FixingChoreographies usingGraphSimilarities NielsLohmann YRSOC2008 - - PowerPoint PPT Presentation

Fixing
Choreographies
 using
Graph
Similarities


Niels
Lohmann
 YR‐SOC
2008
▪
London
▪
12
June
2008
 UNIVERSITÄT ROSTOCK http://service‐technology.org/yrsoc2008

Who is to blame? What went wrong? How can we avoid this?

State‐of‐the‐art
choreography
analysis



• 1. translate
BPEL
choreography
into
formal
model

• 2. check
for
deadlocks

• 3. if
deadlock
found:

• choose
a
"scapegoat"
participant

• remove
it
from
the
choreography

• synthesize
a
corrected
version
(if
possible)

• retranslate
synthesized
participant
back
to
BPEL


Full
tool
support
available!
[WS‐FM2007]


Problem
with
that
approach


• the
synthesized
service

• is
built
independently
from
the
scapegoat

• gives
no
information
what
was
changed

• is
correct,
yet
might
not
cover
the
original
intention


Example
choreography


• ffer

✓

Example
choreography


• ffer

✗

Fix
the
customer
service


✗ ✓ ✓

better
choice
 scapegoat


Setting


• given:

• a
service
(the
scapegoat)

• a
set
of
candidates

• find:

• the
candidate
that
is
most
similar
to
the
scapegoat

• …without
sequentially
checking
all
candidates



Operating
Guidelines
in
a
Nutshell


• automaton


annotated
 with
Boolean
 formulae


• characterizes
all


partners
[ATPN2007]


• partner
iff

• simulated
by
OG

• fulfilling
the


annotations


• many
applications
(service
discovery,
testing,
…)


• ffer

OG
characterizes
all
possible
corrections


✗ ✓ ✓

and
2001
additional
candidates


Setting
(refined)


• given:

• a
service
automaton
(the
scapegoat)

• an
operating
guideline
characterizing
all
candidates

• find:

• the
candidate
that
is
most
similar
to
the
scapegoat

• …without
sequentially
checking
all
candidates



Graph
edit
distance


• a
measure
to
compare
graphs:
edit
distance


=
no.
of
needed
actions
to
achieve
graph
isomorphism


• maybe
associated
with
a
cost
function


b
 d
 e
 a
 c
 d
 a
 d
 e
 a
 d
 e
 c


0,5 0,7 0,3

Graph
edit
distance
vs.
behavior


?b
 !a
 !c
 !a
 ?b
 !c
 ?b
 !a
 ?b
 !c
 !a
 low
edit
distance
 unsimilar
behavior
 high
edit
distance
 equivalent
behavior
  high
edit
distance
 unsimilar
behavior


Simulation‐based
graph
similarity


• Idea:
find
a
similarity
that
respects
simulation

• compare
two
states
and
find
best
transitions


w.r.t.
successor
states

[TACAS2006]


a
 b
 d
 c
 c
 b
 a
 d
 d


Simulation‐based
graph
similarity


• Mismatches
are
treated
with
stuttering
steps

• penalize
stuttering
by
label
similarity
function

• choose
best
pairs
by
maximizing
label
similarity


a
 b
 d
 c
 c
 b
 a
 e
 ε
 f


Simulation‐based
graph
similarity


• label
similarity
function
defines
an
edit
distance

• (a,a) 
➙
keep
a

• (e,d)
➙
change
e
to
d

• (ε,x) 
➙
insert
x

• (f,ε) 
➙
delete
f

• values
can
be
derived
from
semantic
Web
information

• (!€,!$)
or
(?receipt,?confirmation)
rather
high

• (!login,?invoice)
rather
low


a
 b
 d
 c
 c
 b
a
 e
 ε
 f


Simulation
and
OG
matching


• Simulation
is
only
one
part
of
the
OG
matching

• next
step:
make
edit
distance
aware
of
formulas


✗

Respect
formulas


• instead
of
comparison
with
the
OG's
structure…

• compare
with
satisfying
assignments
of
the
formula

• worst‐case
complexity:
O(|QSA|⋅|QOG|⋅2|I|⋅|I|!)


assignments
 edge
permutations


Experimental
results


• Simulation‐
and
matching‐based
edit
distance


implemented
in
tool
RACHEL


• Dynamic
programming
exploits
structure
of
the
problem


• Most
results
within
few
seconds

• Exceptions
have
near‐worst‐case
structure/formulas


• edit
actions
can
be
mapped
back
to
original
service

• result
can
be
influenced
by
adjusting
label
similarities



Fixing
the
example
with
Rachel


• choreographies
can
be
fixed
using
the
edit
distance

• can
help
to
only
change
little
parts
of
the
scapegoat

• prototype
shows
that
fixing
of
real‐life
processes
works

• Open
questions:

• Which
service
to
fix?

• What
about
cyclic
or
nondeterministic
services?

• How
does
the
mapping
back
to
BPEL
really
work?

• Can
we
support
more
elaborate
edit
actions?

• Can
heuristics
help
to
improve
performance?



Take
home
points


• Tool
demo

• "Tools4BPEL4Chor"
(Tomorrow
@
YR‐SOC)

• tool
chain
(editor,
translation,
analysis…)

• Web

• http://service‐technology.org/yrsoc2008
• slides,
tools,
examples,
links
• Conference
paper

• @
Business
Process
Management
(BPM
2008)

• full
definitions,
related
work,
…


See
more


13

• [TACAS2006]
Oleg
Sokolsky,
Sampath
Kannan,
and
Insup
Lee.


Simulation‐based
graph
similarity.
In
TACAS
2006,
volume
3920 
of
LNCS,
pages
426–440.
Springer,
2006.


• [WS‐FM2007]
Niels
Lohmann,
Oliver
Kopp,
Frank
Leymann,
and


Wolfgang
Reisig.
Analyzing
BPEL4Chor:
Verification
and 
participant
synthesis.
In
WS‐FM
2007,
volume
4937
of
LNCS, 
pages
46–60.
Springer,
2008.


• [ATPN2007]
Niels
Lohmann,
Peter
Massuthe,
and
Karsten
Wolf.


Operating
guidelines
for
finite‐state
services.
In
ICATPN
2007, 
volume
4546
of
LNCS,
pages
321‐341.
Springer,
2007.


• [BPM2008]
Niels
Lohmann.
Correcting
deadlocking
service


choreographies
using
a
simulation‐based
graph
edit
distance. 
In
BPM
2008,
LNCS,
Springer,
2008.
In
Press.


References