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Runtime Safety Analysis of Multithreaded Programs

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Runtime Safety Analysis of Multithreaded Programs Koushik Sen University of Illinois at Urbana-Champaign, USA Co-authors Grigore Rosu and Gul Agha – PowerPoint PPT presentation

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Title: Runtime Safety Analysis of Multithreaded Programs


1
Runtime Safety Analysis of Multithreaded Programs
  • Koushik Sen
  • University of Illinois at
  • Urbana-Champaign, USA

Co-authors Grigore Rosu and Gul Agha
2
Talk Overview
  • Motivation
  • MultiPathExplorer
  • Motivating example
  • Instrumentation based on vector clocks
  • Predict specification violations at runtime
  • System architecture
  • Further Applications
  • Conclusion and Future Work

3
Increasing Software Reliability
  • Current solutions
  • Human review of code and testing
  • Most used in practice
  • Usually ad-hoc, intensive human support
  • (Advanced) Static analysis
  • Often scales up
  • False positives and negatives, annotations
  • (Traditional) Formal methods
  • Model checking and theorem proving
  • General, good confidence, do not always scale up

4
Runtime Verification
  • Merge testing and temporal logic specification
  • Specify safety properties in proper temporal
    logic.
  • Monitor safety properties against a run of the
    program.
  • Examples JPaX (NASA Ames), Upenn's Java MaC
    analyzes the observed run.
  • Disadvantage Lack of coverage.

Run
Naïve Observer
5
Our Approach Smart Observer
  • Ideas
  • A single execution trace contains more
    information than appears at first sight
  • Extract other possible runs from a single
    execution
  • Analyze all these runs intelligently.
  • A technique between model checking and testing.

Run
Smart Observer
6
Talk Overview
  • Motivation
  • MultiPathExplorer
  • Motivating example
  • Instrumentation based on vector clocks
  • Predict specification violations at runtime
  • System architecture
  • Further Applications
  • Conclusion and Future Work

7
MultiPathExplorer JMPaX (Java)
  • Based on smart observers
  • Smartness obtained by proper instrumentation
    vector clocks
  • Possible global states generated dynamically ?
    form a lattice
  • Analysis is performed on a level-by-level basis
    in the lattice of global states

8
Motivating Example Safe Landing
Safe Landing Land the air/space craft only after
approval from ground and only if, since then, the
radio signal has not been lost
  • Three variables
  • Landing indicating air/space craft is landing
  • Approved indicating landing has been approved
  • Radio indicating radio signal is live

?Landing ? ?Approved, ?Radio?
9
Code of a Landing Controller
  • Two threaded program to control landing
  • int landing 0, approved 0, radio 1
  • void thread1()
  • askLandingApproval()
  • if (approved 1)
  • print("Landing approved") landing1
    print("Landing started")
  • else print("Landing not approved")
  • void askLandingApproval()
  • if (radio 1) approved 1 else
    approved 0
  • void thread2()
  • while (true) checkRadio()

10
Landing Safety Violation
  • Suppose the plane has received approval for
    landing and just before it started landing the
    radio signal went off
  • the plane must abort landing!
  • A simple observer will most likely not detect the
    bug.
  • JMPaX can construct a possible run in which radio
    goes off between approval and landing

approved 1
landing 1
11
Talk Overview
  • Motivation
  • MultiPathExplorer
  • Motivating example
  • Instrumentation based on vector clocks
  • Predict specification violations at runtime
  • System architecture
  • Further Applications
  • Conclusion and Future Work

12
Events in Multithreaded Programs
  • Given n threads p1, p2, ..., pn,
  • A multithreaded execution is a sequence of events
    e1 e2 er of type
  • internal or,
  • read of a shared variable or,
  • write of a shared variable.
  • eij represents the jth event generated by thread
    pi since the start of its execution.

13
Causality in Multithreaded Programs
  • Define the partial order Á on the set of events
    as follows
  • eik Á eil if k lt l
  • e Á e' if there is some x 2 S such that e ltx e'
    and at least one of e, e is a write.
  • e Á e'' if e Á e' and e' Á e''.

14
Vector Clocks and Relevant Events
  • Consider a subset R of relevant events.
  • (typically those writing specifications
    variables)
  • R-relevant causality is a relation C µ Á
  • C is a projection of Á on R R.
  • We provide a technique based on vector clocks
    that correctly implements the relevant causality
    relation.

