Slides or our ACM/IEEE MoDELS'16 paper on partial loading of XMI models

1. 1
Par$al Loading of XMI Models
Ran Wei, Dimitris Kolovos, Antonio Garcia-Dominguez,
Konstan9nos Barmpis, Richard Paige
University of York

2. 2

3. 3Outline
• Context: EMF and XMI
• EMF's XMI Parser
• Par9al XMI Loading
• Evalua9on & Limita9ons
• Conclusions & Future Work

4. 4Context
• Eclipse Modeling Framework (EMF)
– De-facto standard for building MDE tools
• OCL, Xtext, ATL, Epsilon, EMF-IncQuery, Acceleo, Xpand
• XML Metadata Interchange (XMI)
– Enables model interoperability
– Supported na9vely by EMF and as an import/export
format by modeling tools
• e.g. Enterprise Architect, Modelio, MagicDraw, MicrosoW Visio, Visual
Paradigm

5. 5The Problem
• Model management
opera9ons (valida9on,
transforma9on, etc. )
typically use only a subset
of the elements of a model
• EMF’s XMI parser needs to
load the en9re model
anyway
– Wasteful (memory +
9me)

6. 6var lecturers = Lecturer.allOfKind();
for (l in lecturers) {
l.first_name.println();
l.last_name.println();
l.webPage.url.println();
l.modules.size().println();
}

7. 7Alterna$ves to XMI
• Binary model serialisa9on
– Supported na9vely by EMF
– Smaller files and faster
– S9ll requires full loading
• Database-backed model persistence
– NeoEMF, CDO, Morsa, MongoEMF
– Support dynamic model element loading/unloading
– Not widely supported by modelling tools (yet)

8. 8Contribu$ons
• A par9al XMI loading algorithm
– Skip irrelevant model elements
– Expected memory and performance benefits
• An implementa9on of the algorithm as an extension
to EMF's XMI parser
– To avoid reinven9ng the wheel
– To facilitate exploita9on by EMF-based model
management languages and tools

9. 9EMF's XMI Parser
• Event-based (SAX) parser
– startDocument, startElement, endElement etc.
• Keeps track of its posi9on in the model using a
stack of model elements (EObjects)
– On start element: the top of the object stack is
used to determine what EObject to create
– On end element: the top of the object stack is
removed

10. 10The University Metamodel

11. 11EMF's XMI Parser
Object Stack
Resource

12. 12EMF's XMI Parser
Object Stack
:University
Resource
:University

13. 13EMF's XMI Parser
:University
Object Stack
:University
Resource
:Department
:Department

14. 14EMF's XMI Parser
:University
Object Stack
:University
Resource
:Department
:Department :Lecturer
:Lecturer

15. 15EMF's XMI Parser
:University
Object Stack
:University
Resource
:Department
:Department :Lecturer
:Lecturer
:WebPage
:WebPage

16. 16EMF's XMI Parser
:University
Object Stack
:University
Resource
:Department
:Department :Lecturer
:Lecturer
:WebPage

17. 17EMF's XMI Parser
:University
Object Stack
:University
Resource
:Department
:Department :Lecturer
:Lecturer
:WebPage

18. 18EMF's XMI Parser
:University
Object Stack
:University
Resource
:Department
:Department
:Lecturer
:WebPage

19. 19EMF's XMI Parser
:University
Object Stack
:University
Resource
:Department
:Department :Student
:Lecturer
:WebPage :Student

20. 20EMF's XMI Parser
:University
Object Stack
:University
Resource
:Department
:Department
:Lecturer
:WebPage :Student

21. 21EMF's XMI Parser
:University
Object Stack
:University
Resource
:Department
:Department :Module
:Lecturer
:WebPage :Student
:Module

22. 22EMF's XMI Parser
:University
Object Stack
:University
Resource
:Department
:Department :Module
:Lecturer
:WebPage :Student
:Module
:WebPage
:WebPage

23. 23EMF's XMI Parser
:University
Object Stack
:University
Resource
:Department
:Department :Module
:Lecturer
:WebPage :Student
:Module
:WebPage

24. 24EMF's XMI Parser
:University
Object Stack
:University
Resource
:Department
:Department
:Lecturer
:WebPage :Student
:Module
:WebPage

