Modelling Dynamic Web Data

1. Sergio Maffeis Joint work with Philippa Gardner Modelling Dynamic Web Data APPSEM'04 Tallinn, 15 April 2004

2. Motivation

3. What is dynamic Web data? We model large scale, peer-to-peer systems for sharing dynamic data over the Web. • Distribution is on large scale • Each site provides and consumes data using a (standardised) set of functionalities • Data is dynamic and intensional: can contain calls to Web services, forms, scripted code, etc... • Data is interlinked

4. Modelling dynamic Web data Existing models: • query languages for semistructured data (XML) • Describe data manipulation • Do not include a distribution layer • process calculi for the distributed infrastructure • Are good at orchestrating data exchanges between peers • Tend to abstract from the actual data Modelling dynamic Web data requires merging these approaches.

5. A unified framework Reasoning about data and the distributed infrastructure in the same framework provides means to • understand the system behaviour • give schema/types to documents containing scripts • control access to resources • propose new optimisations

6. The Xd project • Dynamic Web data in Xd • syntax, sematics, examples • Observational equivalences • spectrum of network and process equivalences • Proof techniques • domain bisimilarity • Types and security • access control, data validation • Implementation • declarative platform for intensional data and WS-coordination

7. Dynamic Web data in Xd

8. L2 L1 L3 Xd Processes Trees L4 • A flat space of locations • Locations contain (XML) trees and coordination processes

9. Representing data in Xd a a a a c c b Processes c b Processes T3 @L1:a/c P T’ T2 T1 L2 L1 • Unordered, edge-labelled trees • Scripted processes (no reflection) • Pointers (links)

10. T’ P’ L1 Data manipulation: cut = cuta/e(X).pastea/c<X> a a c P b c b e Q T L2 • select some subtrees with a path expression

11. T’ P’ L1 Data manipulation: cut X= = cuta/e(X).pastea/c<X> T a a c P b c b e Q T L2 • select some subtrees with a path expression • match the subtrees against a binding pattern

12. T’ P’ L1 Data manipulation: cut X= = cuta/e(X).pastea/c<> T T a a c P b c b e Q T L2 • select some subtrees with a path expression • match the subtrees against a binding pattern • cut away the subtrees

13. T’ P’ L1 Data manipulation: paste = cuta/e(X).pastea/c<> T a a c P b c b e T Q L2 • select some paths for pasting

14. T’ P’ L1 Data manipulation: paste = cuta/e(X).pastea/c< > T a a c P b c b e Q T L2 • select some paths for pasting • paste the subtrees in place

15. T’ P’ L1 Data manipulation = cuta/e(X).pastea/c< > T a a c P b c b e Q T L2 • Encode cut, copy, paste by general update command • Simple path expressions as query language (multiple selection) • Other choices possible

16. a a c b c b e T Process selection = runc a a c P R b c b e Q L1 L2 runactivates scripts: click on a hyperlink, system event, ...

17. a a c b c b e T Process selection = runc a a c P R b c b e Q L1 L2 runactivates scripts: click on a hyperlink, system event, ...

18. a a c b c b e T • = intuitive specification of a hyperlink Process migration = go L2.copya/c(X).go L1.pastea/e<X> a a c P R b c b e Q L1 L2

19. a a c b c b e T • = intuitive specification of a hyperlink Process migration = go L2.copya/c(X).go L1.pastea/e<X> a a c P R b c b e Q L1 L2

20. = intuitive specification of a hyperlink Process migration = go L2.copya/c(X).go L1.pastea/e< > T a a a a c c P R b b c b c b e T e Q T L1 L2

21. = intuitive specification of a hyperlink Process migration = go L2.copya/c(X).go L1.pastea/e< > T a a a a c c P R b b c b c b e T e Q T L1 L2

22. = intuitive specification of a hyperlink • over-simplified Process migration = go L2.copya/c(X).go L1.pastea/e<X> a a a a c c P R b b c b c b e e Q T T L1 L2

23. Communication = web service call = web service = result handling code = service instance a a a a c c P R b b c b c b e e Q T L1 L2

24. Communication = go L2.get<a/c,L1> = !get(x,y).copyx(z).go y.put<z> = put(x).pastea/e<x> a a a a c c P R b b c b c b e e Q T L1 L2

25. Communication = go L2.get<a/c,L1> = !get(x,y).copyx(z).go y.put<z> = put(x).pastea/e<x> a a a a c c P R b b c b c b e e Q T L1 L2

26. Communication = go L2.get<a/c,L1> = !get(x,y).copyx(z).go y.put<z> = put(x).pastea/e<x> = copya/c(z).go L1.put<z> a a a a c c P R b b c b c b e e Q T L1 L2

