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Java Race Finder Checking Java Programs for Sequential Consistency Tuba Yavuz-Kahveci Fall 2013
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Outline The Problem: Getting Multithreaded Java Programs Right Java Memory Model Our Solution: Java Race Finder What is model checking anyway? Representing Happens-before Heuristic-based Search Code Modification Suggestions
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What is Sequential Consistency? Program statements are executed according to program order Each thread’s statements are executed according to the program order in that thread’s code Write atomicity Each read operation on a variable sees the most recent write operation on that variable
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What is a Memory Model? Constrains the behavior of memory operations What value can a read operation see? Example memory models Sequential Consistency Easy to understand Relaxed Consistency Models Relaxation of Program order Write atomicity
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Who Should Care? Programmers Understanding how to achieve sequential consistency, if possible Reasoning about correctness Compiler writers Optimizing code within the restrictions of the memory model
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Problem: Getting Multi-threaded Java Programs Right Important Questions Any Java Programmer Should Ask Is my multithreaded program correctly synchronized? Beware!!! Sequential consistency is not guaranteed for incorrectly synchronized Java programs! If my multithreaded program is not correctly synchronized, how can I fix it? If my multithreaded program is not correctly synchronized for a good reason, should I still be worried? Automated tool support is needed to answer these nontrivial questions
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An Example: Peterson’s Mutual Exclusion Algorithm - Version 1 Initialization: flag[0] = flag[1] = turn = shared = 0 /* all non-volatile */ s1: flag[0] = 1; Thread 1 Thread 2 s2: turn = 1; s3: while (flag[1] == 1 && turn == 1) { /*spin*/} s4: shared++; /* critical section */ s5: flag[0] = 0; s6: flag[1] = 1; s7: turn = 0; s8: while (flag[0] == 1 && turn == 0) { /*spin*/} s9: shared++; /* critical section */ s10: flag[0] = 0;
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Outline The Problem: Getting Multithreaded Java Programs Right Java Memory Model Our Solution: Java Race Finder What is model checking anyway? Representing Happens-before Heuristic-based Search Code Modification Suggestions
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What is Java Memory Model (JMM)? A relaxed memory model Sequential consistency is guaranteed only for correctly synchronized programs For programs without data races Incorrectly synchronized programs can show extra behavior that is not sequentially consistent Still subject to some safety rules
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Synchronization Rules in Java Some synchronization actions and their relationship in Java: Unlocking a monitor lock synchronizes with locking that monitor lock. Writing a volatile variable synchronizes with reading of that variable. Starting a thread synchronizes with the first action of that thread. Final action in a thread synchronizes with any action of a thread that detects termination of that thread. Initialization of a field synchronizes with the first access to the field in every thread. In general a release action synchronizes with a matching acquire action.
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Happens-Before Relation An action a1 happens-before action a2, a1 ≤ hb a2, due to one of the following: a1 comes before a2 according to program order: a1 ≤ po a2. a1 synchronizes with a2: a1 ≤ sw a2. a1 happens-before a’ that happens-before a2: Exists a’. a1 ≤ hb a’ and a’ ≤ hb a2 (transitivity). Happens-before, ≤ hb = ( ≤ po U ≤ sw ) +, is a partial-order on all actions in an execution.
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Happens-before Consistency A read operation r can see results of a write operation w provided that: r does not happen-before w: not (r ≤ hb w). There is no intervening write operation: not (exists w’. w r ≤ hb w’ ≤ hb r).