25. 25EMF's XMI Parser
:University
Object Stack
:University
Resource
:Department
:Lecturer
:WebPage :Student
:Module
:WebPage

26. 26EMF's XMI Parser
Object Stack
:University
Resource
:Department
:Lecturer
:WebPage :Student
:Module
:WebPage

27. 27EMF's XMI Parser
Object Stack
:University
Resource
:Department
:Lecturer
:WebPage :Student
:Module
:WebPage

28. 28EMF's XMI Parser
• Every XMI element is processed
• All EObjects need to be created
• All aeribute/reference slots are populated

29. 29Par$al XMI Loading
• Effec9ve Metamodel (aka footprint)
– Extracted from model management programs
– … so that we know what to load from a model
• Par9al Loading Algorithm
– Extension of EMF’s XMI parsing algorithm
– Uses the effec9ve metamodel to
• Skip XMI elements
• Avoid crea9on of elements that are not needed
• Avoid popula9on of slots that are not needed

30. 30Effec$ve M2 Extrac$on
• Iden9fies types/features that are likely to be
accessed during the execu9on of a model
management program
– Extracts an "effec9ve metamodel"
• Prototype for Epsilon but applicable to any
sta9cally
analysable
language

31. 31Effec$ve M2 Extrac$on
Effec9ve Metamodel
Lecturer
var lecturers = Lecturer.allOfKind();
for (l in lecturers)
{
l.first_name.println();
l.last_name.println();
l.webPage.url.println();
l.modules.size().println();
}

32. 32Effec$ve M2 Extrac$on
Effec9ve Metamodel
Lecturer
var lecturers = Lecturer.allOfKind();
for (l in lecturers)
{
l.first_name.println();
l.last_name.println();
l.webPage.url.println();
l.modules.size().println();
}

33. 33Effec$ve M2 Extrac$on
Effec9ve Metamodel
Lecturer
var lecturers = Lecturer.allOfKind();
for (l in lecturers)
{
l.first_name.println();
l.last_name.println();
l.webPage.url.println();
l.modules.size().println();
}

34. 34Effec$ve M2 Extrac$on
Effec9ve Metamodel
Lecturer
var lecturers = Lecturer.allOfKind();
for (l in lecturers)
{
l.first_name.println();
l.last_name.println();
l.webPage.url.println();
l.modules.size().println();
}

35. 35Effec$ve M2 Extrac$on
Effec9ve Metamodel
Lecturer
var lecturers = Lecturer.allOfKind();
for (l in lecturers)
{
l.first_name.println();
l.last_name.println();
l.webPage.url.println();
l.modules.size().println();
}

36. 36Effec$ve M2 Extrac$on
Effec9ve Metamodel
Lecturer
var lecturers = Lecturer.allOfKind();
for (l in lecturers)
{
l.first_name.println();
l.last_name.println();
l.webPage.url.println();
l.modules.size().println();
}

37. 37Effec$ve M2 Extrac$on
Effec9ve Metamodel
Lecturer
first_name
var lecturers = Lecturer.allOfKind();
for (l in lecturers)
{
l.first_name.println();
l.last_name.println();
l.webPage.url.println();
l.modules.size().println();
}

38. 38Effec$ve M2 Extrac$on
Effec9ve Metamodel
Lecturer
first_name
var lecturers = Lecturer.allOfKind();
for (l in lecturers)
{
l.first_name.println();
l.last_name.println();
l.webPage.url.println();
l.modules.size().println();
}

39. 39Effec$ve M2 Extrac$on
Effec9ve Metamodel
Lecturer
first_name
var lecturers = Lecturer.allOfKind();
for (l in lecturers)
{
l.first_name.println();
l.last_name.println();
l.webPage.url.println();
l.modules.size().println();
}

40. 40Effec$ve M2 Extrac$on
Effec9ve Metamodel
Lecturer
first_name
last_name
var lecturers = Lecturer.allOfKind();
for (l in lecturers)
{
l.first_name.println();
l.last_name.println();
l.webPage.url.println();
l.modules.size().println();
}

41. 41Effec$ve M2 Extrac$on
Effec9ve Metamodel
Lecturer
first_name
last_name
var lecturers = Lecturer.allOfKind();
for (l in lecturers)
{
l.first_name.println();
l.last_name.println();
l.webPage.url.println();
l.modules.size().println();
}

