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Summarizing Procedures in Concurrent Programs Shaz Qadeer Sriram K. Rajamani Jakob Rehof Microsoft Research.

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Presentation on theme: "Summarizing Procedures in Concurrent Programs Shaz Qadeer Sriram K. Rajamani Jakob Rehof Microsoft Research."— Presentation transcript:

1 Summarizing Procedures in Concurrent Programs Shaz Qadeer Sriram K. Rajamani Jakob Rehof Microsoft Research

2 Motivation How do you scale program analyses for sequential programs? –Summarize at procedure boundaries Sharir-Pnueli 81, Reps-Horwitz-Sagiv 95 –Used in compiler dataflow analyses –Used in error detection tools SLAM (Ball-Rajamani 00) ESP (Das-Lerner-Seigle 02)

3 Summarization is efficient! Boolean program with: –g globals –n procedures, each with at most m locals –|E| = size of the CFG of the program Complexity : O( |E| 2 O(g+m) ) Complexity linear in the number of procedures!

4 Summarization gives termination! Possibly recursive boolean programs Infinite state systems Checking terminates with summarization!

5 Question Can summarization help analysis of concurrent programs?

6 Difficulty Assertion checking for multithreaded programs is undecidable –Even if all variables are boolean –Further, even if only two threads! –Reduce emptiness of intersection of two CFLs to this problem(Ramalingam 00)

7 Our work New model checking algorithm using summarization –useful for concurrent programs Summaries provide re-use and efficiency for analyzing concurrent programs Enable termination of analysis in a large class of concurrent programs –includes programs with recursion, shared variables and concurrency

8 Difficulties in summarizing concurrent programs What is a summary? –For sequential programs Summary of procedure P = Set of all pre-post state pairs (s,s) obtained by invoking P –This doesnt work for concurrent programs Does not model concurrent updates by other threads

9 Insight In a well synchronized concurrent program –A threads computation can be viewed as a sequence of transactions –While analyzing a transaction, interleavings with other threads need not be considered –Key idea: Summarize transactions!

10 How do you identify transactions? Liptons theory of reduction

11 B: both right + left movers –variable access holding lock N : non-movers –access unprotected variable Four atomicities R : right movers –lock acquire S0S0 S1S1 S2S2 acq(this)x S0S0 T1T1 S2S2 x S7S7 T6T6 S5S5 rel(this)z S7S7 S6S6 S5S5 z L: left movers –lock release S2S2 S3S3 S4S4 r=baly S2S2 T3T3 S4S4 y S2S2 T3T3 S4S4 x S2S2 S3S3 S4S4 x

12 Transaction Any sequence of actions whose atomicities are in R*(N+ )L* is a transaction S0S0 S1S1 S2S2 RR S5S5 S6S6 L S3S3 S4S4 RN L S7S7 R Precommit Transaction Postcommit

13 Transactions and summaries Corollary of Liptons theorem: No need to schedule other threads in the middle of a transaction If a procedure body occurs in a transaction, we can summarize it!

14 Resource allocator (1) bool available[N]; mutex m; int getResource() { int i = 0; L0: acquire(m); L1: while (i < N) { L2: if (available[i]) { L3: available[i] = false; L4: release(m); L5: return i; } L6: i++; } L7: release(m); L8: return i; } Choose N = 2 Summaries:

15 What if transaction boundaries and procedure boundaries do not coincide? Two level model checking algorithm

16 Two level algorithm First level maintains stack Second level maintains stack-less summaries Summaries can start and end anywhere in a procedure

17 Resource allocator (2) bool available[N]; mutex m[N]; int getResource() { int i = 0; L0: while (i < N) { L1: acquire(m[i]); L2: if (available[i]) { L3: available[i] = false; L4: release(m[i]); L5: return i; } else { L6: release(m[i]); } L7: i++; } L8: return i; } Choose N = 2 Summaries:

18 Two level model checking algorithm: in pictures Lets first review the sequential CFL algorithm…

19 bar() main( )bar( )

20 main( )bar( )

21 Two level model checking algorithm: in pictures

22 bar() main( )bar( )

23 main( )bar( ) main T1 main T2 End of transaction bar Three kinds of summaries: 1.MAX 2.MAXCALL 3.MAXRETURN MAXCALL MAXRETURN MAX

24 Concurrency + recursion void foo(int r) { L0: if (r == 0) { L1: foo(r); } else { L2: acquire(m); L3: g++; L4: release(m); } L5: return; } Summaries for foo: Summaries for main: void main() { int q = choose({0,1}); M0: foo(q); M1: acquire(m) M2: assert(g >= 1); M3: release(m); M4: return; } P = main() || main() int g = 0; mutex m;

25 What if the same procedure is called from different phases of a transaction? Instrument the transaction phase into the state of the program

26 Transactional context void foo1() { L0: acquire(n); L1: gn++; L2: bar(); L3: release(n); L4: return; } void foo2() { M0: acquire(n); M1: gn++; M2: release(n); M3: bar(); M4: return; } P = foo1() || foo2() int gm = 0, gn = 0; mutex m, n; void bar() { N0: acquire(m); N1: gm++; N2: release(m); }

27 Recap of technical problems How do you identify transactions –Using the theory of reduction (Lipton 75) What if transaction boundaries do not coincide with procedure boundaries? –Two level model checking algorithm –First level maintains stack –Second level maintains stack-less summaries Procedure can be called from different phases of a transaction –Instrument the transaction phase into the state of program

28 Termination A function is transactional if no transaction ends in the middle of its exectution (includes all transitive callees) Theorem: For concurrent boolean programs, if all recursive functions are transactional, then the algorithm terminates.

29 Sequential case If we feed a sequential program to our algorithm it functions exactly like the Reps- Sagiv-Horwitz-POPL95 algorithm Our algorithm generalizes the RHS algorithm to concurrent programs!

30 Related work Summarizing sequential programs –Sharir-Pnueli 81, Reps-Horwitz-Sagiv 95, Ball-Rajamani 00 Concurrency+Procedures –Bouajjani-Esparza-Touili 02 –Esparza-Podeslki 00 Reduction –Lipton 75 –Qadeer-Flannagan 03

31 (joint work with Tony Andrews)

32 Sequential C program Finite state machines Source code FSM abstraction model checker C data structures, pointers, procedure calls, parameter passing, scoping,control flow Automatic abstraction Boolean program Data flow analysis implemented using BDDs SLAM Push down model

33 Source code abstraction model checker Zing Rich control constructs: thread creation, function call, exception, objects, dynamic allocation Model checking is undecidable! Device driver (taking concurrency into account), web services code

34 What is Zing? Zing is a framework for software model- checking –Language, compiler, runtime, tools Supports key software concepts –Enables easier extraction of models from code Supports research in exploring large state spaces Operates seamlessly with the VS.Net design environment

35 Current status Summarization: –Theory: to appear in POPL 04 –Implementation: in progress Zing: –Compiler, model checker and conformance checker operational –State-delta and transaction-based reduction implemented –Plans: Symbolic reasoning Automatic abstraction

36 Bluetooth demo

37 BPEL4WS checking Zing Model Zing State Explorer BuyerSeller AuctionHouse RegService BPEL Processes

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