u
ts
o
f
th
e
o
r
ig
in
al
im
p
lem
e
n
tatio
n
.
I
f
th
e
ass
er
tio
n
h
o
ld
s
f
o
r
th
e
o
r
ig
i
n
al
p
r
o
g
r
am
,
b
u
t
f
ails
f
o
r
th
e
m
u
tan
t,
th
e
m
u
tatio
n
is
r
eg
ar
d
ed
as d
etec
ted
.
T
h
e
ef
f
ec
tiv
en
ess
o
f
s
tr
o
n
g
m
u
tatio
n
test
in
g
r
elies
o
n
th
e
co
n
ce
p
ts
o
f
in
f
ec
tio
n
a
n
d
p
r
o
p
a
g
atio
n
.
L
et
an
d
d
en
o
te
th
e
e
x
ec
u
tio
n
s
tates
o
f
th
e
o
r
ig
in
al
a
n
d
m
u
tate
d
p
r
o
g
r
am
s
r
esp
ec
tiv
ely
.
A
m
u
tan
t
is
s
aid
to
ca
u
s
e
in
f
ec
tio
n
if
≠
im
m
ed
iately
af
ter
th
e
m
u
tated
s
tatem
en
t
is
ex
ec
u
ted
,
in
d
icatin
g
th
at
th
e
in
jecte
d
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
4
3
,
No
.
1
,
Ju
ly
20
2
6
:
233
-
24
9
236
f
au
lt
h
as
alter
ed
th
e
in
ter
n
al
p
r
o
g
r
am
s
tat
e.
Pro
p
ag
atio
n
o
cc
u
r
s
wh
en
th
is
in
f
ec
te
d
s
atte
in
f
lu
en
ce
s
s
u
b
s
eq
u
en
t
co
m
p
u
tatio
n
s
.
Ultim
ately
,
s
u
c
h
o
f
an
e
v
en
t
is
lead
i
n
g
t
o
a
d
i
s
cr
ep
an
cy
in
o
b
s
er
v
ab
le
o
u
tp
u
ts
.
On
ly
wh
en
b
o
th
in
f
ec
tio
n
an
d
p
r
o
p
ag
atio
n
o
cc
u
r
ca
n
a
m
u
tan
t b
e
s
u
cc
ess
f
u
lly
d
etec
ted
b
y
th
e
t
est ca
s
e.
Pro
b
lem
2
.
1
.
Giv
e
n
a
s
et
o
f
m
u
tan
ts
M
=
{M
1
,
…,
M
k
}
co
n
t
ain
ed
in
a
class
,
d
eter
m
in
e
a
t
est
s
u
ite
T
= {t
1
, …, t
n
}
th
at
ca
n
elim
in
ate
th
e
m
u
tan
ts
ac
co
r
d
in
g
t
o
th
e
f
o
llo
win
g
f
o
r
m
u
latio
n
:
min
(
)
=
(
)
+
∑
(
(
,
)
+
(
,
)
)
∈
(
4
)
(
)
: O
v
er
all
f
itn
ess
f
u
n
ctio
n
f
o
r
e
v
er
y
b
r
an
ch
in
T
th
at
d
ir
ec
tly
co
n
tr
o
ls
th
e
d
e
p
en
d
e
n
cy
o
f
m
u
tan
t
m
.
: E
s
tim
atio
n
o
f
d
is
tan
ce
to
th
e
in
f
ec
tio
n
s
tate.
: Pr
o
p
ag
atio
n
d
is
tan
ce
.
3
.
2
.
M
a
ny
-
o
bje
ct
iv
e
o
pti
m
iz
a
t
io
n
I
n
th
is
r
esear
ch
,
co
v
e
r
ag
e
c
r
iter
ia
f
o
r
test
ca
s
e
g
en
er
ati
o
n
a
r
e
m
o
d
eled
as
a
m
an
y
-
o
b
jectiv
e
o
p
tim
izatio
n
p
r
o
b
lem
,
wh
er
e
ea
ch
o
b
jectiv
e
r
ep
r
esen
ts
th
e
d
is
tan
ce
to
a
p
ar
ticu
lar
test
in
g
tar
g
et
in
th
e
class
u
n
d
er
e
x
am
in
atio
n
[
7
]
.
T
h
e
o
p
tim
izatio
n
p
r
o
ce
s
s
th
er
ef
o
r
e
s
ee
k
s
to
m
i
n
im
ize
th
ese
d
is
tan
ce
s
co
llectiv
ely
.
Acc
o
r
d
in
g
ly
,
th
e
f
o
llo
win
g
f
o
r
m
u
latio
n
is
ad
o
p
te
d
as f
o
llo
ws
:
Pro
b
lem
2
.
2
.
Ass
u
m
e
th
at
U
=
{u
1
,
…,
u
k
}
d
en
o
tes
th
e
s
et
o
f
co
v
e
r
ag
e
o
b
jectiv
es.
T
h
e
g
o
al
is
to
co
n
s
tr
u
ct
a
s
et
o
f
Par
eto
-
o
p
ti
m
al
test
ca
s
es
T
=
{t
1
,
…,
,
t
n
}
s
u
ch
th
at
th
e
f
itn
ess
v
alu
es
ass
o
ciate
d
with
all
tar
g
ets
u
1
, …, u
k
i.e
.
,
ar
e
m
in
im
ized
.
T
h
u
s
,
th
e
p
r
o
b
lem
ca
n
b
e
ex
p
r
ess
ed
as a
m
an
y
-
o
b
ject
iiv
e
p
r
o
b
lem
with
k
o
b
jectiv
es:
{
min
1
(
)
=
(
1
,
)
.
.
.
min
(
)
=
(
,
)
(
5
)
(
1
,
)
: D
is
tan
ce
o
f
test
ca
s
e
t
f
r
o
m
c
o
v
er
in
g
th
e
test
tar
g
et
.
{
1
,
…
,
}
: Co
r
r
esp
o
n
d
in
g
f
itn
ess
v
ec
to
r
.
Usi
n
g
th
e
g
e
n
er
alize
d
r
ef
o
r
m
u
latio
n
a
p
p
r
o
ac
h
,
m
u
ltip
le
co
v
er
a
g
e
c
r
iter
ia
in
clu
d
in
g
b
r
an
c
h
c
o
v
er
a
g
e,
s
tatem
en
t c
o
v
er
ag
e,
a
n
d
s
tr
o
n
g
m
u
tatio
n
c
o
v
er
a
g
e
ca
n
b
e
d
e
f
in
ed
ac
co
r
d
in
g
to
th
e
f
o
llo
win
g
f
o
r
m
u
latio
n
:
Pro
b
lem
2
.