42. 42Effec$ve M2 Extrac$on
Effec9ve Metamodel
Lecturer
first_name
last_name
var lecturers = Lecturer.allOfKind();
for (l in lecturers)
{
l.first_name.println();
l.last_name.println();
l.webPage.url.println();
l.modules.size().println();
}

43. 43Effec$ve M2 Extrac$on
Effec9ve Metamodel
Lecturer
first_name
last_name
webPage
var lecturers = Lecturer.allOfKind();
for (l in lecturers)
{
l.first_name.println();
l.last_name.println();
l.webPage.url.println();
l.modules.size().println();
}

44. 44Effec$ve M2 Extrac$on
Effec9ve Metamodel
Lecturer
first_name
last_name
webPage
WebPage
var lecturers = Lecturer.allOfKind();
for (l in lecturers)
{
l.first_name.println();
l.last_name.println();
l.webPage.url.println();
l.modules.size().println();
}

45. 45Effec$ve M2 Extrac$on
Effec9ve Metamodel
Lecturer
first_name
last_name
webPage
WebPage
url
var lecturers = Lecturer.allOfKind();
for (l in lecturers)
{
l.first_name.println();
l.last_name.println();
l.webPage.url.println();
l.modules.size().println();
}

46. 46Effec$ve M2 Extrac$on
Effec9ve Metamodel
Lecturer
first_name
last_name
webPage
WebPage
url
var lecturers = Lecturer.allOfKind();
for (l in lecturers)
{
l.first_name.println();
l.last_name.println();
l.webPage.url.println();
l.modules.size().println();
}

47. 47Effec$ve M2 Extrac$on
Effec9ve Metamodel
Lecturer
first_name
last_name
webPage
WebPage
url
var lecturers = Lecturer.allOfKind();
for (l in lecturers)
{
l.first_name.println();
l.last_name.println();
l.webPage.url.println();
l.modules.size().println();
}

48. 48Effec$ve M2 Extrac$on
Effec9ve Metamodel
Lecturer
first_name
last_name
webPage
modules
WebPage
url
var lecturers = Lecturer.allOfKind();
for (l in lecturers)
{
l.first_name.println();
l.last_name.println();
l.webPage.url.println();
l.modules.size().println();
}

49. 49Effec$ve M2 Extrac$on
Effec9ve Metamodel
Lecturer
first_name
last_name
webPage
modules
WebPage
url
Module
var lecturers = Lecturer.allOfKind();
for (l in lecturers)
{
l.first_name.println();
l.last_name.println();
l.webPage.url.println();
l.modules.size().println();
}

50. 50Effec$ve M2 Extrac$on
Effec9ve Metamodel
Lecturer
first_name
last_name
webPage
modules
WebPage
url
Module
var lecturers = Lecturer.allOfKind();
for (l in lecturers)
{
l.first_name.println();
l.last_name.println();
l.webPage.url.println();
l.modules.size().println();
}

51. 51Effec$ve M2 Extrac$on
Effec9ve Metamodel
Lecturer
first_name
last_name
webPage
modules
WebPage
url
Module
var lecturers = Lecturer.allOfKind();
for (l in lecturers)
{
l.first_name.println();
l.last_name.println();
l.webPage.url.println();
l.modules.size().println();
}

52. 52Effec$ve M2 Extrac$on

53. 53Effec$ve M2 Reconcilia$on
• Effec9ve metamodels extracted from model
management programs may be incomplete
– They require reconcilia9on

54. 54Effec$ve M2 Reconcilia$on

55. 55Par$al Loading Algorithm
• The en9re document is s9ll read but only XMI
elements of elements are processed
• Novelty: Placeholder Objects
– The object stack is essen9al to EMF's XMI loading
algorithms
– We create one placeholder object for each
irrelevant type and use in in the place of ignored
model elements

56. 56Reconciled Effec$ve M2

57. 57Par$al XMI Loading
Object Stack
Resource
Placeholders
:University
:Department
:Student

58. 58Par$al XMI Loading
:University
Object Stack
Resource
Placeholders
:University
:Department
:Student

59. 59Par$al XMI Loading
:University
Object Stack
Resource
Placeholders
:University
:Department
:Student
:Department