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Anatomy of a Data Race Definition: If two actions a1 and a2 from different threads access the same memory location loc, the actions are not ordered by happens-before and if one of the actions is a write, then there is a data race on loc. Example: ≤ hb Thread 1 Thread 2 Initialization: boolean done = false; /* non-volatile */ done = true; if (done) // use result Race on done!!! result = compute();
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A Simple Fix A write to a volatile variable synchronizes with a read of that variable. Example: ≤ hb Thread 1 Thread 2 Initialization: volatile boolean done = false; done = true; if (done) // use result result = compute(); ≤ hb Not in a race
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Outline The Problem: Getting Multithreaded Java Programs Right Java Memory Model Our Solution: Java Race Finder What is model checking anyway? Representing Happens-before Heuristic-based Search Code Modification Suggestions
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Our Solutions/Contributions Is my multi-threaded program correctly synchronized? Kim K., Yavuz-Kahveci T., Sanders B.Precise Data Race detection in Relaxed Memory Model using Heuristic based Model Checking [ASE Conf. 2009] If my multi-threaded program is not correctly synchronized, how can I fix it? Kim K., Yavuz-Kahveci T., Sanders B. JRF-E: Using Model Checking to give Advice on Eliminating Memory Model-related Bugs [ASE Conf. 2010, ASE Journal 2012] If my program is not correctly synchronized for a good reason, should I still be worried? Jin H., Yavuz-Kahveci T., Sanders B. Java Path Relaxer: Extending JPF for JMM-aware model checking [JPF Workshop] Jin H., Yavuz-Kahveci T., Sanders B. Java Memory Model-Aware Model Checking [TACAS 2012]
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Outline The Problem: Getting Multithreaded Java Programs Right Java Memory Model Our Solution: Java Race Finder What is model checking anyway? Representing Happens-before Heuristic-based Search Code Modification Suggestions
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State/Snapshot of a Running Java Program Values of Static Fields Heap (objects) Thread states Bytecode for the Java program JAVA VIRTUAL MACHINE
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Model Checking Java Programs Values of Static Fields Heap (objects) Thread states Main Thread Thread1 Thread2 Thread3 … Main Thread Thread2 Thread1 Thread3 … Main Thread Thread3 Thread2 Thread1 …
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Model Checking for Sequential Consistency Java Race Finder (JRF) Java Path Finder (JPF) Multi-threaded Java application Data Race? yes no a model-checker for Java programs checks for general correctness properties assumes sequential consistency explores all possible thread interleaving extends JPF’s state representation to detect data races
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Our Approach for Detecting Data Races Algorithm: for each execution path EP j = of program P do initialize happens-before relation for each action a i, i= 1 to n, do let loc be the memory location a i accesses if (it is safe (without a data race) for a i to access loc) generate DATA RACE error execute a i update happens-before relation
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Representing Happens-Before We define an h-function that captures the happens-before relation in an implicit way. h: SyncAddr U Thread -> 2 Addr. SyncAddr: Volatile variables and locks Addr: Non-volatile variables Is it safe for a j of thread t i to access loc? does h(t i ) contain loc? Which variables can be safely accessed if acquire on s (with a matching release on s) is executed? h(s).
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The h-function Initialization: At the beginning there is only the main thread: h0 = λz.if z = main then static(P) else φ Update: Executing an action updates the h-function: action(t, x) h = h’ h: h-function before executing action t: the thread the action belongs to x: synchronization variable (volatile or a lock) h’: the updated h function
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Updating the h-function action a n by thread th n+1 write a volatile field vrelease(t,v) h n read a volatile field vacquire(t, v) h n lock the lock variable lckacquire(t, lck) h n unlock the lock variable lckrelease(t,lck) h n start thread t′release(t,t′) h n join thread t′acquire(t, t′) h n t′.isAlive() returns falseacquire(t, t′) h n write a non-volatile field xinvalidate(t, x) h n read a non-volatile field xhnhn instantiate an object containing non-volatile fields fields and volatile fields volatiles new (t, fields, volatiles ) h n
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Action Semantics Variables that can be safely accessed from thread t copied to the set for synchronization variable x release(t, x)h = h[x → h(t) ∪ h(x)] Variables in the set of synchronization variable x will now be safely accessed by thread t acquire(t, x)h = h[t → h(t) ∪ h(x)] Only thread t which changed x can safely access it. invalidate(t, x) h = λz. if (t = z) then h(z) else h(z)\{x} The non-volatile fields of the newly created object can be safely accessed by the thread who created it. The volatile fields are initialized to refer to empty sets. new(t, fields, volatiles)h = λz. if (t = z) then h(t) ∪ fields else if (z ∈ volatiles ) then{} else h(z)
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Implementation of the h-function
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How JRF extends JPF
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Test Programs Sources# of examples# of examples found to have data races Textbook by Herhily and Shavitz. 6519 Amino Concurrent Building Blocks Library 109 Google Concurrent Data Structures Workshop. 1210 Java Grande Forum Benchmark Suite 106 Webserver Simulator – Student Projects 287
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Time Overhead of JRF
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Space Overhead of JRF
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Outline The Problem: Getting Multithreaded Java Programs Right Java Memory Model Our Solution: Java Race Finder What is model checking anyway? Representing Happens-before Heuristic-based Search Code Modification Suggestions
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Finding the data race quickly race State space of a program initial state Each path from initial state to a leaf state represents a separate execution. race
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Finding the data race using DFS race State space of a program initial state Each path from initial state to a leaf state represents a separate execution. race DFS counter-example
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Finding the data race using BFS race State space of a program initial state Each path from initial state to a leaf state represents a separate execution. race BFS counter-example
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Heuristic-Based Data Race Search Our goal is to reach a state that has a data race as quick as possible. Assign a traversal priority to each program state based on how close it may be to a racy state. Writes-First (WF): Prefer write statements to read statements Watch-Written (WW): Prefer access to memory locations recently written by another thread Avoid Release/Acquire (ARA): Avoid scheduling threads that perform proper synchronization. Acquire-First (AF): Prefer acquire operations that do not have a matching release operation.