3
.
L
et
B
=
{b
1
,
…,
b
k
}
wh
ich
is
s
et
o
f
b
r
an
ch
es
o
f
a
class
.
Fin
d
th
e
n
u
m
b
er
o
f
s
ets
o
f
n
o
n
-
d
o
m
in
an
t
test
ca
s
es
T
=
{t
1
,
…,
t
n
}
th
at
m
i
n
im
ize
th
e
f
itn
ess
f
u
n
ctio
n
f
o
r
all
test
ca
s
e
u
1
,
…,
u
k
i
n
clu
d
in
g
m
in
im
izin
g
o
b
jectiv
e
k
as f
o
ll
o
ws:
{
min
1
(
)
=
(
1
,
)
+
(
1
,
)
.
.
.
(
)
=
(
,
)
+
(
,
)
(
6
)
(
1
,
)
:
No
r
m
alize
d
b
r
an
c
h
d
is
tan
c
e
f
o
r
ea
ch
ex
ec
u
te
d
b
r
an
ch
cl
o
s
est
to
t
in
r
elatio
n
t
o
b
r
an
ch
in
r
elatio
n
to
b
r
an
c
h
(
i.e
.
,
th
o
s
e
with
t
h
e
m
in
im
u
m
co
n
tr
o
l
-
d
ep
e
n
d
en
cy
d
e
p
th
)
.
(
1
,
)
:
R
esp
ec
tiv
e
d
eg
r
ee
o
f
ap
p
r
o
x
im
atio
n
(
i.e
.
,
th
e
n
u
m
b
er
o
f
c
o
n
tr
o
l
d
ep
en
d
en
cies b
et
wee
n
th
e
clo
s
est ex
ec
u
ted
b
r
a
n
ch
an
d
).
Pro
b
lem
2
.
4
.
T
h
e
r
e
is
S
=
{S
1
,
…,
S
k
}
as
a
s
et
o
f
s
tatem
en
ts
in
th
e
class
.
Fin
d
th
e
n
u
m
b
er
o
f
s
ets
o
f
non
-
d
o
m
in
a
n
t
test
ca
s
es
T
=
{
t
1
,
…,
t
n
}
th
at
m
in
im
ize
th
e
f
it
n
ess
f
u
n
ctio
n
f
o
r
all
test
ca
s
es
u
1
,
…,
u
k
in
clu
d
in
g
m
in
im
izin
g
o
b
jectiv
e
k
as f
o
ll
o
ws:
{
min
1
(
)
=
(
1
,
)
+
(
(
1
)
,
)
.
.
.
min
(
)
=
(
,
)
+
(
(
)
,
)
(
7
)
(
(
)
,
)
:
No
r
m
alize
d
b
r
a
n
ch
d
is
tan
ce
b
etwe
en
test
ca
s
e
t
an
d
th
e
b
r
an
ch
clo
s
est
to
(
)
.
i.e
.
,
th
e
b
r
an
ch
co
n
tr
o
llin
g
t
h
e
ex
ec
u
ti
o
n
o
f
s
tatem
en
t
.
(
,
)
: Rep
r
esen
ts
th
e
co
r
r
esp
o
n
d
in
g
ap
p
r
o
x
im
atio
n
lev
e
l.
Pro
b
lem
2
.
5
.
T
h
er
e
is
M
=
{
1
,
…,
}
as
a
s
et
o
f
m
u
ta
n
t
o
f
th
e
class
.
Fin
d
a
s
et
o
f
n
o
n
-
d
o
m
i
n
ated
test
ca
s
e
f
r
o
m
T =
{t
1
, …,
t
n
}
wh
ich
m
in
im
ize
f
itn
ess
f
u
n
cti
o
n
f
o
r
all
ev
er
y
m
u
tan
t
m
1
,
…,
m
k
as f
o
llo
ws:
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
A
u
to
-
g
e
n
era
ted
u
n
it testi
n
g
u
s
in
g
P
C
A
-
a
Dyn
a
MOS
A
(
Ma
d
e
R
a
ja
A
d
i
S
u
r
ya
S
a
p
u
tr
a
)
237
{
min
1
(
)
=
(
1
,
)
+
(
(
1
)
,
)
+
(
1
,
)
+
(
1
,
)
.
.
.
min
(
)
=
(
,
)
+
(
(
)
,
)
+
(
,
)
+
(
,
)
(
8
)
(
(
1
)
,
)
: N
o
r
m
alize
d
b
r
a
n
ch
d
is
tan
ce
an
d
ap
p
r
o
x
i
n
atio
n
lev
el
o
f
test
ca
s
e
t
f
o
r
m
u
ta
n
t
.
(
,
)
:
I
n
f
ec
tio
n
d
is
tan
ce
.
(
,
)
: Pr
o
p
ag
atio
n
d
is
tan
ce
.
3
.
3
.
P
CA
a
lg
o
rit
hm
PC
A
is
a
m
u
ltiv
ar
iate
s
tatis
ti
ca
l
m
eth
o
d
d
esig
n
e
d
to
an
aly
ze
tab
u
lar
d
ata
in
wh
i
ch
o
b
s
e
r
v
atio
n
is
ch
ar
ac
ter
ized
b
y
m
u
ltip
le
co
r
r
elate
d
q
u
an
titativ
e
v
ar
iab
les
[
1
5
]
.
T
h
e
p
r
im
ar
y
o
b
jectiv
e
o
f
PC
A
i
s
to
ex
tr
ac
t
th
e
m
o
s
t
in
f
o
r
m
ativ
e
s
tr
u
ctu
r
e
f
r
o
m
th
e
d
ataset
b
y
tr
an
s
f
o
r
m
in
g
th
e
o
r
ig
in
al
co
r
r
elate
d
v
ar
iab
les
in
to
a
n
ew
s
et
o
f
m
u
tu
ally
o
r
th
o
g
o
n
ak
v
ar
iab
les,
k
n
o
wn
as
p
r
in
ci
p
al
co
m
p
o
n
en
ts
.