15
Vector Clock Algorithm
  • Let Vi be an n-dimensional vector of natural
    numbers for each thread pi.
  • Let Vxa and Vxw be vectors for each shared
    variable x.
  • if eik is relevant, i.e., if eik 2 R, then
  • Vii à Vii 1
  • if eik is a read of a variable x then
  • Vi à maxVi,Vxw
  • Vxa à maxVxa,Vi
  • if eik is a write of a variable x then
  • Vxw à Vxa à Vi à maxVxa,Vi
  • if eik is relevant then
  • send message h eik, i, Vi i to observer.

16
Correspondence with Standard Vector Clocks
17
Implementing Causality by Vector Clocks
  • Theorem If he, i, Vi and he', j, V' i are
    messages sent by our algorithm, then
  • e C e' iff Vi V'i
  • If i and j are not given, then
  • e C e' iff V lt V

18
Example with Two Threads
  • thread T1
  • x
  • ...
  • y x 1
  • thread T2
  • z x 1
  • ...
  • x

(initially x -1)
19
Relevant Global State
  • The program state after the events
    ek11,ek22,...,eknn is called a relevant global
    multithreaded state or simply a state.
  • A state ?k1 k2 kn is called consistent if and
    only if it can be seen in some possible run of
    the system.

20
MultiThreaded Run
  • e1e2 eR is a multithreaded run iff it
    generates a sequence of global states ?K0 ?K1
    ?KR such that
  • each ?Kr is consistent and
  • ?Kr after event er becomes ?Kr1.
  • (consecutive states)

21
Computation Lattice
  • We say ? À ?' when there is some run in which ?
    and ?' are consecutive states
  • Consistent global states together with the
    transitive closure of À form a lattice
  • Multithreaded runs are paths in the lattice

22
Example Revisited
  • thread T1
  • x
  • ...
  • y x 1
  • thread T2
  • z x 1
  • ...
  • x

23
Monitoring Safety Formula
(x gt 0) ! (y 0), (y gt z))s
24
Safety Violation in a Possible Run
(x gt 0) ! (y 0), (y gt z))s
25
Talk Overview
  • Motivation
  • MultiPathExplorer
  • Motivating example
  • Instrumentation based on vector clocks
  • Predict specification violations at runtime
  • System architecture
  • Further Applications
  • Conclusion and Future Work

26
Safety Against All Runs
  • Number of possible runs can be exponential
  • Traverse the state lattice level by level
  • Avoids analyzing an exponential number of runs
  • Maintain a queue of events
  • Enqueue an event as soon as it arrives
  • Construct a new level from the set of states in
    the previous level and the events in the queue
  • Monitor safety formula against all states in a
    level using dynamic programming and intelligent
    merging.

27
Algorithm Pseudocode
  • for each (e 2 Q)
  • if exists s 2 CurrentLevel s.t. isNextState(s,e)
    then
  • NextLevel à addToSet(NextLevel,createState(s,e))
  • if isUnnecessary(s) then
  • remove(s,CurrentLevel)
  • if isEmpty(CurrentLevel) then
  • monitorAll(NextLevel)
  • CurrentLevel à NextLevel NextLevel Ã
  • Q Ã removeUnnecessaryEvents(CurrentLevel,Q)

28
Complexity
  • Time complexity is O(w.2m.n)
  • w width of the lattice
  • m size of the formula
  • n length of the run
  • Memory used is O(w.2m)
  • w width of the lattice
  • m number of temporal operators in the formula
  • Further optimizations
  • Consider bounded width w of queue Q

29
Reason for Efficiency
s00
s11
s12
s21
s32
s31
s41
30
JMPaX Architecture
31
Further Applications
  • Security
  • Security policies as safety requirements
  • Predict safety violations efficiently!

?communicate(A,B,K) ? ? (sendKey(S,(A,B),K) ?
? requestKey(S,A,B))
32
Contributions
  • Introduce vector clock algorithm in multithreaded
    systems to capture relevant causality.
  • Efficiently Predict safety errors from successful
    runs.
  • A modular implementation of the above ideas in a
    analysis tool, JMPaX.
  • http//fsl.cs.uiuc.edu/jmpax/ for JMPaX prototype.

33
Future Work
  • Evaluate JMPaX on real, large applications
  • Develop predictive algorithms for other
    requirements specification logics
  • Consider a superset of partial order to gain
    efficiency
  • Find more scalable techniques that can fill the
    gap between model checking and testing
  • Integrate with NASA Ames Java PathExplorer Tool
    (JPaX).
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