Controlling Reversibility in Rhopi

1. Controlling Reversibility in Rhopi Ivan Lanese Computer Science Department Focus research group University of Bologna/INRIA Bologna, Italy Joint work with Claudio Antares Mezzina (INRIA), Jean-Bernard Stefani (INRIA) and Alan Schmitt (INRIA)

2. Roadmap • Our aim • Reversibility • A rollback operator • Conclusions

3. Roadmap • Our aim • Reversibility • A rollback operator • Conclusions

4. Do you remember Rhopi? • What I will present is a follow-up of Rhopi’s talk, presented by Claudio Mezzina at last seminar • I will briefly recall it, but mainly build on top of it

5. What Rhopi really is? • Rhopi, as well as the calculi RCCS and CCSk, propose (slightly different) answers to the same question: How can we reverse a process?

6. A tool • For us, Rhopi is a tool • We want to reverse processes to program dependable distributed systems • The same tool can be used also for different purposes (e.g., modelling biological systems) • Rhopi alone is not enough • We want to go back only in case of errors • We want to specify how far back to go • We want to avoid repeating the same errors • We want to make the good results permanent • We want to add compensations to the mix

7. Drawbacks of Rhopi alone

8. Drawbacks of Rhopi alone

9. Drawbacks of Rhopi alone

10. Drawbacks of Rhopi alone

11. Drawbacks of Rhopi alone

12. Drawbacks of Rhopi alone

13. Drawbacks of Rhopi alone

14. Drawbacks of Rhopi alone

15. Drawbacks of Rhopi alone

16. Drawbacks of Rhopi alone • Absolutely no control • Impossible to make a result permanent • The activity producing it can always be undone • No commit • All the states are (weak) equivalent • Each program is either stuck or divergent

17. The small-step approach • Add simple mechanisms for controlling reversibility • In RCCS: irreversible actions • Here: a rollback primitive • Other interesting possibilities exist • Understand their behavior • In a concurrent setting • Expressive power

18. Final destination • Can reversibility act as an underlying theory for understanding various techniques for dependability in distributed systems? • Checkpointing • Transactions • Apple Time Machine • …

19. Roll-pi idea • Normal computation goes forward • There is an explicit primitive, roll γ, to trigger a rollback • γ refers to a specific point in the past of the program • In a concurrent world, difficult to speak about time • We refer to an action to undo • Includes undoing all the actions depending on it • … and now we need some formal stuff

20. Roadmap • Our aim • Reversibility • A rollback operator • Conclusions

21. h i P Q P : : a m e s s a g e = ; j ( ) X P i t . a r g g e r j ( j ) l l l P Q i i t p a r a e c o m p o s o n j P º a n e w n a m e : j b l X i v a r a e j l l 0 n u p r o c e s s Q h i j ( ( ) ) f = g Q X P P . a a ! X HOpi fundamentals

22. h i j ( ( ) ) j ( j ) j j j P Q P X P P Q P X 0 . : : a a º a = ; : ¯ M N i t c o n g u r a o n s : : = ; h d P t r e a · : j [ ] k m e m o r y m ; j ( j ) l l l M N p a r a e j M i i t t r e s r c o n º u : j l l ¯ i 0 t n u c o n g u r a o n ~ j h i k h h k t ¢ a g s · : : = ; ( ( h i ) j ( ( ) ) ) d P X Q i t . a c o n r e c o r m : : · : a · : a = 1 2 Rhopi syntax

23. ( h i ) j ( ( ) ) P X Q . m · : a · : a = 1 2 F o r w a r d : P ( h i ) j ( ( ) ) ( f = g ) j [ ] k k k P X Q Q ³ . · : a · : a º : m ; X 1 2 : ( ) j [ ] k k P B a c k w a r d : m ; m : Ã Rhopi semantics • A forward rule similar to HOpi, managing tags and creating a memory • A backward rule for going back

24. ( h ( i ) ) h h i h j i i k k k b b d X P X X 0 0 . . : : : a a c 3 2 1 Rhopi example

25. [ h ( ( h h j i ) ) i i h h i h j i i ] k k k k k b b d k b d k M X X P N X 0 0 0 . . : : : : : a a c : ; 2 1 3 1 2 Rhopi example

26. [ [ ( h ( ( h h h h h j i ) i ) i j i i i h h j h i i h ) j i i ] ] k k k k k k k b b b d d k d b d k k k M X P X N X N 0 0 0 0 0 0 . . : : : : : : : a a c c : ; : ; 3 1 4 2 1 2 3 1 4 Rhopi example

27. [ h ( ( h h j i ) ) i i h h i h j i i ] k k k k k b b d k b d k M X X P N X 0 0 0 . . : : : : : a a c : ; 2 1 3 1 2 Rhopi example