T
h
ese
co
m
p
o
n
en
t
s
ca
p
tu
r
e
d
o
m
in
a
n
t
v
ar
ian
ce
p
atter
n
s
an
d
r
e
v
ea
l similar
ity
s
tr
u
ctu
r
es a
m
o
n
g
o
b
s
er
v
atio
n
s
.
I
n
th
is
s
tu
d
y
,
PC
A
is
ap
p
lied
to
ex
am
in
e
a
n
d
r
e
d
u
ce
th
e
n
u
m
b
er
o
f
co
v
e
r
ag
e
o
b
jectiv
es
in
v
o
lv
e
d
in
th
e
o
p
tim
izatio
n
p
r
o
ce
s
s
.
B
y
an
aly
zin
g
th
e
r
elatio
n
s
h
ip
s
am
o
n
g
th
e
o
b
jectiv
e
f
itn
ess
v
alu
e
s
,
r
ed
u
n
d
a
n
t
o
r
less
in
f
o
r
m
ativ
e
o
b
jectiv
es
in
th
e
h
ig
h
-
d
im
e
n
s
io
n
al
o
b
jectiv
e
s
p
ac
e
ca
n
b
e
id
en
tifie
d
a
n
d
r
em
o
v
ed
.
T
h
is
d
im
en
s
io
n
ality
r
ed
u
ctio
n
p
r
o
ce
s
s
aim
s
to
s
im
p
lify
th
e
m
an
y
-
o
b
jectiv
e
test
ca
s
e
g
en
er
atio
n
p
r
o
b
lem
wh
ile
p
r
eser
v
in
g
th
e
m
o
s
t
r
elev
an
t
in
f
o
r
m
atio
n
[
1
4
]
.
T
h
e
m
ain
ad
v
an
tag
es
o
f
ap
p
l
y
in
g
PC
A
in
th
is
co
n
tex
t
in
clu
d
es:
−
E
lim
in
atin
g
r
ed
u
n
d
a
n
t f
ea
tu
r
e
ch
ar
ac
ter
is
tics
with
in
th
e
o
b
je
ctiv
e
s
p
ac
e;
−
R
ed
u
cin
g
co
m
p
u
tatio
n
al
c
o
m
p
lex
ity
an
d
e
n
h
an
cin
g
th
e
e
f
f
icien
cy
o
f
th
e
s
ea
ch
p
r
o
ce
s
s
; a
n
d
−
Pre
s
er
v
in
g
th
e
m
o
s
t c
r
itical
co
v
er
ag
e
o
b
jectiv
es.
Fro
m
a
m
ath
em
atica
l
s
tan
d
p
o
i
n
t,
PC
A
p
er
f
o
r
m
s
d
i
m
en
s
io
n
a
lity
r
ed
u
ctio
n
b
y
p
r
o
jectin
g
th
e
o
r
ig
in
al
o
b
jectiv
e
s
p
ac
e
in
t
o
a
n
ew
s
e
t
o
f
o
r
th
o
g
o
n
al
co
o
r
d
in
ates
.
E
ac
h
d
im
e
n
s
io
n
r
e
p
r
esen
ts
an
o
b
jectiv
e,
an
d
th
e
tr
an
s
f
o
r
m
atio
n
is
g
u
id
ed
b
y
v
ar
ian
ce
m
a
x
im
izatio
n
.
C
o
m
p
o
n
en
ts
ass
o
ciate
d
with
lar
g
er
v
ar
ian
ce
v
al
u
es
ar
e
co
n
s
id
er
ed
to
c
o
n
tain
m
o
r
e
s
ig
n
if
ican
t
in
f
o
r
m
atio
n
.
T
h
er
ef
o
r
e,
th
e
p
r
in
cip
al
co
m
p
o
n
en
ts
ar
e
s
elec
ted
ac
co
r
d
in
g
to
th
e
d
escen
d
in
g
o
r
d
er
o
f
t
h
eir
v
a
r
ian
ce
.
T
h
e
f
ir
s
t
p
r
i
n
cip
al
co
m
p
o
n
en
t
is
d
ef
in
ed
as
th
e
d
ir
ec
tio
n
th
at
m
ax
im
izes
d
ata
v
a
r
ian
ce
.
S
u
b
s
eq
u
en
t
co
m
p
o
n
en
ts
ar
e
s
elec
ted
s
u
ch
th
at
th
ey
ar
e
o
r
th
o
g
o
n
al
to
p
r
ev
io
u
s
ly
ch
o
s
en
co
m
p
o
n
e
n
ts
an
d
m
a
x
im
ize
th
e
r
em
ain
in
g
v
ar
ia
n
ce
.
T
h
is
iter
ativ
e
p
r
o
ce
s
s
co
n
tin
u
es
u
n
t
il
a
r
ed
u
ce
d
co
o
r
d
in
ate
s
p
a
ce
is
co
n
s
tr
u
cted
.
Dim
en
s
io
n
s
ass
o
ciate
d
with
z
er
o
v
ar
ian
ce
ar
e
d
is
ca
r
d
ed
,
as
th
ey
d
o
n
o
t
co
n
tr
i
b
u
te
m
ea
n
in
g
f
u
l
i
n
f
o
r
m
atio
n
to
th
e
tr
an
s
f
o
r
m
e
d
s
p
ac
e.
3
.
4
.
M
a
ny
-
o
bje
ct
iv
e
s
ea
rc
h
Ov
er
th
e
p
ast
d
ec
ad
e,
co
n
s
id
e
r
ab
le
atten
tio
n
h
as
b
ee
n
d
e
v
o
t
ed
to
th
e
p
r
o
b
lem
o
f
au
to
m
ate
d
test
d
ata
g
en
er
atio
n
[
5
]
,
[
1
6
]
,
p
a
r
ticu
lar
ly
with
th
e
o
b
jectiv
e
o
f
ac
h
ie
v
in
g
h
ig
h
lev
els
o
f
co
d
e
co
v
er
ag
e
u
n
d
er
d
if
f
er
e
n
t
co
v
er
ag
e
m
et
r
ics
s
u
ch
as
b
r
an
ch
[
1
7
]
,
s
tatem
en
t
[
1
6
]
,
a
n
d
m
eth
o
d
co
v
er
a
g
e
[
1
8
]
.
