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Java PathRelaxer: Extending JPF for JMM-Aware Model Checking Huafeng Jin, Tuba Yavuz-Kahveci, and Beverly Sanders Computer and Information Science and Engineering University of Florida

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Contents Memory Model The Java Memory Model Algorithm Implementation Experience Conclusion

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Contents Memory Model The Java Memory Model Algorithm Implementation Experience Conclusion

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Specifies “which value each read of a memory location may return”. Sequentially consistent (SC) memory model Memory actions must execute one at a time in a single total single order Read always see the value of the most recent write to that memory location. Relaxed memory models PSO, TSO, Java Memory Model (JMM), etc. Memory Model

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Specifies “which value each read of a memory location may return”. Sequentially consistent (SC) memory model Memory actions must execute one at a time in a single total single order Read always see the value of the most recent write to that memory location. Relaxed memory models PSO, TSO, Java Memory Model (JMM), etc. Memory Model JPF assumes SC memory model

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Example Intially, x = 0, done = false Intially, x = 0, done = false SCMM r == 1 Thread-1Thread-2 x = 1; done = true; while (!done){/*spin*/} r = x;

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Example Intially, x = 0, done = false Intially, x = 0, done = false Thread-1Thread-2 x = 1; done = true; while (!done){/*spin*/} r = x; SCMM r == 1 JMM r == 0 ˅ r == 1

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Java’s String class public final class String{ private final char value[]; private final int offset; private final int count; private int hash; //default 0 … public int hashCode(){ int h = hash, len = count; //read of hash if (h == 0 && len > 0){ … /*calculate hash code locally and assign to h*/ hash = h; //write of hash } return h; } Data race is benign in both SC MM and JMM

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Another Version public final class String{ private final char value[]; private final int offset; private final int count; private int hash; //default 0 … public int hashCode(){ int h = hash, len = count; //read of hash if (h == 0 && len > 0){ … /*calculate hash code locally and assign to h*/ hash = h; //write of hash } h = hash; //read of hash return h; } Benign in SC MM but not benign in JMM

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Another Version public final class String{ private final char value[]; private final int offset; private final int count; private int hash; //default 0 … public int hashCode(){ int h = hash, len = count; //read of hash if (h == 0 && len > 0){ … /*calculate hash code locally and assign to h*/ hash = h; //write of hash } h = hash; //read of hash return h; } Benign in SC MM but not benign in JMM Return hash code or 0

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JPF: generates executions under SC memory model. JPR: generates executions under an overapproximation of JMM. Extending JPF

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Contents Memory Model The Java Memory Model Algorithm Implementation Experience Conclusion

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SC memory model: Read sees most recent write to that location. Java memory model: Read sees any write (past/future) to that location provided the execution is Well-formed Meets causality constraints Overview of JMM

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Action (memory related) Action (memory related) Non-synchronization actions: non-volatile write, non-volatile read Synchronization actions: volatile write, volatile read, lock, unlock, thread start, thread join, … JMM Action tThread ID kAction kind (volatile read/write, non-volatile read/write, lock/unlock, thread start, thread join …) vVariable/monitor uUnique action ID

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Execution E Execution E JMM Execution AFinite set of actions PProgram ≤ po Program order, a partial order over A based on each thread’s sequence. ≤ so Synchronization order, a total order over all the synchronization actions in A WWrite-seen function, maps each read action to the write action it sees VValue-written function, maps each write action to the value it writes

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A partial order over actions with regard to ≤ so Synchronizes-with Order ≤ sw unlock(x) ≤ sw subsequent lock(x) volatile write(x)subsequent volatile read(x) start thread t1 st action of thread t Write of default value1 st action in each thread

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A partial order over actions by taking transitive closure of ≤ po and ≤ sw Initially, x == 0 ⋀ done == false, done is volatile Happens-before Order ≤ hb Thread-1Thread-2 x = 1; done = true while (!done){/*spin*/} r = x; ≤ po ≤ sw

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Thread-1Thread-2 x = 1; done = true while (!done){/*spin*/} r = x; A partial order over actions by taking transitive closure of ≤ po and ≤ sw Initially, x == 0 ⋀ done == false, done is volatile Happens-before Order ≤ hb ≤ po ≤ sw ≤ hb

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In an execution Data Race Thread-1: … Write … Thread-2: … Read … x ≤ hb

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A program: If all the SC executions are free of data races, it is Data-Race-Free program (DRF). If all the SC executions are free of data races, it is Data-Race-Free program (DRF). DRF Guarantee: Any legal execution of DRF program is SC. Data Race Free

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For all reads r of variable v, it cannot be r ≤ hb W(r) W(r) ≤ hb w ≤ hb r (w writes to v) Well-formed Execution

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r can only be 1, not 0 Initially, x == 0 ⋀ done == false, done is volatile Example Thread-1Thread-2 x = 1; done = true while(!done) {/*spin*/} r = x; ≤ po ≤ sw If read x = 0, then there is an interleaving write x = 1.

