1. Concurrency Verification

2. Why concurrency verification Concurrent programs show in many systems –Multi-task support in OS kernels –Handling interrupts from external devices –… Will be more common –Multi-core processors Intellectually interesting –Correctness/incorrectness are not obvious

3. Shared-State Concurrency Model Memory A B

4. 100 101 Execution Model: Simple Examples T1:T2: [ 100 ] := 3[ 101 ] := 5 35 T1:T2: [ 100 ] := 3[ 100 ] := 5 3/5 Don’t know which one is written first, but order doesn’t matter. Order may affect the result if threads share resources.

5. Execution Model: Simple Examples T1:T2: [ x ] := 3[ y ] := 5 x y x y 35 3/5 It is difficult to discuss resource sharing with memory pointer aliasing.

6. Execution Model: Simple Examples T1:T2: C 11 ; C 12 ; C 1n C 21 ; C 22 ; C 2n T1 T2 Non-deterministic interleaving may produce exponential num. of execution traces; Different traces may lead to different results (depends on the resource sharing).

7. Challenges to reason about concurrent programs Sharing of resources makes the result dependent on the ordering of execution Non-deterministic interleaving produces exponential num. of possible ordering Memory pointer aliasing makes it difficult to tell how resources are shared

8. Outline of this Lecture Separation Logic Review Concurrent Separation Logic (CSL) Rely-Guarantee Reasoning (R-G) Modular verification of fine-grained concurrency – recent progress

9. Separation Logic A Hoare-style program logic: { p } C { q } What’s new here is the assertion language. [Ishtiaq&O’Hearn’01,Reynolds’02]

10. Separation Logic Assertions l  n n l p  qp  q pq emp empty heap p  qp  q p  q

11. Separation Logic Assertions l  n n l p  qp  q pq emp empty heap l  _ defined as  n. l  n l  n defined as (l  n)  true l n

12. Properties p  emp  p p  q  q  p p  p  p p  true  p p  p  p  (l  _)  (l  _)  false p  p  true p  true  p 

13. Assertions Model Ownership {(l  _)} [l] := m; {(l  m)}  {emp} [l] := m; {???}  Ownership cannot be duplicated: (l  _)  (l  _)  (l  _)

14. Strength of Separation {(x  n)  (y  n)} [x] := m; {(x  m)  (y  n)} {(x  n)  (y  n)} [x] := m; {(x  m)  (y  n)}   what if x=y ?

15. A Frame Rule for Modularity { p } C { q } { p  r } C { q  r } Another example showing the strength of separation! C p q r r

16. Specification of a List top … List (top)  (top = null)  emp   next. top  (_, next)  List ( next ).

17. Example: getNode getNode() if (top <> null){ r1 = top; r2 = top.next; top = r2; } else {r1 = null } { List (top) } { List (top)  top  null } {  next. top  (_, next)  List ( next ) } { r1 = top   next. top  (_, next)  List ( next )  r2 = next } { r1  (_, _)  List ( r2 ) } { r1  (_, _)  List ( top ) }{ List ( top ) * (top = r1 = null  emp  r1  (_, _) ) }

18. Reading Materials http://www.cs.cmu.edu/~jcr/ See the miniCourse webpage of John Reynolds:

19. Outline of This Lecture Separation Logic Review Concurrent Separation Logic (CSL) Rely-Guarantee Reasoning (R-G) Modular verification of fine-grained concurrency – recent progress

20. Separation Logic for Concurrency 100 101 T1:T2: [ 100 ] := 3[ 101 ] := 5 35 T1:T2: [ 100 ] := 3[ 100 ] := 5 3/5 Separation is an effective way to control interference.