A
m
o
n
g
th
e
p
r
o
p
o
s
ed
tech
n
iq
u
es,
s
ea
r
ch
-
b
ased
a
p
p
r
o
ac
h
es
esp
ec
ially
GAs
[
1
9
]
h
av
e
d
em
o
n
s
tr
ated
s
tr
o
n
g
p
o
te
n
tial
in
au
to
m
atin
g
th
is
p
r
o
ce
s
s
[
5
]
.
E
x
is
tin
g
m
e
th
o
d
s
g
en
er
ally
f
all
in
to
two
m
ain
ca
teg
o
r
ies:
s
in
g
le
-
tar
g
et
an
d
m
u
lti
-
tar
g
e
t
f
o
r
m
u
latio
n
s
.
I
n
s
in
g
le
-
tar
g
et
ap
p
r
o
ac
h
es,
ev
o
lu
tio
n
a
r
y
alg
o
r
ith
m
s
attem
p
t
to
o
p
tim
ize
o
n
e
co
v
er
ag
e
g
o
al
at
a
tim
e.
E
ac
h
tar
g
et,
s
u
ch
as
a
s
p
ec
if
ic
b
r
an
c
h
,
is
tr
an
s
l
ated
in
to
a
f
itn
ess
f
u
n
ctio
n
th
at
e
v
alu
ates
h
o
w
clo
s
e
a
g
en
er
ated
test
ca
s
e
o
r
test
s
u
i
te
is
to
s
ati
s
f
y
in
g
th
at
tar
g
et
[
1
6
]
.
T
h
is
p
r
o
x
im
ity
is
ty
p
ical
ly
m
ea
s
u
r
ed
u
s
in
g
two
wh
ite
-
b
o
x
h
eu
r
is
tics
,
n
am
ely
th
e
ap
p
r
o
ac
h
le
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eq
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Fra
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d
A
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[
2
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]
in
tr
o
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ce
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[
2
1
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Pan
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[
1
1
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later
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SA,
a
m
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GA
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y
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Ho
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ter
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s
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2
2
]
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E
ac
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f
an
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te
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id
er
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is
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th
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te
x
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First,
test
ca
s
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s
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o
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ld
r
em
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cise,
as
ex
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s
s
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d
m
ay
p
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test
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d
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o
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tio
n
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th
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p
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s
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er
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y
im
p
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v
in
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d
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ated
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e
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s
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th
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3
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5
.
Co
ntr
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l f
lo
w
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a
ph
(
CF
G
)
T
h
e
C
FG
m
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e
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n
n
in
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s
s
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av
io
r
o
f
a
p
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g
r
am
b
y
r
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r
esen
tin
g
th
e
p
o
ten
tial
p
ath
s
th
at
m
ay
b
e
tr
av
er
s
ed
d
u
r
in
g
r
u
n
tim
e.
B
ased
o
n
th
is
r
ep
r
esen
tatio
n
,
d
if
f
er
e
n
t
co
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ag
e
o
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v
es
ca
n
b
e
f
o
r
m
ally
d
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a
n
d
ev
al
u
ated
.
3
.
6
.
T
est
s
uite
s
a
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t
est
ca
s
es
A
test
s
u
ite
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ep
r
esen
ts
a
co
lle
ctio
n
o
f
test
ca
s
es
d
esig
n
ed
to
ass
e
s
s
th
e
b
eh
av
io
r
o
f
a
p
r
o
g
r
am
.
E
ac
h
test
ca
s
e
is
co
m
p
o
s
ed
o
f
a
s
eq
u
en
ce
o
f
m
eth
o
d
ca
lls
with
v
ar
iab
le
len
g
th
s
.
I
n
s
in
g
l
e
-
o
b
jectiv
e
s
ea
r
ch
tech
n
iq
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es,
a
s
ep
ar
ate
test
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s
e
is
p
r
o
d
u
ce
d
f
o
r
ea
c
h
test
in
g
o
b
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e.
T
h
e
r
esu
ltin
g
test
ca
s
es
ar
e
s
u
b
s
eq
u
en
tly
co
m
b
in
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to
co
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s
tr
u
ct
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co
m
p
r
e
h
en
s
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e
test
s
u
ite
f
o
r
test
in
g
th
e
wh
o
le
p
r
o
g
r
a
m
.
3
.
7
.
O
bje
c
t
iv
es t
o
be
co
v
er
e
d
T
h
e
o
b
jectiv
es
in
v
o
lv
e
d
in
p
r
o
g
r
am
ev
alu
atio
n
ca
n
b
e
ass
ess
ed
u
s
in
g
v
ar
io
u
s
c
o
v
er
a
g
e
m
etr
ics,
in
clu
d
in
g
d
if
f
e
r
en
t
co
v
er
ag
e
m
ea
s
u
r
es,
n
am
ely
lin
e,
b
r
an
c
h
,
m
u
tatio
n
,
a
n
d
m
et
h
o
d
co
v
e
r
ag
e
m
etr
ics
.
I
n
th
is
s
tu
d
y
,
th
e
e
v
alu
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n
is
lim
ited
to
th
r
ee
s
p
ec
if
ic
cr
it
er
i
a:
lin
e
,
b
r
a
n
ch
,
an
d
m
u
tati
o
n
co
v
er
ag
e.
T
h
e
p
er
f
o
r
m
an
ce
in
d
icato
r
s
u
tili
ze
d
in
th
e
aDy
n
aM
OSA
ap
p
r
o
ac
h
ar
e
s
u
m
m
ar
ize
d
in
T
a
b
le
1
.
T
ab
le
1
.
Per
f
o
r
m
an
ce
in
d
icato
r
ID
P
e
r
f
o
r
ma
n
c
e
i
n
d
i
c
a
t
o
r
D
e
scri
p
t
i
o
n
I1
Ex
e
c
u
t
e
d
l
o
o
p
c
o
u
n
t
I
n
d
i
c
a
t
e
s
t
h
e
t
o
t
a
l
n
u
m
b
e
r
o
f
t
h
e
l
o
o
p
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t
e
r
a
t
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o
n
s
t
h
a
t
w
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r
e
p
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r
f
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me
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d
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r
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n
g
t
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e
e
x
e
c
u
t
i
o
n
o
f
t
h
e
t
e
st
c
a
s
e
s.
I2
M
e
t
h
o
d
c
o
v
e
r
a
g
e
c
o
u
n
t
R
e
p
r
e
se
n
t
s
t
h
e
n
u
m
b
e
r
o
f
d
i
s
t
i
n
c
t
m
e
t
h
o
d
s
t
h
a
t
w
e
r
e
i
n
v
o
l
v
e
d
b
y
t
h
e
g
e
n
e
r
a
t
e
d
t
e
st
c
a
ses
.
