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Semantics & Verification Research Group Department of Computer Science University of Malta 2008 Runtime Verification of Contracts for Java Programs Christian.

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Presentation on theme: "Semantics & Verification Research Group Department of Computer Science University of Malta 2008 Runtime Verification of Contracts for Java Programs Christian."— Presentation transcript:

1 Semantics & Verification Research Group Department of Computer Science University of Malta 2008 Runtime Verification of Contracts for Java Programs Christian Colombo Gordon J. Pace Gerardo Schneider FLACOS - November 2008

2 Semantics & Verification Research Group Department of Computer Science University of Malta 2 2008 RV & Contracts  In SOA we are concerned with security and trust.  Model checking is not scalable.  Testing lacks coverage.  Particular behaviour only emerges during normal use of service composition.  Runtime verification monitors the behaviour during runtime, scales up.  Real-time properties / overheads.  Contracts may have conflicts.

3 Semantics & Verification Research Group Department of Computer Science University of Malta 3 2008 Runtime Verification -------------- -------------- Specification-------------- --------------

4 Semantics & Verification Research Group Department of Computer Science University of Malta 4 2008 Runtime Verification -------------- -------------- Contracts-------------- --------------

5 Semantics & Verification Research Group Department of Computer Science University of Malta 5 2008 Runtime Verification -------------- Deontic Contracts -------------- -------------- Deontic Contracts --------------

6 Semantics & Verification Research Group Department of Computer Science University of Malta 6 2008 Dynamic Automata with Timers & Events (DATE)  Communicating symbolic automata enriched with events and timers.  Automata are automatically replicated according to context: hence dynamic.  Supports:  Conditions and actions on transitions  Real-time  Communication between automata

7 Semantics & Verification Research Group Department of Computer Science University of Malta 7 2008 An Example (1)

8 Semantics & Verification Research Group Department of Computer Science University of Malta 8 2008 An Example (2)

9 Semantics & Verification Research Group Department of Computer Science University of Malta 9 2008 LARVA - Architecture AspectJ Matching method names AspectJ Matching method names USER

10 Semantics & Verification Research Group Department of Computer Science University of Malta 10 2008 Contract Language Example

11 Semantics & Verification Research Group Department of Computer Science University of Malta 11 2008 Contract Language to Automata

12 Semantics & Verification Research Group Department of Computer Science University of Malta 12 2008 Contract Language to LARVA EVENTS { login = {*.login()} logout= {*.logout()} request= {*.requestItem()} } PROPERTY clcontract { STATES { BAD { V } NORMAL { S1 S2 } STARTING { Init } } TRANSITIONS { Init -> S1 [login] Init -> V [request] Init -> S2 [logout] S1 -> S1 [login] S1 -> S1 [request] S1 -> S2 [logout] S2 -> S2 [logout] S2 -> V [request] S2 -> S1 [login] }

13 Semantics & Verification Research Group Department of Computer Science University of Malta 13 2008 Contradictions in Contracts O(request) request Contradiction Detected!

14 Semantics & Verification Research Group Department of Computer Science University of Malta 14 2008 Ongoing Work  Working closely with industry  Guarantees on the effect of monitoring – memory and time  Identifying better notations  Investigating compensable actions

15 Semantics & Verification Research Group Department of Computer Science University of Malta 15 2008 Conclusions  Mathematical framework – DATE  Implemented useable tool – LARVA  Highly expressive (incl. real-time)  Evolving theory with practical guarantees  Can monitor contracts  Find contradictions in contracts  Future prospects of collaboration and improvement of current framework

16 Semantics & Verification Research Group Department of Computer Science University of Malta 16 2008 Questions ??

17 Semantics & Verification Research Group Department of Computer Science University of Malta 17 2008

18 Semantics & Verification Research Group Department of Computer Science University of Malta 18 2008 A Scenario – Dynamic Triggers  Imagine we need to check login/logout for each user.  We have to trigger an automaton for every user, to keep track whether each user is logged in or not.  Use method parameters to get context.