21. The language x := e | [e] := e' | x := [e] | cons(e) | dispose(e) | C; C | C || C | … A new construct: l.acq() | l.rel()

22. Operational Semantics ( l.acq(), (s, h, L))  (skip, (s, h, L{l  0}) ) Program state: (s, h, L) where L  locks  {0, 1} L( l ) = 1 ( l.rel(), (s, h, L))  (skip, (s, h, L{l  1}) )

23. How to control interference? Basic idea: –Each thread has private memory (resource) The private resource can be arbitrarily used Private resources of different threads are disjoint –Shared resources are protected by locks Shared resources are disjoint with local resources Can only be used when the lock is acquired (i.e. in critical regions) Different locks protect different resources

24. Basic Memory Model Private Shared (accessible only in critical regions)

25. Basic Memory Model

28. When the resource is acquired/released, it must be well- formed. The well-formedness is resource invariant.

29. Concurrent Separation Logic (CSL) Lock-based critical regions (CR): l.acq(); … l.rel() Invariants about memory protected by locks:  = {l 1  r 1, …, l n  r n } r 1  rn rn l1l1 lnln

30. CSL – Formalization Key ideas: Threads can only access disjoint resources at the same time. p  qp  q pq ┝ {p 2 } C 2 {q 2 } ┝ {p 1 } C 1 {q 1 } ┝ {p 1  p 2 } C 1 || C 2 {q 1  q 2 }

31. CSL – Parallel Composition p  qp  q pq ┝ {p 2 } C 2 {q 2 } ┝ {p 1 } C 1 {q 1 } ┝ {p 1  p 2 } C 1 || C 2 {q 1  q 2 }   I(  )  p 1  p 2 I(  )  q 1  q 2 r 1  rn rn l1l1 lnln We’ll define I(  ) later.

32. CSL - Locks ┝ {p} l.acq() {p   ( l )}  Lock acquire: Note: do not support reentrant locks ┝ {p   ( l )} l.rel() {p}  Lock release: Compare the rules with cons and dispose

33. Examples Put (x): l.acq(); while( full ){ l.rel(); l.acq(); } c := x; full := true; l.rel(); Get (y): l.acq(); while( !full ){ l.rel(); l.acq(); } y := c; full := false; l.rel();  ( l ) = full  c  _, _   full  emp

34. Examples Put (x): l.acq(); while( full ){ l.rel(); l.acq(); }  ( l ) = full  c  _, _   full  emp c := x; full := true; l.rel(); {x  _, _ } {x  _, _   ( l ) } {x  _, _ } {x  _, _   ( l )   full } {x  _, _ } {c  _, _ } {full  c  _, _ } {  ( l ) } {emp }

35. Examples get (y): l.acq(); while( !full ){ l.rel(); l.acq(); }  ( l ) = full  c  _, _   full  emp y := c; full := false; l.rel(); {emp} {  ( l ) } { emp } {  ( l )  full } {c  _, _ } {y  _, _ } {y  _, _  (  full  emp) } {y  _, _   ( l )} {y  _, _ }

36. Examples x := cons(a, b); put(x); get(y); use(y); dispose(y); {x  _, _ } put (x) {emp }{emp} get (y) {y  _, _ } {emp  emp} {emp} {x  _, _ } {emp } {y  _, _ } {emp} {emp  emp}

37. Outline of This Lecture Separation Logic Review Concurrent Separation Logic (CSL) Rely-Guarantee Reasoning (R-G) Modular verification of fine-grained concurrency – recent progress

38. Owicki-Gries Method Susan Owicki and David Gries, 1975

39. Non-Interference Key idea: execution of a statement does not invalidate proofs of other code fragments that may run in parallel with the statement in question. Given a proof {p} c {q}, and a command T whose precondition is pre(T), we say T does not interfere with {p} c {q} if - {q  pre(T)} T {q}; and - for all c’ in c (but not in await), {pre(c’)  pre(T)} T {pre(c’)}

40. Non-Interference {p 1 } c 1 {q 1 }, … {p n } c n {q n } are interference-free if, for any await or primitive statement T (not inside await) in c i, and for all j  i, T does not interfere with {p j } c j {q j }. This method is not compositional!