I3
To
t
a
l
me
t
h
o
d
c
a
l
l
s
i
n
t
e
st
s
R
e
f
l
e
c
t
s t
h
e
p
v
e
r
a
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n
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m
b
e
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f
met
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d
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a
t
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n
s
o
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c
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r
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g
a
c
c
r
o
ss
a
l
l
e
x
e
c
u
t
e
d
t
e
st
c
a
ses
.
I4
O
b
j
e
c
t
i
n
st
a
n
t
i
a
t
i
o
n
c
o
u
n
t
S
h
o
w
s
h
o
w
m
a
y
o
b
j
e
c
t
s wer
e
c
r
e
a
t
e
d
d
u
r
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n
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t
h
e
e
x
e
c
u
t
i
o
n
o
f
t
h
e
t
e
st
su
i
t
e
.
I5
C
o
v
e
r
e
d
st
a
t
e
m
e
n
t
s
R
e
p
r
e
se
n
t
s
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o
w
m
a
n
y
st
a
t
e
m
e
n
t
s
i
n
t
h
e
c
o
d
e
w
e
r
e
a
c
t
u
a
l
l
y
c
o
v
e
r
e
d
.
I6
Te
st
c
a
s
e
s
t
a
t
e
m
e
n
t
s
To
t
a
l
n
u
m
b
e
r
o
f
e
x
e
c
u
t
a
b
l
e
s
t
a
t
e
m
e
n
t
s wit
h
i
n
a
l
l
g
e
n
e
r
a
t
e
d
t
e
s
t
c
a
ses
.
I7
Te
st
l
e
n
g
t
h
A
v
e
r
a
g
e
l
e
n
g
t
h
o
f
t
e
st
c
a
ses
i
n
t
e
r
ms
o
f
me
t
h
o
d
c
a
l
l
s
e
q
u
e
n
c
e
s.
T
h
e
p
r
o
p
o
s
ed
p
er
f
o
r
m
a
n
ce
in
d
icato
r
s
en
ab
le
th
e
ev
al
u
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o
f
h
o
w
ef
f
ec
tiv
ely
th
e
PC
A
-
aDy
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aM
OSA
alg
o
r
ith
m
p
er
f
o
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m
s
co
m
p
ar
ed
with
th
e
b
as
elin
e
aDy
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m
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d
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Fo
r
ex
am
p
le,
h
ig
h
e
r
v
alu
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f
co
v
e
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ed
m
eth
o
d
(
I
2
)
an
d
co
v
er
ed
s
tatem
en
ts
(
I
5
)
g
en
er
ally
r
e
f
lect
s
tr
o
n
g
e
r
c
o
v
er
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p
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wh
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s
lo
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n
u
m
b
er
s
o
f
te
s
t
ca
s
e
s
tatem
en
ts
(
I
6
)
an
d
s
h
o
r
ter
test
len
g
th
s
(
I
7
)
in
d
icate
m
o
r
e
co
n
cise
an
d
ef
f
icien
t
test
s
.
B
y
ap
p
ly
in
g
th
ese
in
d
icato
r
s
d
u
r
in
g
ex
p
e
r
im
en
tal
an
aly
s
is
,
th
e
s
tu
d
y
is
ab
le
to
ex
am
i
n
e
th
e
b
alan
ce
b
etwe
en
test
in
g
t
h
o
r
o
u
g
h
n
ess
an
d
ef
f
icien
cy
,
th
e
r
eb
y
p
r
o
v
id
in
g
in
s
ig
h
ts
in
t
o
th
e
s
ca
lab
ilit
y
an
d
p
r
ac
tical
ap
p
licab
ilit
y
o
f
th
e
p
r
o
p
o
s
ed
a
p
p
r
o
ac
h
.
3
.
8
.
B
ra
nch c
o
v
er
a
g
e
B
r
an
ch
co
v
er
a
g
e
r
ef
er
s
to
d
e
cisi
o
n
p
o
in
ts
in
th
is
p
r
o
f
r
am
,
s
u
ch
as
if
,
wh
ile
,
o
r
s
im
ila
r
co
n
d
itio
n
al
co
n
s
tr
u
cts.
W
h
itin
th
e
C
FG,
t
h
ese
d
ec
is
io
n
p
o
in
ts
ar
e
r
ep
r
e
s
en
ted
as
n
o
d
es
th
at
ty
p
ically
co
n
tain
at
least
to
w
o
u
tg
o
in
g
ed
g
ed
.
E
ac
h
o
u
tg
o
in
g
ed
g
e
co
r
r
esp
o
n
d
s
to
a
p
o
s
s
ib
le
b
r
an
ch
o
f
e
x
ec
u
tio
n
,
m
ea
n
in
g
th
at
s
in
g
le
n
o
d
e
m
ay
lead
to
m
u
ltip
le
alt
er
n
ativ
e
p
ath
s
.
T
h
e
d
e
g
r
ee
to
wh
ich
a
test
ca
s
e
t
co
v
er
s
a
b
r
an
c
h
b
ca
n
b
e
q
u
an
tifie
d
u
s
in
g
th
e
f
o
ll
o
win
g
f
itn
ess
s
f
o
r
m
u
latio
n
:
(
)
=
(
,
)
+
(
,
)
(
9
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
A
u
to
-
g
e
n
era
ted
u
n
it testi
n
g
u
s
in
g
P
C
A
-
a
Dyn
a
MOS
A
(
Ma
d
e
R
a
ja
A
d
i
S
u
r
ya
S
a
p
u
tr
a
)
239
(
,
)
:
T
h
e
s
tr
u
ct
u
r
al
d
is
tan
ce
b
etw
ee
n
th
e
b
r
a
n
ch
ex
ec
u
ted
b
y
te
s
t
ca
s
e
t
an
d
th
e
tar
g
et
b
r
an
c
h
th
at
m
u
s
t
b
e
co
v
er
e
d
.
T
h
e
d
is
tan
ce
(
,
)
co
r
r
esp
o
n
d
s
to
th
e
to
tal
c
o
u
n
t
o
f
co
n
tr
o
l
d
e
p
en
d
e
n
cies
o
r
ed
g
e
d
s
ep
ar
atin
g
d
ec
is
io
n
n
o
d
es
in
th
e
C
FG.
