1. Dynamic Analysis of Multithreaded Java Programs Dr. Abhik Roychoudhury National University of Singapore

2. Program Debugging Age-old activity Age-old activity Simple bug checks handled by compiler – type errors Simple bug checks handled by compiler – type errors Compiler does not detect violation of behavioral invariants Compiler does not detect violation of behavioral invariants –At control location L1, the value of x cannot be 0 Other errors for diff. classes of programs Other errors for diff. classes of programs –Multithreaded (Concurrent or Parallel) –Real-time

3. Real-time Constraints Example: Example: –Data is arriving as a burst every 10 ms –Every burst is a set of records with a primary key –Sort the primary keys before next dataset arrives Need to guarantee that our sorting program always completes before 10 ms Need to guarantee that our sorting program always completes before 10 ms –Worst Case Execution Time  10 ms Worst Case Execution Time should consider all possible inputs Worst Case Execution Time should consider all possible inputs –Exponentially many inputs based on permutations. –Need an efficient analysis technique.

4. Real-time Constraints Worst Case Execution Time estimation is a static analysis technique. Worst Case Execution Time estimation is a static analysis technique. –Performed at compile-time by analyzing the control flow graph of the program –No data is collected/analyzed during run-time. We are trying to prove a property about all possible runs of the program. We are trying to prove a property about all possible runs of the program. Currently working with Li Xianfeng (Ph.D. student) Currently working with Li Xianfeng (Ph.D. student)

5. Multithreaded Programs Threads do computation AND communication Threads do computation AND communication –e.g. Update of shared resources in a critical section Communication among threads Communication among threads –By reading/writing shared variables/objects Java programming language Java programming language –By explicitly sending/receiving messages Message Passing Interface (MPI) Message Passing Interface (MPI) Multithreaded Program Execution Platform Multithreaded Program Execution Platform –Concurrent (Several threads run on single processor with a scheduler) –Parallel (threads run on different processors).

6. Static Analysis and Verification Verification of behavioral properties involves Verification of behavioral properties involves –Constructing a transition system to show the state changes as the program executes –Traversing the transition to check all behaviors. –Roughly corresponds to an efficient version of exhaustive program simulation for all possible inputs. More complicated if sys. is unbounded in size More complicated if sys. is unbounded in size –E.g. the number of threads in a program may be unbounded, but always finite. Currently working with Irina Mariuca Gheorghita (Ph.D. student) Currently working with Irina Mariuca Gheorghita (Ph.D. student)

7. Dynamic Analysis Given an exec. trace of a multi-threaded program Given an exec. trace of a multi-threaded program –Analyze the behavior shown in that trace. Corresponds to natural notion of debugging Corresponds to natural notion of debugging –Debug a program based on a “test case” (the execution trace) Lower complexity than verif. techniques Lower complexity than verif. techniques –No need to Explore a large state space graph But need to collect/store/analyze huge traces  But need to collect/store/analyze huge traces 

8. Cyclic debugging Normal debugging activity is cyclic Normal debugging activity is cyclic 1.Try a test case 2.Encounter a “bug” 3.Run the program again with the test case 4.Use breakpoints etc. and try to locate bug. 5.If not successful, go to 3. Multi-threaded programs are non-deterministic Multi-threaded programs are non-deterministic How to re-generate trace ?? How to re-generate trace ??

9. Simple Example Initially: x= y= 0 Initially: x= y= 0 Lock Lock Lock Lock x = 1 if (x == 1) x = 1 if (x == 1) Unlock y = 1 Unlock y = 1 else y = 2 else y = 2 Unlock Unlock Threads communicating via shared variables Threads communicating via shared variables All shared variable accesses are protected All shared variable accesses are protected

10. Execution trace 1 User executes as follows: User executes as follows: –Thread 1 selected by scheduler. –Lock x = 1 unlock executed by Thread 1. –Thread 2 selected by scheduler –Thread 2 executes and y is set to 1 User suspects the result y =1 User suspects the result y =1 Tries to run the program again with x = y = 0 Tries to run the program again with x = y = 0

11. Execution Trace 2 Program executes again Program executes again –Scheduler now selects Thread 2 first –If ( x== 1) y = 1 else y = 2 results in y = 2 –Thread 1 is executed now and x is set to 1 User tries to debug based on this trace User tries to debug based on this trace But this is a diff. trace with diff. results. But this is a diff. trace with diff. results. Results from the non-determinism of the scheduler. Results from the non-determinism of the scheduler. Non-deterministic exec. in parallel platforms also Non-deterministic exec. in parallel platforms also –Relative processor speeds

12. Problems with Dynamic Analysis Multithreaded programs need to store the trace (or a portion of it) for future analysis. Multithreaded programs need to store the trace (or a portion of it) for future analysis. –In sequential programs it is enough to store the inputs (test-case) generating the trace. Dynamic Analysis is w.r.t. a specific trace Dynamic Analysis is w.r.t. a specific trace –How to generate “representative” traces ? (How to find “good” test cases ? ) –How to compactly store traces for offline analysis? –How to regenerate partially stored traces ? –Offline/ Post-mortem analysis techniques

13. Finding representative traces Describe the invariant property you want to preserve Describe the invariant property you want to preserve –At program loc. L1, x should be greater than zero –At all locations, x should be not equal to zero Construct a state transition graph of the program automatically from the program Construct a state transition graph of the program automatically from the program Efficiently traverse the graph to find possible violations of the property. Efficiently traverse the graph to find possible violations of the property.