46. Rely-Guarantee Reasoning Use rely (R) and guarantee (G) conditions to summarize the behaviors of environments and the thread itself. RRR G GG p q

47. Rely-Guarantee Reasoning R and G: specification of state transitions example: x’  x RRR G GG p q

48. Inference Rules

49. Inference Rules (2)

50. Example || {x = 0} {x = 2}

51. y := 0; z := 0; < x := x+1; y := 1; > < x := x+1; z := 1; > || {x = 0} {x = 2} G1  y = 0  y’ = 1  x’ = x+1  z’ = z G2  z = 0  z’ = 1  x’ = x+1  y’ = y R1  G2R2  G1 {x = y+z  y = 0} {x = y+z  z = 0} {x = y+z  y = 1}{x = y+z  z = 1} {x = y+z  y = 0  z = 0} {x = y+z  y = 1  z = 1}

52. Soundness Partial correctness Safety Preservation of R/G

53. Outline of This Lecture Separation Logic Review Concurrent Separation Logic (CSL) Rely-Guarantee Reasoning (R-G) Modular verification of fine-grained concurrency – recent progress

54. An Optimistic Non-blocking Stack ABA problem leads to corrupted stacks … n Next n Top pop( ){ local done, next, t; done = false; while (!done) { t = Top; if (t==null) return null; next = t.Next; done = CAS(&Top, t, next); } return t;

55. ABA Problem Threads T1 and T2 are interleaved as follows: A B C Top t next Timeline T1: pop() { t = Top next = t.Next interrupted resumes CAS(&Top,t,next) succeeds stack corrupted T2: a = pop(); b = pop(); push(a); Top

56. Fix Bugs with Hazard Pointers [Michael04] pop( ){ 1local done, next, t, t1; 2done = false; 3while (!done) { 4 t = Top; 5 if (t==null) return null; 6 HP[tid] = t; 7 t1 := Top; 8 if (t == t1){ 9 next = t.Next; 10 done = CAS(&Top, t, next); 11 } 12} 13retireNode(t); 14HP[tid] = null; 15return t; push(x) 16local done, t; 17done = false; 18while(!done) { 19 t = Top; 20 x.Next := t; 21 done = CAS(&Top, t, x); 22 } 23return true; How to verify its correctness?

57. The key of concurrency verification is to control sharing of resources. Two classic methods: Concurrent Separation Logic (CSL) [O’Hearn 2004] Rely-Guarantee Reasoning [Jones'83]

58. Concurrent Separation Logic Very good modularity –Reduce concurrency verification to seq. verification –Frame rules (will explain later)  Invariant not very expressive for fine-grained alg.  How to say “x cannot decrease in C”? (necessary for fine-grained algorithms)  need extensive use of auxiliary variables  see [Parkinson et al.’07] atomic{ -{ I } C -{ I } }

59. The key of Concurrency Verification is to control sharing of resources. Two classic methods: Concurrent Separation Logic (CSL) [O’Hearn 2004] Rely-Guarantee Reasoning [Jones'83]

60. Rely-Guarantee Reasoning All resources are shared, but access must follow contracts (R-G)! (R1, G1)(R2, G2)

61. Rely-Guarantee Reasoning Thread T and its environment –Environment: the collection of all other threads except T R: rely condition about environment’s transition G: guarantee to the environment p, q: pre-/post-conditions (R,G) ┝ {p} C {q}

62. Rely-Guarantee Reasoning (R1, G1)(R2, G2) Non-Interference (NI): G2  R1 and G1  R2

63. Example … [100] := m; … [101] := n; … 100101 G 1 : [101] = [101]' R 1 : [100] = [100]' G 2 : [100] = [100]' R 2 : [101] = [101]' Modularity broken!