Fu
r
th
er
m
o
r
e,
th
e
b
r
a
n
ch
d
is
tan
ce
ca
n
b
e
d
eter
m
in
e
d
u
s
in
g
th
e
f
o
ll
o
win
g
f
o
r
m
u
latio
n
:
I
t
is
eq
u
al
to
th
e
n
u
m
b
er
o
f
co
n
tr
o
l
d
e
p
en
d
e
n
cies
o
r
ed
g
es
b
etwe
en
b
r
a
n
ch
n
o
d
es
in
th
e
C
FG.
Mo
r
eo
v
er
,
(
,
)
is
th
e
b
r
an
ch
d
is
tan
ce
,
wh
ich
ca
n
b
e
ca
lcu
lated
b
y
th
e
f
o
llo
win
g
f
o
r
m
u
la:
(
,
)
=
{
0
1
(
∈
,
)
(
∈
,
)
+
1
(
1
0
)
(
∈
,
)
:
R
ep
r
esen
ts
th
e
m
i
n
im
ized
n
o
n
-
n
o
r
m
alize
d
d
is
tan
ce
.
Sin
c
e
a
d
ec
is
io
n
s
tatem
en
t
n
o
r
m
a
lly
h
as
two
p
o
s
s
ib
le
o
u
tco
m
es,
t
h
e
p
r
e
d
icate
m
ay
b
e
ex
ec
u
te
d
m
u
ltip
le
tim
es
d
u
r
i
n
g
test
in
g
,
a
n
d
t
h
e
s
m
allest
co
m
p
u
ted
d
is
tan
ce
v
alu
e
is
s
elec
ted
d
u
r
in
g
e
x
ec
u
tio
n
.
3
.
9
.
L
ine c
o
v
er
a
g
e
I
n
a
C
FG r
ep
r
esen
tatio
n
,
ea
ch
n
o
d
e
co
r
r
esp
o
n
d
s
to
a
s
p
ec
if
ic
lin
e
o
r
b
lo
ck
o
f
p
r
o
g
r
am
c
o
d
e
.
T
h
e
lin
e
co
v
er
ag
e
ac
h
iev
ed
b
y
a
test
ca
s
e
t
ca
n
th
er
ef
o
r
e
b
e
f
o
r
m
u
lated
u
s
in
g
th
e
f
o
llo
win
g
f
itn
ess
f
u
n
ctio
n
:
(
)
=
(
,
)
+
(
(
)
,
)
(
11
)
(
,
)
:
I
n
d
icate
s
th
e
s
tr
u
ctu
r
al
d
is
tan
ce
b
etwe
en
p
r
o
g
r
a
m
s
tatem
en
ts
,
an
d
(
(
)
,
)
:
R
ep
r
esen
ts
t
h
e
d
is
tan
ce
f
r
o
m
th
e
b
r
a
n
ch
ex
ec
u
ted
b
y
test
ca
s
e
t
to
th
e
n
ea
r
e
s
t b
r
an
ch
r
elativ
e
to
th
e
tar
g
et
m
u
tatio
n
.
3
.
1
0
.
M
uta
t
io
n c
o
v
er
a
g
e
Mu
tatio
n
test
in
g
is
p
er
f
o
r
m
e
d
b
y
in
t
r
o
d
u
cin
g
s
m
all
ar
tifi
cial
m
o
d
if
icatio
n
s
in
to
th
e
s
o
u
r
ce
co
d
e
th
r
o
u
g
h
s
et
o
f
m
u
tatio
n
o
p
e
r
a
to
r
s
.
T
h
ese
ch
an
g
es
s
im
u
late
p
o
ten
tial
f
au
lts
th
at
m
ay
o
cc
u
r
in
r
ea
l
p
r
o
g
r
a
m
s
.
T
h
e
m
u
tate
d
v
e
r
s
io
n
s
o
f
th
e
p
r
o
g
r
a
m
ar
e
g
e
n
er
ated
b
y
ap
p
ly
in
g
m
u
tatio
n
o
p
er
ato
r
s
to
s
elec
ted
lo
ca
tio
n
s
in
th
e
C
FG o
f
th
e
o
r
ig
in
al
s
o
u
r
ce
co
d
e.
I
n
th
is
s
tu
d
y
,
s
ev
er
al
m
u
tatio
n
o
p
er
ato
r
s
ar
e
em
p
lo
y
ed
,
in
clu
d
in
g
b
ar
ia
b
le
r
ep
lace
m
e
n
t,
u
n
ar
y
o
p
er
ato
r
in
s
er
tio
n
,
co
n
s
tan
t
s
u
b
s
titu
tio
n
,
an
d
ar
ith
m
etic
o
p
er
ato
r
r
ep
lace
m
en
t.
B
y
ex
ec
u
tin
g
th
e
s
a
m
e
test
ca
s
es
o
n
b
o
th
o
r
ig
in
al
a
n
d
m
u
tated
p
r
o
g
r
am
s
,
d
if
f
er
e
n
ce
s
in
th
e
r
esu
ltin
g
o
u
tp
u
ts
ca
n
b
e
o
b
s
er
v
e
d
.
I
f
th
e
b
eh
av
io
r
o
f
th
e
m
u
tated
p
r
o
g
r
am
d
if
f
er
s
f
r
o
m
th
e
o
r
ig
in
al
p
r
o
g
r
a
m
,
th
e
m
u
tan
t
is
co
n
s
id
er
ed
d
etec
ted
(
o
r
k
illed
)
.
T
h
e
m
u
tatio
n
c
o
v
er
a
g
e
o
f
tes
t c
ase
t
is
th
en
ev
alu
ate
d
u
s
in
g
th
e
f
o
llo
win
g
f
itn
ess
f
o
r
m
u
latio
n
:
(
)
=
(
,
)
+
(
(
)
,
)
+
(
,
)
+
(
,
)
(
1
2
)
(
,
)
:
Den
o
tes
th
e
s
tr
u
ctu
r
al
d
is
tan
ce
b
etwe
en
t
h
e
p
r
o
g
r
a
m
s
tatem
en
t
ex
ec
u
ted
b
y
test
ca
s
e
t
an
d
th
e
lo
ca
tio
n
o
f
t
h
e
m
u
tated
s
tate
m
en
t.