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An Example: Peterson’s Mutual Exclusion Algorithm - Version 1 Initialization: flag[0] = flag[1] = turn = shared = 0 /* all non-volatile */ s1: flag[0] = 1; Thread 1 Thread 2 s2: turn = 1; s3: while (flag[1] == 1 && turn == 1) { /*spin*/} s4: shared++; /* critical section */ s5: flag[0] = 0; s6: flag[1] = 1; s7: turn = 0; s8: while (flag[0] == 1 && turn == 0) { /*spin*/} s9: shared++; /* critical section */ s10: flag[0] = 0;
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DFS vs Heuristic Search s1: flag[0] = 1; Thread 1 s2: turn = 1; s3: while (flag[1] == 1 && turn == 1) { /*spin*/} s4: shared++; /* critical section */ s5: flag[0] = 0; Thread 2 s6: flag[1] = 1; s7: turn = 0; Thread 1 s1: flag[0] = 1; s2: turn = 1; Thread 2 s6: flag[1] = 1; s7: turn = 0; Race! turn not in h(thread2)! DFS Search Path Heuristic Search Path
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Experimental Results: Heuristic Search Code (lines of code) SearchStateLengthTime (sec) Memory (MB) DisBarrier (232) DFS Heuristic BFS 109 79 2589 109 39 36 4 3 256 53 46 644 Moldyn (1252) DFS Heuristic BFS 2821 1896 5127 2821 950 >574* 231 257 1014 579 518 988 DEQueue (334) DFS Heuristic BFS 33 19 30 28 12 9 112112 27 26 31 BinaryStaticTree Barrier (1910) DFS Heuristic BFS 61 137 2275 61 52 >18* 7 9 2221 66 86 986 *: JPF ran out of memory
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Outline The Problem: Getting Multithreaded Java Programs Right Java Memory Model Our Solution: Java Race Finder What is model checking anyway? Representing Happens-before Heuristic-based Search Code Modification Suggestions
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What went wrong? Thread 1 s1: flag[0] = 1; s2: turn = 1; Thread 2 s6: flag[1] = 1; s7: turn = 0; source statement manifest statement removes turn from h(thread2) accesses turn when turn is not in h(thread2)
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How to fix it? Data races are due to absence of happens-before relationship Suggest code modifications that will create happens-before relationship between the source and manifest statements Change the variable to volatile Change the array to an atomic array Move the source statement to make use of existing happens- before relationships due to transitivity Perform the same synchronization Change another variable to volatile to create happens-before relationships due to transitivity
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Change to atomic array Thread 1 s1: flag[0] = 1; s2: turn = 1; Thread 2 s6: flag[1] = 1; source statement manifest statement removes flag[1] from h(thread1) Accesses flag[1] when flag[1] is not in h(thread1) Change flag to atomic array Peterson’s ME Alg. turn and flag are volatile s3: while (flag[1] == 1 && turn == 1) { /*spin*/} Thread 1
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An Example for move source Initialization: goFlag = false; volatile Data publish; s1: r = new Data(); Thread 1 Thread 2 s2: publish = r; s3: r.setDesc(e); s4: goFlag = true; t1: if (publish != null) { t2: while (!goFlag); t3: String s = publish.getDesc(); t4: assert(s.equals(“e”); } Updates published object after making the reference visible Compiler may reorder s3 and s4 May use the published object when it is in an inconsistent state
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Move source statement s1: r = new Data(); Thread 1 Thread 2 s2: publish = r; s3: r.setDesc(e); s4: goFlag = true; t1: if (publish != null) { t2: while (!goFlag); publish is volatile goFlag is not volatile source statement removes goFlag from h(thread2) manifest statement Accesses goFlag when goFlag is not in h(thread2) Move s4 before s2 s4: goFlag = true;
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An Example for perform the same synchronization operation Initialization: int data; final Object lock = new Object(); s1: print (data); Thread 1 Thread 2 t1: synchronized (lock) { /*lock*/ t2: data = 1; t3: } /*unlock*/ For every non-volatile variable v, acquireHistory(v) stores the set of safe accesses by thread t via a synchronization operation on s. Thread2’s safe access on data is noted as an example behavior.