27. Communication = go L2.get<a/c,L1> = !get(x,y).copyx(z).go y.put<z> = put(x).pastea/e<x> T = copya/c(z).go L1.put< > a a a a c c P R b b c b c b e e T Q T L1 L2

28. Communication = go L2.get<a/c,L1> = !get(x,y).copyx(z).go y.put<z> = put(x).pastea/e<x> T = copya/c(z).go L1.put< > a a a a c c P R b b c b c b e T e Q T L1 L2

29. Communication = go L2.get<a/c,L1> = !get(x,y).copyx(z).go y.put<z> = put(x).pastea/e< > T = copya/c(z).go L1.put< > T a a a a c c P R b b c b c b e T e Q T L1 L2

30. Communication = go L2.get<a/c,L1> = !get(x,y).copyx(z).go y.put<z> = put(x).pastea/e< > T = copya/c(z).go L1.put< > T a a a a c c P R b b c b c b e e Q T T L1 L2 Potential problem: who can return a result to put?

31. Restriction = go L2.get<a/c,L1> = !get(x,y).copyx(z).go y.put<z> = put(x).pastea/e<x> a a a a c c P R b b c b c b e e Q T L1 L2

32. Restriction = go L2.get<a/c,L1,put> = !get(x,y,w).copyx(z).go y.w<z> = put(x).pastea/e<x> a a a a c c P R b b c b c b e e Q T L1 L2 • Add the return channel put as a parameter to get

33. Restriction = go L2.get<a/c,L1,put> = !get(x,y,w).copyx(z).go y.w<z> = put(x).pastea/e<x> = (new put)( | ) a a a a c c P R b b c b c b e e Q T L1 L2 • Add the return channel put as a parameter to get • Make put an unforgeable secret with restriction binder (new put)(-)

34. Restriction = go L2.get<a/c,L1,put> = !get(x,y,w).copyx(z).go y.w<z> = put(x).pastea/e<x> = (new put)( | ) a a a a c c P R b b c b c b e e Q T L1 L2

35. Restriction = go L2.get<a/c,L1,put> = !get(x,y,w).copyx(z).go y.w<z> = put(x).pastea/e<x> = (new put)( | ) a a a a c c P R b b c b c b e e Q T L1 L2

36. Restriction = go L2.get<a/c,L1,put> = !get(x,y,w).copyx(z).go y.w<z> = put(x).pastea/e<x> = (new put)( | ) a a a a c c P R b b c b c b e e Q T L1 L2

37. Restriction = go L2.get<a/c,L1,put> = !get(x,y,w).copyx(z).go y.w<z> = put(x).pastea/e<x> = (new put)( | ) a a a a c c P R b b c b c b e e T Q T L1 L2

38. Restriction = go L2.get<a/c,L1,put> = !get(x,y,w).copyx(z).go y.w<z> = put(x).pastea/e<x> = (new put)( | ) a a a a c c P R b b c b c b e e T Q T L1 L2

39. Restriction = go L2.get<a/c,L1,put> = !get(x,y,w).copyx(z).go y.w<z> = put(x).pastea/e<x> = (new put)( | ) a a a a c c P R b b c b c b e T e Q T L1 L2

40. Restriction = go L2.get<a/c,L1,put> = !get(x,y,w).copyx(z).go y.w<z> = put(x).pastea/e<x> = (new put)( | ) a a a a c c P R b b c b c b e e Q T T L1 L2 • Nothing can interefere with put now • Interference with get at L2: same technique, types, …

41. Function repository Data Repository Data warehouse Example: rendez-vous Client L2 L1 L3 L4

42. Function repository Data Repository Data warehouse Example: rendez-vous Client L2 L1 L3 L4

43. Function repository Data Repository Data warehouse Example: rendez-vous Client L2 L1 L3 L4

44. Function repository Data Repository Data warehouse Example: rendez-vous Client L2 L1 L3 L4

45. Function repository Data Repository Data warehouse Example: rendez-vous Client L2 L1 L3 L4

46. Function repository Data Repository Data warehouse Example: rendez-vous Client L2 L1 L3 L4

47. Function repository Data Repository Data warehouse Example: rendez-vous Client L2 L1 L3 L4

48. Function repository Data Repository Data warehouse Example: rendez-vous Client L2 L1 L3 L4

49. Function repository Data Repository Data warehouse Example: rendez-vous Client L2 L1 L3 L4

50. Function repository Data Repository Data warehouse Example: rendez-vous Client L2 L1 L3 L4 • Reduce network traffic • Comply to access control policies • Forward streams of results