(
(
)
,
)
:
I
n
d
icate
s
th
e
n
o
r
m
aliz
ed
b
r
an
c
h
d
is
tan
ce
ass
o
ciate
d
with
th
e
m
u
tated
b
r
a
n
ch
.
(
,
)
: Rep
r
esen
ts
th
e
in
f
ec
tio
n
d
is
tan
ce
.
(
,
)
: Ref
er
s
to
th
e
p
r
o
p
ag
atio
n
d
is
tan
ce
.
3
.
1
1
.
T
est
ca
s
e
g
ener
a
t
io
n und
er
m
ultiple o
ptim
iza
t
io
n o
bje
ct
iv
es
I
n
au
t
o
m
ated
test
ca
s
e
g
e
n
er
a
tio
n
,
two
p
r
im
ar
y
co
n
s
id
er
atio
n
s
ar
e
t
y
p
ically
a
d
d
r
ess
ed
:
m
in
im
izin
g
th
e
n
u
m
b
er
o
f
s
tatem
en
ts
with
in
ea
ch
test
ca
s
e
wh
ile
s
im
u
ltan
eo
u
s
ly
m
ax
im
izin
g
th
e
co
v
er
ag
e
ac
h
ie
v
ed
b
y
th
e
g
en
e
r
ated
test
s
.
Dif
f
er
e
n
t
co
v
er
a
g
e
c
r
iter
ia
ca
n
b
e
u
s
ed
to
ev
alu
ate
t
h
e
ad
e
q
u
ac
y
o
f
a
test
s
u
ite.
E
ac
h
cr
iter
io
n
ca
n
b
e
t
r
ea
ted
as
a
s
ep
ar
ate
o
p
tim
izatio
n
o
b
jectiv
e,
allo
win
g
t
h
e
test
g
en
e
r
a
tio
n
p
r
o
b
lem
t
o
b
e
m
o
d
eled
as a
m
a
n
y
-
o
b
jectiv
e
o
p
tim
izatio
n
task
.
Ass
u
m
e
th
at
th
e
test
ed
p
r
o
g
r
a
m
co
n
tain
s
m
co
v
er
ag
e
test
s
,
wh
ich
co
n
s
is
ts
o
f
o
b
jectiv
es
r
elate
d
to
b
r
an
ch
co
v
e
r
ag
e,
o
b
jectiv
es
ass
o
ciate
d
with
lin
e
co
v
er
a
g
e,
an
d
o
b
jectiv
es
r
ep
r
esen
ti
n
g
m
u
tatio
n
co
v
er
ag
e.
He
n
ce
th
e
to
tal
n
u
m
b
er
o
f
o
b
jectiv
es
is
g
iv
e
n
b
y
m
=
+
+
.
Fo
r
a
test
s
u
ite
T
=
{
1
,
2
,
…
,
}
,
th
e
g
o
al
o
f
th
e
o
p
tim
izat
io
n
p
r
o
ce
s
s
is
to
m
in
im
ize
th
e
f
itn
ess
v
alu
e
ass
o
ciate
d
with
all
o
b
jectiv
es:
{
min
(
)
(
=
1
,
2
,
…
,
)
min
(
)
(
=
1
,
2
,
…
,
)
min
(
)
(
=
1
,
2
,
…
,
)
(
13
)
3
.
1
2
.
P
CA
a
lg
o
rit
h
m
T
o
g
en
er
ate
e
f
f
ec
tiv
e
test
ca
s
es,
PC
A
i
s
ap
p
lied
to
r
ed
u
ce
t
h
e
d
im
en
s
io
n
ality
o
f
th
e
o
b
jectiv
e
s
p
ac
e
b
y
r
em
o
v
in
g
r
e
d
u
n
d
an
t
in
f
o
r
m
atio
n
wh
ile
p
r
eser
v
in
g
th
e
m
o
s
t
s
ig
n
if
ican
t
co
m
p
o
n
e
n
ts
.
T
h
e
r
esu
ltin
g
r
ed
u
ce
d
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
4
3
,
No
.
1
,
Ju
ly
20
2
6
:
233
-
24
9
240
o
b
jectiv
e
s
et
is
th
en
u
tili
ze
d
d
u
r
in
g
t
h
e
m
an
y
-
o
b
jectiv
e
s
o
r
tin
g
p
r
o
ce
s
s
o
f
ca
n
d
id
ate
s
o
lu
tio
n
s
with
in
th
e
p
o
p
u
latio
n
,
g
u
id
in
g
t
h
e
ev
o
l
u
tio
n
ar
y
s
ea
r
c
h
.
B
y
ap
p
ly
in
g
th
is
d
im
en
s
io
n
ality
r
e
d
u
ct
io
n
s
tr
ag
eth
y
,
th
e
d
eg
r
ad
atio
n
in
s
ea
r
ch
p
er
f
o
r
m
an
ce
o
f
te
n
o
b
s
er
v
ed
in
aD
y
n
aM
OSA
wh
en
d
ea
lin
g
with
a
lar
g
e
n
u
m
b
er
o
f
o
p
tim
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n
o
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jectiv
es c
an
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e
m
itig
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.
Fig
u
r
e
1
p
r
esen
ts
th
e
s
eq
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tial
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r
k
f
lo
w
o
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e
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A
p
r
o
ce
s
s
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s
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ed
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ce
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d
im
en
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io
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o
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th
e
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jectiv
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s
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r
e
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in
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ac
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ir
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itial
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e
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lete
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et
o
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aw
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jectiv
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ated
f
r
o
m
th
e
test
ca
s
e
o
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tim
izatio
n
p
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o
ce
s
s
.
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o
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tain
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,
th
e
alg
o
r
ith
m
ex
tr
ac
ts
th
e
f
itn
ess
m
atr
ix
f
,
w
h
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ep
r
esen
t
s
th
e
ev
alu
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n
s
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r
es o
f
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ch
iin
d
iv
id
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al
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r
elatio
n
to
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e
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e
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o
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Fig
u
r
e
1
.