60. 60Par$al XMI Loading
:University
Object Stack
Resource
Placeholders
:University
:Department
:Student
:Department
:Lecturer

61. 61Par$al XMI Loading
:University
Object Stack
Resource
Placeholders
:University
:Department
:Student
:Department
:Lecturer :Lecturer

62. 62Par$al XMI Loading
:University
Object Stack
Resource
Placeholders
:University
:Department
:Student
:Department
:Lecturer :Lecturer
:WebPage :WebPage

63. 63Par$al XMI Loading
:University
Object Stack
Resource
Placeholders
:University
:Department
:Student
:Department
:Lecturer :Lecturer
:WebPage :WebPage

64. 64Par$al XMI Loading
:University
Object Stack
Resource
Placeholders
:University
:Department
:Student
:Department
:Lecturer :Lecturer
:WebPage

65. 65Par$al XMI Loading
:University
Object Stack
Resource
Placeholders
:University
:Department
:Student
:Department
:Lecturer
:WebPage

66. 66Par$al XMI Loading
:University
Object Stack
Resource
Placeholders
:University
:Department
:Student
:Department
:Lecturer
:WebPage
:Student

67. 67Par$al XMI Loading
:University
Object Stack
Resource
Placeholders
:University
:Department
:Student
:Department
:Lecturer
:WebPage
:Student

68. 68Par$al XMI Loading
:University
Object Stack
Resource
Placeholders
:University
:Department
:Student
:Department
:Lecturer
:WebPage

69. 69Par$al XMI Loading
:University
Object Stack
Resource
Placeholders
:University
:Department
:Student
:Department
:Lecturer
:WebPage
:Module
:Module

70. 70Par$al XMI Loading
:University
Object Stack
Resource
Placeholders
:University
:Department
:Student
:Department
:Lecturer
:WebPage
:Module
:Module
:WebPage

71. 71Par$al XMI Loading
:University
Object Stack
Resource
Placeholders
:University
:Department
:Student
:Department
:Lecturer
:WebPage
:Module
:Module

72. 72Par$al XMI Loading
:University
Object Stack
Resource
Placeholders
:University
:Department
:Student
:Department
:Lecturer
:WebPage
:Module

73. 73Par$al XMI Loading
:University
Object Stack
Resource
Placeholders
:University
:Department
:Student :Lecturer
:WebPage
:Module

74. 74Par$al XMI Loading
Object Stack
Resource
Placeholders
:University
:Department
:Student :Lecturer
:WebPage
:Module

75. 75Par$al XMI Loading
Object Stack
Resource
Placeholders
:University
:Department
:Student :Lecturer
:WebPage
:Module

76. 76Par$ally Loaded Model

77. 77Integra$on with EMF

78. 78
Evalua$on_

79. 79Benchmarks
• Models from GraBaTs 2009
• 5 data sets
– set0 – set4, obtained by reverse-engineering Java
projects
– Sizes: 9.2MB, 27.9MB, 283.2MB, 626.7MB and
676.9MB
• Benchmark query sets
– EOL queries automa9cally generated to access
20%, 40%, 60%, 80% and 100% of all data sets

80. 80Benchmark Results: Set 0

81. 81Benchmark Results: Set 1

82. 82Benchmark Results: Set 2

83. 83Benchmark Results: Set 3

84. 84Benchmark Results: Set 4

85. 85Observa$ons
• Linear behaviour with regard to the number of
model elements and slots of interest
– Loading 9me
– Memory footprint
• When loading 100% of the model, the par9al
loading algorithm is marginally slower

86. 86Limita$ons
• XMI models should use unique IDs rather than
fragment path IDs
– Such as //@departments.0/@modules.0
• Par9ally loaded models are read-only
– Changes cannot be saved back to the original
model

87. 87Conclusions
• First aeempt to par9ally load XMI models
• to save 9me and memory
• Algorithm implemented as an extension to
EMF's XMI parser
• Scales linearly with respect to the number of
model elements and slots of interest

88. 88Future Work
• Run9me model-level pruning
– Avoiding XML tags and its children if completely
not needed
• Propaga9ng changes back to the original
model
• Suppor9ng fragment path IDs
• Par9al loading of models serialised in EMF's
binary format