64. Rely-Guarantee Reasoning Expressive for fine-grained concurrency “x cannot decrease”: x'  x  Treat everything as shared; no private data  Limited support of modularity

65. Expressiveness and Modularity Expressiveness of interference Modularity (local reasoning) CSL R-G How to reach here?

66. Modular verification of fine- grained concurrency SAGL [Feng et al’07] RGSep [Vafeiadis & Parkinson’07] LRG [Feng’09] HLRG [Fu et al'10] Deny-Guarantee [Dodds et al'09]

67. SAGL: Separated A-G Logic [Feng et al'07] Key idea: Separate resources into local and shared! Private Shared (R1, G1)(R2, G2)

68. SAGL [Feng et al’07] Separate resources into shared and private Shared can be accessed at any time –governed by R and G –more expressive than I in CSL Exclusive access to private resources –follows local reasoning in CSL –not specified in R and G –better memory modularity (R,G) ┝ {(a, p)} C {(r, q)}

69. Example: regained data modularity … [100] := m; … [101] := n; … 100101 -{(emp, 100  _) } -{(emp, 101  _)} G 1 : emp R 1 : emp G 2 : emp R 2 : emp

70. Expressiveness and Modularity Expressiveness of interference Modularity (local reasoning) CSL R-G SAGL (RGSep) But still not as modular as CSL! More expressive for interference: R/G vs. invariants I More modular: do not specify local data in R/G

71. R-G with Local Reasoning Frame rules in CSL: I ┝ {p} C {q} I  I' ┝ {p} C {q} No corresponding rules in R-G, SAGL and RGSep. (R,G) ┝ {(a, p)} C {(r, q)} All shared resources must be globally known and specified in R/G. Allow local reasoning and information hiding.

72. LRG: Local Rely-Guarantee Reasoning [Feng'09] a  a' S1S1 S2S2 S1'S1'S2'S2' a a' Separating conjunction over R/G: (R 0  R 1,G 0  G 1 ) ┝ {p  r} C {p'  r} side conditions omitted (frame) (R 0,G 0 ) ┝ {p} C {p'}

73. LRG Another interesting rule for modularity: (R 0  R 1,G 0  G 1 ) ┝ {p} C {q} side conditions omitted (R 1,G 1 ) ┝ {p} C {q} (hide) Need invariants as fences R, G, I ┝ {p} C {q}

74. Expressiveness and Modularity Expressiveness of interference Modularity (local reasoning) CSL R-G SAGL RGSep LRG R * R' G * G'

75. HLRG – Adding Histories to R/G [Fu et al.’10] LRG still not good enough to verify the stack algorithm Existing approach: heavy use of history variables. Needs to say “if something happened before in history, then I guarantee that …” Our solution: Adding past-tense temporal operators to assertions and R/G

76. HLRG - Assertion Language State Assertions: Trace Assertions: p, q, R, G::= P | Id | p q | … P, Q ::= B | E E | P * Q | …

77. p q s0s1s2s3s4s5s6 Time p q p holds over the historical trace q holds ever since q q q

78. s0s1s2s3s4s5s6 Time p = (p true)  p p was once true in the history, including the current trace. p

79. p holds at every step in the history p =( p) Time s0s1s2s3s4s5s6 p … p p p

80. p  q Time p q s6s6 s5s5 s4s4 s3s3 s2s2 s1s1 s0s0

81. HLRG R, G, I ┝ {p} C {q} Now R, G, I, p and q are all trace assertions The stack algorithm verified without using history variables!

82. Expressiveness and Modularity Expressiveness of interference Modularity (local reasoning) CSL R-G SAGL RGSep LRG HLRG use trace assertions

83. Expressiveness and Modularity Expressiveness of interference Modularity (local reasoning) CSL R-G SAGL RGSep LRG HLRG Deny- Guarantee A separation algebra for interference (D-G)

84. What do we learn? We need expressive assertions to specify fine-grained interference! Invariant I Actions (R,G) Trace assertions  p,  p, Separation gives us local reasoning (modularity)! All resources as shared Separate local & shared in R/G R  R' and G  G'(  p)  (  q) …

85. Take-home messages: We need expressive assertions to specify fine-grained interference! Separation gives us local reasoning (modularity)!

86. Reading Recommendation Modular fine-grained concurrency verification Viktor’s Thesis Local Rely Guarantee, Xinyu Feng HLRG Deny-Guarantee Reasoning