Model Generation for Distributed Java Programs

1
Model Generation for Distributed Java Programs

• Rabéa Boulifa
• Eric Madelaine
• Oasis Team
• INRIA, Sophia-Antipolis France, I3S, UNSA

Luxembourg, November 28, 2003
scientiFic engIneering of Distributed Java
applIcation
2
Outline

• Distributed Java Applications, the ProActive
  Library
• Approach
• Models Networks and LTSs
• Model Construction
• Conclusion

scientiFic engIneering of Distributed Java
applIcation
Luxembourg, November 28, 2003
3
Context, ProActive library

• Active objects communicate by Remote Method
  Invocation.
• Each active object
• has a request queue (always accepting incoming
  requests)
• has a body specifying its behaviour (local state
  and computation, service of requests, submission
  of requests)
• manages the  wait by necessity  of responses
  (futures)

Luxembourg, November 28, 2003
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Approach
Control flow analysis
MCG
ProActive Application
Behavioural Semantics
LTS

• Behavioural model (Labelled Transition Systems),
  built in a compositional (structural) manner
  One LTS per active object.
• Synchronisation based on ProActive semantics
• Usable for Model-checking ? finite / small
  models

scientiFic engIneering of Distributed Java
applIcation
Luxembourg, November 28, 2003
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Method Calls informal diagram
Current object
Remote object
!Req_m
!Req_m

• method call

?Req_m

• request arriving in
• the queue

?Req_m
!Serv_m

• request served
• (executed and removed)

!Serv_m
!Rep_m

• response sent back

!Rep_m

• response received

?Rep_m
?Rep_m
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Model Networks of synchronised LTSs

• Finite enumeration active objects ? Synchro.
  Networks Arnold 80
• Boxes and links computed by static analysis
• Labelled transition systems, LTSs
• 1 LTS per activity LTS behaviour LTS queue.
• LabelsRequests/Responses (meth. name finite
  abstract. of param.)

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Construction procedure

• Finite network analyse the source code of the
  application, by some finite abstraction of
  parameters.
• For each Active Object Class (with all required
  passive classes)
• build the Method Call Graph, MCG
• compute the sequential LTS, using the SOS rules
• interleave at each wait by necessity points,
  using the Future rule (gt asynchronous LTS).
• generate the request queue LTS.
• combine the asynchronous LTS with the queue LTS.
• Property For a finite data abstraction ?
  Termination guaranteed

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Building of Network

• Enumeration
• O Oi a finite number of active object
  classes.
• Dom (Oi) a finite number of instantiations of
  each class.
• (use a finite abstraction of creation
  parameters)
• Incoming ports (available services) set of
  public methods
• Outgoing links remote requests
• (use a finite abstraction of message
  parameters)

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Method Call Graph
MCGltid, V, ?C, ?T , ? gt method name nodes
call edges transfer edges reference to
future nodes ? ent(id), call(id), rep(id),
seq, ret public void getForks()
ObjectForSynchro lf
Forkid.take() ObjectForSynchro lr
Forkright_ind.take()
waitFor(lf) waitFor(lr)
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scientiFic engIneering of Distributed Java
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Rules SOS-style

Premisses
ltvpattern, n, A, M, Sc, Smgt ? ltv', n', A, M',
Sc, Smgt
MCG node
method stack
LTS node
Continuation stack
LTS
mapping

At beginning ltvent(runActivity), ?, ?, M, ,
gt
Luxembourg, November 28, 2003
scientiFic engIneering of Distributed Java
applIcation
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Local Call
We will go and analyse its code, just as if we
where inlining it. We shall not develop loops or
recursive procedures.
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scientiFic engIneering of Distributed Java
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Remote Call
v1 ?T v2 Active(O) fresh(n')
R_Call
ltv1call(O.m), n, A, M, Sc, Smgt ?
ltv2, n', A?(n  
n ), M ? v1 ? n', Sc, Smgt
!Req_M
O is a remote active object. We simply generate a
send message !Req_M encoding the method name and
its (abstracted) parameters.
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Futures
?Rep_M
?(v1)v2 n1M(v1) n2M(v2) A (A ??
)
Fut
ltv1, Agt ? A 
Where M is the phantom of M, i.e. the union of
all Ms during the construction procedure
V v O.m1(x) xxx yyy v.f()
scientiFic engIneering of Distributed Java
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Luxembourg, November 28, 2003
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Example (Philosopher Diner)

• public void runActivity()
• while(true)
• think() getForks()
• eat() putForks()
• public void getForks()
• ObjectForSynchro lf
• Forkid.take()
• ObjectForSynchro lr
• Forkright_ind.take()
• waitFor(lf)
• waitFor(lr)

Luxembourg, November 28, 2003
scientiFic engIneering of Distributed Java
applIcation
15
MCG ? LTS
Sc
Sm




Luxembourg, November 28, 2003
scientiFic engIneering of Distributed Java
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MCG ? LTS
Sc Sm





Luxembourg, November 28, 2003
scientiFic engIneering of Distributed Java
applIcation
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MCG ? LTS
Sc Sm















Luxembourg, November 28, 2003
scientiFic engIneering of Distributed Java
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18
Conclusion

• Behaviour models of ProActive distributed
  applications encode asynchronous communication
  between distributed objects.
• With usual data/structure abstraction, we build
  finite, hierarchical, models suitable for
  automatic verification.
• Prototype implementation based on Soot and
  Bandera tools.
• Future directions
• Parameterised models can be finitely instantiated
  (adapted to each property), or directly fed into
  specialised tools. They are more compact and more
  flexible.
• Other ProActive features group communication,
  exceptions.
• Behaviour specification for distributed
  components.

Luxembourg, November 28, 2003
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Properties

• Check properties
• deadlocks, livelock, temporal logic formulas
• Check equivalence with

Luxembourg, November 28 ,2003
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applIcation
20
Model Generation for Distributed Java Programs

• Rabéa Boulifa
• Eric Madelaine
• Oasis Team
• INRIA, Sophia-Antipolis France
• http//www-sop.inria.fr/oasis/Vercors
• http//www-sop.inria.fr/oasis/Proactive

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21
Model Networks of synchronised LTSs(2)

• Labelled transition systems, LTSs
• 1 LTS per activity LTS behaviour LTS queue.
• Labels Requests/Responses
• (method name finite abstraction of
  parameters)
• Construction by SOS rules, based on the Method
  Call Graph.

Luxembourg, November 28, 2003
scientiFic engIneering of Distributed Java
applIcation
22
MCG ? LTS
Sc
Sm




Luxembourg, November 28, 2003
scientiFic engIneering of Distributed Java
applIcation