19 Semantics & Verification Research Group Department of Computer Science University of Malta 19 2008 Specifying Properties  Intuitive, clear and succinct logic.  Understandable and useable by developers.  Includes all the required expressive power.  Automatically instrumentable in the target system.  Low overheads (eg. Determinism)

20 Semantics & Verification Research Group Department of Computer Science University of Malta 20 2008 Simple Examples  Ensuring that only authorised users access reserved areas in the system.  Checking that a train gate which started closing has indeed closed after a number of seconds.  Monitoring the life-cycle of an object (such as a transaction), ensuring it goes through its stages properly.

21 Semantics & Verification Research Group Department of Computer Science University of Malta 21 2008 Specifying Context  Actions and conditions on transitions can access the context (User).  A context can be nested to have a more specific context within it:  Eg: Check login for each site of each individual user.

22 Semantics & Verification Research Group Department of Computer Science University of Malta 22 2008 LARVA - Architecture LARVA --------------- ---- EVENTS & PROPERTIES --------------- ---- LARVA --------------- ---- EVENTS & PROPERTIES --------------- ---- USER

23 Semantics & Verification Research Group Department of Computer Science University of Malta 23 2008 LARVA - Architecture (2) LARVA ---------------- --- EVENTS & PROPERTIES ---------------- --- LARVA ---------------- --- EVENTS & PROPERTIES ---------------- --- AspectJ Matching method names AspectJ Matching method names COMPILER

24 Semantics & Verification Research Group Department of Computer Science University of Malta 24 2008 Recall Scenario Load Site Prompt for PW Good Login PressOK \ checkUserName() PressOK \ checkPassword() \ Goodlogin ! Trigger new automaton FOREACH user PressOK Logged in Logged out Bad logins Logged out ChGoodlogin? Badlogin

25 Semantics & Verification Research Group Department of Computer Science University of Malta 25 2008 LARVA – Script GLOBAL { FOREACH (User u) { VARIABLES { Channel gl; } EVENTS { goodlogin() = {gl.receive(User u1)} where {u = u1;} pressOK() = {*.pressedOK(u1)} where {u = u1;} badlogin() = {*.loginTry(u1)} where {u = u1;} } PROPERTY one { STATES { BAD { badlogins } NORMAL { loggedout2 loggedout3 loggedin } STARTING { loggedout1 } } TRANSITIONS { loggedout1 -> loggedin [goodlogin] loggedout2 -> loggedin [goodlogin] loggedout3 -> loggedin [goodlogin] loggedout1 -> loggedout2 [badlogin] loggedout2 -> loggedout3 [badlogin] loggedout3 -> badlogins [badlogin] } PROPERTY two { STATES { NORMAL { promptPW goodlogin } STARTING { loadsite } } TRANSITIONS { loadsite -> promptPW [PressOK\checkUserName()] promptPW -> goodlogin [PressOK\checkPassword()\gl.send(u);] promptPW -> loadsite [PressOK] } METHODS { boolean checkUserName(){return true;} boolean checkPassword(){return true;} }

26 Semantics & Verification Research Group Department of Computer Science University of Malta 26 2008 LARVA - Compilation into Java  AOP to capture events.  A hierarchy of classes: one for each context.  Each class has a reference to its parent context. (E.g. The account context, have access to the user context.)  A hashmap to keep track of the distinct objects which we are checking.

27 Semantics & Verification Research Group Department of Computer Science University of Malta 27 2008 Case-Study (2): Properties  Logging of credit card numbers – no risk of exposing sensitive information.  Execution of transactions – correct progress through states.  Authorisation transaction – transaction consistency.  Backlog – retries in case of failure.

28 Semantics & Verification Research Group Department of Computer Science University of Malta 28 2008 Case-Study (3): - Experience  A lot of interesting properties are relatively simple.  Intuitive definition of properties.  Identified shortcomings of Larva and it was extended.  RV helps in clearly identifying requirements.  Integration in system life cycle.