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An execution E with ≤ hb is legal if there is a finite sequence of set of actions C i and well- formed executions E i with ≤ hbi and ≤ swi such that C 0 = ∅, C i ⊆ C i-1 for all i > 0, ∪ C i = A, and for each i > 0 the following rules are satisfied: An execution E with ≤ hb is legal if there is a finite sequence of set of actions C i and well- formed executions E i with ≤ hbi and ≤ swi such that C 0 = ∅, C i ⊆ C i-1 for all i > 0, ∪ C i = A, and for each i > 0 the following rules are satisfied: Causality Rules (complicated)

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An execution E with ≤ hb is legal if there is a finite sequence of set of actions C i and well- formed executions E i with ≤ hbi and ≤ swi such that C 0 = ∅, C i ⊆ C i-1 for all i > 0, ∪ C i = A, and for each i > 0 the following rules are satisfied: An execution E with ≤ hb is legal if there is a finite sequence of set of actions C i and well- formed executions E i with ≤ hbi and ≤ swi such that C 0 = ∅, C i ⊆ C i-1 for all i > 0, ∪ C i = A, and for each i > 0 the following rules are satisfied: Causality Rules (complicated) E → E 1 → E 2 → … → E i ∅ C1C1 C2C2 C i-1 Justify

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Causality Rules: Rules out out-of-thin-air values Example: Initially, x == y == 0, x and y are non-volatile r1 == r2 == 42 is out-of-thin-air value r1 == r2 == 42 is out-of-thin-air value Out-of-thin-air Value Thread-1Thread-2 r1 = x;r2 = y; y = r1;x = r2;

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Contents Memory Model The Java Memory Model Algorithm Implementation Experience Conclusion

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Fixed-point semantics Overapproximation of JMM WriteSet JPR Overview WriteSet Write: add values to Read: Pick value from JPF

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Structure of JPR JPR Driver JPFJMMListener WriteSet old WriteSet new Events Iterative calls Bytecode of the target program

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JPF’s state representation is extended with the following metadata: Metadata WriteSetMemLoc → 2 Aid × Val Collect write values ActionSet2 Action Current set of actions HBSet2 Aid × Aid Collect ≤ hb relations ImposeSet2 Aid × Val Rule out some out-of-thin-air values ReadAid → Aid × ValRecord W(r) and V(W(r)) WriteAid → ValRecord V(w)

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Initially, x == y == 0, x and y are non-volatile. Under JMM, r1 == 1 ⋀ r2 == 1 is possible. Example Thread-1Thread-2 r1 = x;r2 = y; y = 1;x = 1;

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init: x = 0, y = 0; Thread-1Thread-2 A1: r1 = x;B1: r2 = y; A2: y = 1;B2: x = 1; init: x = 0, y = 0 WS(x) = { }, WS(y) = { } IS = ∅ 1 st iteration GWS = ∅ init

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init: x = 0, y = 0; Thread-1Thread-2 A1: r1 = x;B1: r2 = y; A2: y = 1;B2: x = 1; init: x = 0, y = 0 WS(x) = { }, WS(y) = { } IS = ∅ R(A1) =, legal past read A1; r1 = x; 1 st iteration initA1

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init: x = 0, y = 0; Thread-1Thread-2 A1: r1 = x;B1: r2 = y; A2: y = 1;B2: x = 1; init: x = 0, y = 0 WS(x) = { }, WS(y) = {, } IS = ∅, R(A1) = A1; r1 = x; A2: y = 1; 1 st iteration initA1A2

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init: x = 0, y = 0; Thread-1Thread-2 A1: r1 = x;B1: r2 = y; A2: y = 1;B2: x = 1; init: x = 0, y = 0 WS(x) = { }, WS(y) = {, } IS = ∅, R(A1) = A1; r1 = x; A2: y = 1; B1: r2 = y; 1 st iteration init A1A2 B1

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init: x = 0, y = 0; Thread-1Thread-2 A1: r1 = x;B1: r2 = y; A2: y = 1;B2: x = 1; init: x = 0, y = 0 WS(x) = { }, WS(y) = {, } IS = ∅, R(A1) =, R(B1) = legal past read A1; r1 = x; A2: y = 1; B1: r2 = y; 0 1 st iteration init A1A2 B1

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init: x = 0, y = 0; Thread-1Thread-2 A1: r1 = x;B1: r2 = y; A2: y = 1;B2: x = 1; init: x = 0, y = 0 WS(x) = {, }, WS(y) = {, } IS = ∅, R(A1) =, R(B1) = A1; r1 = x; A2: y = 1; B1: r2 = y; 0 B2: x = 1; r1 = 0, r2 = 0 1 st iteration init A1A2 B1B2