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Perform that synchronized block s1: print (data); Thread 1 Thread 2 t1: synchronized (lock) { /*lock*/ t2: data = 1; t3: } /*unlock*/ data is not volatile Perform synchronized (lock) to access data source statement removes data from h(thread1) manifest statement Accesses data when data is not in h(thread1) s0: synchronized (lock) { /*lock*/ s2: } /*unlock*/
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An Example for change another to volatile Initialization: int x; boolean done = false; /* both non- volatile*/ s1: x = 1; Thread 1 Thread 2 t1: while (!done); t2: assert(x == 1); s2: done = true; Potential data races both on x and done. Should we really change both to x and done to volatile? Can we get away by changing only one?
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Change other to volatile s1: x = 1; Thread 1 Thread 2 t1: while (!done); t2: assert(x == 1); s2: done = true; x and done are not volatile source statement removes x from h(thread2) manifest statement accesses x when x is not in h(thread2) Change done to volatile
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JRF-E: Eliminating Data Races JRF is configured to produce threshold # of counter-example paths and write to a file JRF-E works on the output of JRF and analyzes the counter- example paths to generate code modification suggestions For each race reports intersection of suggestions on all the relevant counter- example paths For each specific code modification suggestion reports the frequency
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JRF-E RESULT ====================================================== data race #1 jrf.hbset.util.HBDataRaceException... ______________________________________________________ analyze counter example data race source statement : "putstatic" at simple/SimpleRace.java:64 : "x = 1;" data race manifest statement : "getstatic" at simple/SimpleRace.java:74: "assert (x==1);" Change the field "simple.SimpleRace.x from INITIALIZER" to volatile. Change the field "simple.SimpleRace.done from INITIALIZER" to volatile. ______________________________________________________ advice from acquiring history NONE ====================================================== data race #2 jrf.hbset.util.HBDataRaceException... ______________________________________________________ analyze counter example data race source statement : "putstatic" at simple/SimpleRace.java:65 : "done = true;" data race manifest statement : "getstatic" at simple/SimpleRace.java:73: "while(!done) { /*spin*/ }" Change the field "simple.SimpleRace.done from INITIALIZER" to volatile. ______________________________________________________ advice from acquiring history NONE ______________________________________________________ frequency of advice [1times] Change the field "simple.SimpleRace.x from INITIALIZER" to volatile. [2times] Change the field "simple.SimpleRace.done from INITIALIZER" to volatile. ______________________________________________________ statistic JRF takes 0:0:1 to find 2 equivalent races with 9 counterexample traces. JRF-E takes 0:0:0 in 9 races analysis. How did it happen? How many times a suggestion has been made considering all the races? feedback on a single race feedback on all races How to fix it? feedback on another race
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JRF-E - Analyzing threshold # of races In all except MCSLock, the right suggestion made when Threshold <= 10.
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Suggestions that worked LengthThreshold# of Racy Fields Change (other) to volatile Change to atomic array Use synchronized block DisBarrier40121 LockFreeHashS et 50141 OptimisticList42131 MCSLock6510032 LinearSenseBar rier. 611021 Iterator_EBDeq ue 11111 Lufact19111 Sor44121 Webserver Sim.68121
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Conclusion Even experts can benefit from tool support for detecting data races. JRF can also analyze synchronization idioms that do not use locking. Has become an official extension of Java Path Finder http://babelfish.arc.nasa.gov/trac/jpf JRF-E makes working suggestions for most of the data races in our experiments. JRF-E can teach programmers the intricacies of Java Memory Model.
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Thank You Questions?
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