29 Semantics & Verification Research Group Department of Computer Science University of Malta 29 2008 Benchmark – Expressivity

30 Semantics & Verification Research Group Department of Computer Science University of Malta 30 2008 Benchmark – Performance  Dummy transaction processing system (4 properties – 2 real-time)  Memory and time required is considerable but linear to the number of objects being monitored (replication of automata).  Compares well with Java-MOP which is the most similar work available for usage.

31 Semantics & Verification Research Group Department of Computer Science University of Malta 31 2008

32 Semantics & Verification Research Group Department of Computer Science University of Malta 32 2008 AOP  Automatic code weaving using pointcuts and advises.  Pointcut: call(* *.*(..))  d.bark(b) && target(d) && args(b)  Advise: before, after, around  before (Dog d, Bark b): pointcut(d,b){ spotACat(); }

33 Semantics & Verification Research Group Department of Computer Science University of Malta 33 2008 Other Events  Upon return: upon the return of a method (rather than the entry of the method).  Upon exception thrown: rather than simple method call, we can trigger the automaton upon an exception throw.

34 Semantics & Verification Research Group Department of Computer Science University of Malta 34 2008 Other Events (2)  Upon exception handling: rather than simple method call, we can trigger the automaton upon the start of a catch block.  Clocks: trigger the automaton upon the elapse of an amount of time.  Channels: an automaton can trigger another automaton.

35 Semantics & Verification Research Group Department of Computer Science University of Malta 35 2008 Object Equality  What if an object does not implement an equals method?  The user can specify which attributes of the object constitute the context.  E.g. A transaction is the same as long as it has the same id.

36 Semantics & Verification Research Group Department of Computer Science University of Malta 36 2008 Invariants  What if some attributes of an object should not change?  The user can specify these attributes.  E.g. A transaction should remain with the same amount once the amount is set.

37 Semantics & Verification Research Group Department of Computer Science University of Malta 37 2008 Chained Transitions  Should we allow transitions to trigger other transitions?  This could lead to an infinite loop!  So we disable aspects within the aspect code itself.  But we allow the user to take the risk with channels...

38 Semantics & Verification Research Group Department of Computer Science University of Malta 38 2008 Determinism  For easier execution of the automaton, we opted for determinism.  The user specifies the order of transitions as they are written down in the script file.

39 Semantics & Verification Research Group Department of Computer Science University of Malta 39 2008 Overhead of Verification (1)  Depends on a number of factors:  The actions the user puts on transitions.  The statements in the where clauses.  The amount of objects that the user keeps context of.  Very difficult to give an upper-bound because of the amount of freedom we give the user.

40 Semantics & Verification Research Group Department of Computer Science University of Malta 40 2008 Overhead of Verification (2)  But we can guarantee the maximum memory overhead of our system…  …given that the user does not add other method calls on transitions.  We use Lustre so that the memory can be calculated at compile-time.

41 Semantics & Verification Research Group Department of Computer Science University of Malta 41 2008 Real-Time Issues  Because of the Java Garbage Collection there is a limit to accuracy that we can give.  Using Java wait method is quite good within a certain number of milliseconds.

42 Semantics & Verification Research Group Department of Computer Science University of Malta 42 2008 Real-Time Issues (2)  Consider a system which satisfies all its properties.  Will the properties still hold if we introduce the monitoring?  We provide a fragment of Duration Calculus which is “slow-down invariant”.

43 Semantics & Verification Research Group Department of Computer Science University of Malta 43 2008 Compiler  The Compiler and Parser Manual are available at:  www.cs.um.edu.mt/~svrg/Tools/LARVA/  christiancolombo.com/academic-masters-tools.html  Feel free to use it and give us feedback.

44 Semantics & Verification Research Group Department of Computer Science University of Malta 44 2008 Nesting – Context within Context  FOREACH (User u){ ...  FOREACH (Site s)  {  EVENTS{  Login() = {User u1.login(Site s1)}  where {u = u1; s=s1;}  } ...  }

45 Semantics & Verification Research Group Department of Computer Science University of Malta 45 2008 Events  System Events – method call, method return, exception throw, exception handling.  Channel Communication.  Clock Timeouts.


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