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init: x = 0, y = 0; Thread-1Thread-2 A1: r1 = x;B1: r2 = y; A2: y = 1;B2: x = 1; init: x = 0, y = 0 WS(x) = {, }, WS(y) = {, } IS = ∅, R(A1) =, R(B1) = legal past read A1; r1 = x; A2: y = 1; B1: r2 = y; 0 B2: x = 1; 1 1 st iteration init A1A2 B1

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init: x = 0, y = 0; Thread-1Thread-2 A1: r1 = x;B1: r2 = y; A2: y = 1;B2: x = 1; init: x = 0, y = 0 A1; r1 = x; A2: y = 1; B1: r2 = y; 0 B2: x = 1; r1 = 0, r2 = 1 1 WS(x) = {, }, WS(y) = {, } IS = ∅, R(A1) =, R(B1) = 1 st iteration init A1A2 B1B2

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init: x = 0, y = 0; Thread-1Thread-2 A1: r1 = x;B1: r2 = y; A2: y = 1;B2: x = 1; init: x = 0, y = 0 A1; r1 = x; A2: y = 1; B1: r2 = y; 0 B2: x = 1; 1 B1: r2 = y; WS(x) = { }, WS(y) = { } IS = ∅, R(A1) =, R(B1) = 0 legal past read 1 st iteration init A1 B1

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init: x = 0, y = 0; Thread-1Thread-2 A1: r1 = x;B1: r2 = y; A2: y = 1;B2: x = 1; init: x = 0, y = 0 A1; r1 = x; A2: y = 1; B1: r2 = y; 0 B2: x = 1; 1 B1: r2 = y; A2: y = 1; WS(x) = { }, WS(y) = {, } IS = ∅, R(A1) =, R(B1) = 1 st iteration init A1A2 B1

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init: x = 0, y = 0; Thread-1Thread-2 A1: r1 = x;B1: r2 = y; A2: y = 1;B2: x = 1; init: x = 0, y = 0 A1; r1 = x; A2: y = 1; B1: r2 = y; 0 B2: x = 1; 1 B1: r2 = y; A2: y = 1; B2: x = 1; WS(x) = {, }, WS(y) = {, } IS = ∅, R(A1) =, R(B1) = r1 = 0, r2 = 0 1 st iteration init A1A2 B1B2

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init: x = 0, y = 0; Thread-1Thread-2 A1: r1 = x;B1: r2 = y; A2: y = 1;B2: x = 1; init: x = 0, y = 0 A1; r1 = x; A2: y = 1; B1: r2 = y; 0 B2: x = 1; 1 B1: r2 = y; A2: y = 1; B2: x = 1; A2: y = 1; WS(x) = {, }, WS(y) = {, } IS = ∅, R(A1) =, R(B1) = r1 = 0, r2 = 0 1 st iteration init A1A2 B1B2

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init: x = 0, y = 0; Thread-1Thread-2 A1: r1 = x;B1: r2 = y; A2: y = 1;B2: x = 1; init: x = 0, y = 0 A1; r1 = x; A2: y = 1; B1: r2 = y; 0 B2: x = 1; 1 B1: r2 = y; A2: y = 1; B2: x = 1; A2: y = 1; B1: r2 = y; WS(x) = { }, WS(y) = { } IS = ∅ R(B1) = legal past read 1 st iteration initB1

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init: x = 0, y = 0; Thread-1Thread-2 A1: r1 = x;B1: r2 = y; A2: y = 1;B2: x = 1; init: x = 0, y = 0 A1; r1 = x; A2: y = 1; B1: r2 = y; 0 B2: x = 1; 1 B1: r2 = y; A2: y = 1; B2: x = 1; A2: y = 1; B1: r2 = y; A1; r1 = x; WS(x) = { }, WS(y) = { } IS = ∅ R(B1) =, R(A1) = legal past read 1 st iteration init A1 B1

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init: x = 0, y = 0; Thread-1Thread-2 A1: r1 = x;B1: r2 = y; A2: y = 1;B2: x = 1; init: x = 0, y = 0 A1; r1 = x; A2: y = 1; B1: r2 = y; 0 B2: x = 1; 1 B1: r2 = y; A2: y = 1; B2: x = 1; A2: y = 1; B1: r2 = y; A1; r1 = x; A2: y = 1; B2: x = 1; A2: y = 1; r1 = 0, r2 = 0 1 st iteration

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init: x = 0, y = 0; Thread-1Thread-2 A1: r1 = x;B1: r2 = y; A2: y = 1;B2: x = 1; init: x = 0, y = 0 A1; r1 = x; A2: y = 1; B1: r2 = y; 0 B2: x = 1; 1 B1: r2 = y; A2: y = 1; B2: x = 1; A2: y = 1; B1: r2 = y; A1; r1 = x; A2: y = 1; B2: x = 1; A2: y = 1; B2: x = 1; A1; r1 = x; 0 A2: y = 1; 1 r1 = 0, r2 = 1 1 st iteration