28. ( h ( i ) ) h h i h j i i k k k b b d X P X X 0 0 . . : : : a a c 3 2 1 Rhopi example

29. Roadmap • Our aim • Reversibility • A rollback operator • Conclusions

30. j j j ( j ) j h i j ( ) j l l P Q X P P Q P X P 0 . r o : : º a a a ° = ° ; : j j ( j ) j j [ ] k M N M M N P 0 : : º u · : ¹ ; = ; : Roll pi syntax • Extends Rhopi syntax • Adds the primitive roll γ for triggering rollback • Adds a γ label to triggers • The idea: roll γ takes the system back to the state before the trigger labelled by γ has been consumed • More precisely: undoes all the steps caused by the interaction involving the trigger labelled by γ

31. ( h i ) j ( ( ) ) P X Q . m · : a · : a = 1 2 ° ( ) C & N o m k P k ( h i ) j ( ( ) ) ( f = g ) j [ ] k k k P X Q Q ³ ; . · : a · : a º : m ; X 1 2 ° ° : ; ( j [ ] j ( ) ) k k l l k N N l t I r o c o m p e e m ; · : ( ) N a i v e j [ ] j ( ) j k l l k & N N r o m ; · : m à k Giving semantics: naïve try • The forward rule uses the key k to replace the placeholder γ • A rule for roll • N ►k verifies that all the elements in N are related to k • Complete checks that the term is closed under causal relation • contains the elements in N not related to k

32. ( h ( i ) ) h h i j i k k k b b l l X X X 0 0 . . r o : : : a a c ° 3 2 1 ° Naïve semantics example

33. [ h ( h ( i j ) ) i h h i j ] i k k k k k b b l l k k b l k l M X X N X 0 0 . . r o r o : : : : : a a c : ; ° 1 3 2 1 2 ° Naïve semantics example

34. ~ ~ h [ h [ h ( h ( i i i j j ) ) i h h h i i j ] i ] k k k k k k h h b b h h l k k l k k k b l l k l k l k M M X X N N X 0 0 0 . . r o ¢ ¢ r o r o : : : : : : a a : : c : : c ; ; ° 3 2 1 1 1 2 1 4 4 2 3 1 4 ° ; ; Naïve semantics example

35. ~ ~ h [ h [ h ( h ( i i i j j ) ) i h h h i i j ] i ] k k k k k k h h b b h h l k k l k k k b l l k l k l k M M X X N N X 0 0 0 . . r o ¢ ¢ r o r o : : : : : : a a : : c : : c ; ; ° 3 2 1 1 1 2 1 4 4 2 3 1 4 ° ; ; Naïve semantics example

36. ( h ( i ) ) h h i j i k k k b b l l X X X 0 0 . . r o : : : a a c ° 3 2 1 ° Naïve semantics example

37. k k l l l l k k r r o o 1 1 The concurrency anomaly

38. k k l l l l k k r r o o 1 1 The concurrency anomaly

39. k 1 The concurrency anomaly

40. k k l l l l k k r r o o 1 1 The concurrency anomaly

41. k The concurrency anomaly

42. The concurrency anomaly • Intuitively, I have rolls for undoing every action… • …but I am not able to go back to the starting state • I miss the possibility of performing rollbacks concurrently • Can I write a semantics capturing this aspect?

43. ( h i ) j ( ( ) ) P X Q . m · : a · : a = 1 2 ° ( ) C o m k P ( h i ) j ( ( ) ) ( f = g ) j [ ] k k k P X Q Q ³ ; . · : a · : a º : m ; X 1 2 ° ° : ; ( ) j [ ] ( ) j [ ] ² l l k k l l k k ( ) S t a r t r o r o · : m ; · : m ; à 1 1 ( j [ ] ) k k N N l t I c o m p e e m ; ( ) R o l l j [ ] j ² k & N N m ; m à k Giving semantics: taming concurrency • The rollback has been splitted in two steps • Tagging the memory • Executing the rollback of a tagged memory

44. k k l l l l k k r r o o 1 1 Concurrent rollback

45. k k l l l l k k r r o o 1 1 Concurrent rollback

46. k k l l l l k k r r o o 1 1 Concurrent rollback

47. k 1 Concurrent rollback

48. Concurrent rollback

49. 0 0 0 f h h d k d ¤ ¤ M M M M M M i i t t ³ e n w a n u n m a r e à , Properties of concurrent semantics • Correct • If I go backward from M, I reach a state able to go forward to M • Complete • I can simulate any number of concurrent rollbacks • Good as abstract specification

50. Going towards an implementation • The concurrent semantics is very high-level • Includes atomic steps involving an unbounded number of participants • Concurrently executing • Possibly distributed • Can we refine the semantics to a more distributed one? • Giving the same final result • Yes! • But technicalities are quite complex…