14. Finding representative traces If any violation exists, your search produces If any violation exists, your search produces –A counterexample trace –A trace at the end of which the invariant property/assertion is violated. Use the counterexample trace as a representative trace to guide debugging. Use the counterexample trace as a representative trace to guide debugging. Currently working with Daniel Hogberg (Ph.D. student) Currently working with Daniel Hogberg (Ph.D. student)

15. Compactly storing traces Treat the program trace as a string s over a pre- defined alphabet. Treat the program trace as a string s over a pre- defined alphabet. Create a hierarchical representation of the program trace which is more compact Create a hierarchical representation of the program trace which is more compact –(catches repetitions of chunks of code) The compact representation should be created online, as the program is executing The compact representation should be created online, as the program is executing We have developed a scheme for compressing Java bytecode for multi-threaded programs. We have developed a scheme for compressing Java bytecode for multi-threaded programs. Working with Wang Tao (Ph.D. student) and Ankit Goel (visiting student) Working with Wang Tao (Ph.D. student) and Ankit Goel (visiting student)

16. Compressed Path - Example 1 2 3 Uncompressed Path 123123 Compressed Representation S  AA A  123 Control Flow Graph If-then statement

17. Post-mortem analysis of traces Compressed traces should be easy to navigate Compressed traces should be easy to navigate –Post-mortem analysis should not involve decompressing entire trace. –Useful to detect data races in multi-threaded Java programs –Data races  Unprotected shared variable accesses x = 1 x = 2 x = 1 x = 2 if (x == 1) then S1 if (x == 2) then S2 if (x == 1) then S1 if (x == 2) then S2 The programmer expects S1, S2 to be executed The programmer expects S1, S2 to be executed May not happen due to data races. May not happen due to data races.

18. Tracing strategy Too costly to track down all shared variable operations in a realistic Java program Too costly to track down all shared variable operations in a realistic Java program Even if the operations are stored compactly, the run-time overheads may be too high. Even if the operations are stored compactly, the run-time overheads may be too high. One possibility is to store only the synchronization operations during run-time. One possibility is to store only the synchronization operations during run-time. Regenerate and analyze possible orderings of the other communication operations – unsynchronized shared variable accesses. Regenerate and analyze possible orderings of the other communication operations – unsynchronized shared variable accesses. Looking for students in these topics. Looking for students in these topics.

19. Relevant Papers Compactly Representing Parallel Program Executions, (pdf) A. Goel, A. Roychoudhury and T. Mitra ACM Symposium on Principles and Practice of Parallel Programming (PPoPP) 2003. Compactly Representing Parallel Program Executions, (pdf) A. Goel, A. Roychoudhury and T. Mitra ACM Symposium on Principles and Practice of Parallel Programming (PPoPP) 2003.pdf Specifying Multithreaded Java Semantics for Program Verification, (ps, pdf) A. Roychoudhury and T. Mitra ACM/IEEE International Conference on Software Engineering (ICSE) 2002, pages 489-499. Specifying Multithreaded Java Semantics for Program Verification, (ps, pdf) A. Roychoudhury and T. Mitra ACM/IEEE International Conference on Software Engineering (ICSE) 2002, pages 489-499.pspdfICSEpspdfICSE Depiction and Playout of Multi-threaded Program Executions, A. Roychoudhury, Submitted for publication Depiction and Playout of Multi-threaded Program Executions, A. Roychoudhury, Submitted for publication Symbolic Simulation of Live Sequence Charts, S. Choudhary, A Roychoudhury and RHC Yap, Submitted for publication. Symbolic Simulation of Live Sequence Charts, S. Choudhary, A Roychoudhury and RHC Yap, Submitted for publication.

20. My Contact Information First two papers available from my web-page. First two papers available from my web-page. http://www.comp.nus.edu.sg/~abhik/ http://www.comp.nus.edu.sg/~abhik/ http://www.comp.nus.edu.sg/~abhik/ If you are interested in the projects, send e-mail If you are interested in the projects, send e-mail –abhik@comp.nus.edu.sg abhik@comp.nus.edu.sg –dcsar@nus.edu.sg dcsar@nus.edu.sg