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r1 = 0, r2 = 1 The WriteSet collected after 1 st iteration is GWS(x) = {, } GWS(y) = {, } It is passed to the 2 nd iteration init: x = 0, y = 0; Thread-1Thread-2 A1: r1 = x;B1: r2 = y; A2: y = 1;B2: x = 1;

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init: x = 0, y = 0; Thread-1Thread-2 A1: r1 = x;B1: r2 = y; A2: y = 1;B2: x = 1; init: x = 0, y = 0 WS(x) = {, }, WS(y) = {, } IS = ∅ 2 nd iteration GWS(x) = {, } GWS(y) = {, } init

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init: x = 0, y = 0; Thread-1Thread-2 A1: r1 = x;B1: r2 = y; A2: y = 1;B2: x = 1; init: x = 0, y = 0 WS(x) = {, }, WS(y) = {, } IS = ∅ 2 nd iteration A1: r1 = x; initA1

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init: x = 0, y = 0; Thread-1Thread-2 A1: r1 = x;B1: r2 = y; A2: y = 1;B2: x = 1; init: x = 0, y = 0 WS(x) = {, }, WS(y) = {, } IS = { }, R(A1) = potential future read 2 nd iteration A1: r1 = x; 0 1 … initA1

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init: x = 0, y = 0; Thread-1Thread-2 A1: r1 = x;B1: r2 = y; A2: y = 1;B2: x = 1; init: x = 0, y = 0 WS(x) = {, }, WS(y) = {, } IS = { }, R(A1) = 2 nd iteration A1: r1 = x; 0 1 A2: y = 1; … initA1A2

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init: x = 0, y = 0; Thread-1Thread-2 A1: r1 = x;B1: r2 = y; A2: y = 1;B2: x = 1; init: x = 0, y = 0 WS(x) = {, }, WS(y) = {, } IS = { }, R(A1) = 2 nd iteration A1: r1 = x; 0 1 A2: y = 1; B1: r2 = y; … init A1A2 B1

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init: x = 0, y = 0; Thread-1Thread-2 A1: r1 = x;B1: r2 = y; A2: y = 1;B2: x = 1; init: x = 0, y = 0 WS(x) = {, }, WS(y) = {, } IS = { }, R(A1) =, R(B1) = 2 nd iteration A1: r1 = x; 0 1 A2: y = 1; B1: r2 = y; 01 … … init A1A2 B1

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init: x = 0, y = 0; Thread-1Thread-2 A1: r1 = x;B1: r2 = y; A2: y = 1;B2: x = 1; init: x = 0, y = 0 WS(x) = {, }, WS(y) = {, } IS = { }, justified R(A1) =, R(B1) = 2 nd iteration A1: r1 = x; 0 1 A2: y = 1; B1: r2 = y; 01 B2: x = 1; … … r1 = 1, r2 = 1 init A1A2 B1B2

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3 rd iteration generates the same global WriteSet as 2 nd iteration, so a fixed-point is reached. Possible outcomes running JPR: r1 == 0 ⋀ r2 == 0 r1 == 0 ⋀ r2 == 1 r1 == 1 ⋀ r2 == 0 r1 == 1 ⋀ r2 == 1 Example

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Contents Memory Model The Java Memory Model Algorithm Implementation Experience Conclusion

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JRF (Java Racefinder) is a JPF extension used to precisely detect data races. Kyunghee Kim, Eric Mercer, Neha Rungta, Tuba Yavuz-Kahveci, Beverly Sanders http://babelfish.arc.nasa.gov/trac/jpf/wiki/proje cts/jpf-racefinder Working with JRF

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Data Race Free (DRF) Guarantee For DRF programs, model checking under SC memory model is enough. JPF is sufficient, no need to run JPR. Working with JRF

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JRF JPF JPR DRF? Y DRF? N

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Contents Memory Model The Java Memory Model Algorithm Implementation Experience Conclusion

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Group 1 tc1 – tc20 from JMM causality test cases http://www.cs.umd.edu/~pugh/java/memoryModel/unified Proposal/testcases.html Group 2 Benign data races (hash code, is prime) Group 3 Harmful data races (dcl, peterson, dekker) Testing Suites

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Experiment Results Test Cases Time (milliseconds)

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Experiment Results Test Cases Time (milliseconds) JPR takes much longer time than JPF: Iterations Data choice generators

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Experiment Results Test Cases Number of states

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Contents Memory Model The Java Memory Model Algorithm Implementation Experience Conclusion

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JPR: Applies a fixed-point based semantic Adds non-SC behaviors into JPF Generates an overapproximiation of JMM Conclusion

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