Ov
e
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v
iew
o
f
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PC
A
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d
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r
e
T
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e
f
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ess
m
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en
n
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alize
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to
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o
d
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ce
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atr
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en
s
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r
in
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s
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e
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m
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ar
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le
n
u
m
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ical
s
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g
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with
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o
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o
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tio
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ately
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m
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atin
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s
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B
ased
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Fro
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a
tr
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r
r
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s
h
ip
s
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s
s
o
b
jectiv
es.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
A
u
to
-
g
e
n
era
ted
u
n
it testi
n
g
u
s
in
g
P
C
A
-
a
Dyn
a
MOS
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(
Ma
d
e
R
a
ja
A
d
i
S
u
r
ya
S
a
p
u
tr
a
)
241
Usi
n
g
t
h
e
co
r
r
elatio
n
m
atr
i
x
,
th
e
eig
en
v
al
u
es
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to
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o
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m
in
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f
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o
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th
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PC
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tr
an
s
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o
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m
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s
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b
s
eq
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tly
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o
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ith
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ates
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etain
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ig
h
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t
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s
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y
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m
o
s
t
m
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g
f
u
l
in
f
o
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m
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.
On
ly
p
r
in
cip
al
co
m
p
o
n
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ts
w
ith
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ig
n
i
f
ican
t
c
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ib
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tio
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etain
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ter
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ality
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ed
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.
Fin
ally
,
th
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alg
o
r
ith
m
r
etu
r
n
s
th
e
r
ed
u
ce
d
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et
o
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o
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wh
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th
e
o
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ig
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n
al
f
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l
l
o
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d
u
r
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g
th
e
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o
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tio
n
ar
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r
ch
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ase.
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y
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g
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ed
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n
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a
n
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d
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ig
h
ly
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r
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o
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ile
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r
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g
t
h
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o
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t
in
f
o
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ati
v
e
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ce
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A
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n
tr
ib
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tes
to
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ed
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ci
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g
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o
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ith
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lex
ity
m
im
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ch
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th
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g
e
m
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y
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o
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jectiv
e
o
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tim
izatio
n
s
p
ac
es.
Sin
ce
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to
m
ated
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s
e
g
en
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atio
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o
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ten
in
v
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lar
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m
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s
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ly
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ality
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ately
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ay
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ch
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s
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m
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er
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es
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th
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g
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p
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f
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n
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atin
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ap
p
r
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h
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3
.
1
3
.
E
x
perim
ent
a
l desig
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T
h
e
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p
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im
en
tal
s
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d
y
was
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ied
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t
to
in
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tig
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e
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o
llo
win
g
r
esear
ch
q
u
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n
s
(
R
Qs)
co
n
ce
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n
in
g
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cr
iter
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ad
ap
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e
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y
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jectiv
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test
ca
s
e
g
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er
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.
R
Q1
.
T
o
w
h
at
ex
ten
t
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th
e
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ize
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f
o
b
jectiv
e
g
r
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p
s
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n
f
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en
ce
th
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s
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r
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h
p
e
r
f
o
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m
an
ce
o
f
th
e
PC
A
-
aDy
n
aM
OSA
alg
o
r
ith
m
?
Mo
r
eo
v
e
r
,
h
o
w
ca
n
th
e
o
p
t
im
al
n
u
m
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er
o
f
g
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o
u
p
s
f
o
r
th
e
alg
o
r
ith
m
b
e
d
eter
m
in
ed
?
Fig
u
r
e
2
illu
s
tr
ates
th
e
p
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c
ed
u
r
al
wo
r
k
f
lo
w
o
f
th
e
p
r
o
p
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s
ed
PC
A
-
b
ased
ap
p
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o
ac
h
f
o
r
m
a
n
y
-
o
b
jectiv
e
test
ca
s
e
g
en
er
atio
n
.
T
h
e
p
r
o
ce
s
s
b
eg
in
s
b
y
in
itiali
zin
g
a
s
et
o
f
o
b
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es
∗
alo
n
g
s
id
e
a
ca
n
d
id
ate
p
o
p
u
latio
n
P.
On
ce
in
itialized
,
th
e
alg
o
r
ith
m
p
r
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c
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d
s
b
y
g
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o
u
p
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g
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o
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in
to
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s
ter
s
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ased
o
n
s
im
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ity
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r
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r
al
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elat
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s
h
ip
s
.
E
ac
h
o
b
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e
g
r
o
u
p
∗
[
]
is
th
e
n
in
d
ep
en
d
en
tly
p
r
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ce
s
s
ed
th
r
o
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d
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ality
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ase
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s
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g
PC
A.
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h
is
s
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an
s
f
o
r
m
s
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ch
g
r
o
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p
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es
in
to
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u
ce
d
o
b
j
ec
tiv
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s
et
[
]
,
r
etain
in
g
o
n
ly
th
e
m
o
s
t
in
f
o
r
m
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r
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itize
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tio
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ac
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d
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an
s
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o
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m
e
d
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d
im
e
n
s
io
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s
.
T
h
e
o
r
d
er
ed
p
o
p
u
latio
n
is
th
e
n
s
u
b
jecte
d
to
n
o
n
-
d
o
m
in
ated
s
o
r
tin
g
to
id
en
tify
Par
eto
-
o
p
tim
al
i
n
d
i
v
id
u
als
an
d
ass
ig
n
d
o
m
in
an
ce
r
a
n
k
s
.
Fin
ally
,
th
e
s
o
r
ted
p
o
p
u
latio
n
is
r
etu
r
n
e
d
as
th
e
o
u
tp
u
t
o
f
t
h
e
p
r
o
ce
s
s
,
co
n
clu
d
in
g
th
e
wo
r
k
f
lo
w.
T
h
e
wo
r
k
f
lo
w
o
f
th
e
p
r
o
p
o
s
ed
PC
A
-
b
ased
m
an
y
-
o
b
jectiv
e
test
ca
s
e
g
en
er
atio
n
ap
p
r
o
ac
h
is
d
escr
ib
ed
in
Alg
o
r
ith
m
1
.
Alg
o
r
ith
m
1
PC
A
-
b
ased
m
an
y
-
o
b
jectiv
e
test
ca
s
e
g
en
er
atio
n
Input: Population P, Popula
tion Number S, Target set M
Output: Generated test suite T
1 Initialize population S randomly
2 Initialize archive A
3 Identify uncovered targets U
4 While search budget no exhausted, do
5 Group objectives in U
6 Apply PCA to each group
7
Generate reduced objective set
8 Perform performance
-
based sorting
9 Update archive with new covered targets
10 end while
11 return A as a final test suite T
R
Q2
.
Ho
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ated
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ated
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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Evaluation Warning : The document was created with Spire.PDF for Python.