Contrˆole de version incertain dans l’´edition collaborative ouverte de documents arborescents

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Contrˆ ole de version incertain dans l’´ edition collaborative ouverte de documents arborescents

M. Lamine BA, Talel Abdessalem & Pierre Senellart

BDA’13 – 22-25 October 2013 (Nantes, France)

http://dbweb.enst.fr/

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Motivations Versioning on the Web is Uncertain

Versioning on the Web is Uncertain (I)

◮ Large-scale, open and collaborative editing platforms, e.g., wikipedia

◮ Unreliable contributors, Novice vs. Experts, etc.

◮ Malicious edits, Vandalism acts,Contradictions

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Versioning on the Web is Uncertain (II)

Version control is used in large-scale web collaborative editing platforms in order to integratecontributions from different sources and to support fixing errors with the possibility to query previousdata versions

◮ No notion of more relevant versions or contributions which will fit to user-preferences, but just the concept of last validrevisions

◮ Deterministicversion control models [Kerstin et al.(2009), Al Koc et al.(2011)] in the literature

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Versioning on the Web is Uncertain (III)

v0 (a0, c0) v1 (a1, c1) v2 (a2, c2) v4 (a1, c4)

v₃ (a₃, c₃) derivation derivation

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Versioning on the Web is Uncertain (III)

v0 (a0, c0) v1 (a1, c1) v2 (a2, c2) v4 (a1, c4)

Q1:v2 |¬a1

Q₂:v₂ |¬c₁

Q₃:all v_i|Pr(v_i)6=0

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Versioning on the Web is Uncertain (III)

v0 (a0, c0) v1 (a1, c1) v2 (a2, c2) v4 (a1, c4)

Q1:v2 |¬a1

Q₂:v₂ |¬c₁

Q₃:all v_i|Pr(v_i)6=0

☛ Uncertain version control in Open Collaborative Contexts

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Versioning on the Web is Uncertain (IV)

d2) Person

Name

“Obama”

Origin

“Tanzania”

d4) Person

Name

“Obama

Origin

“Tanzania”

Function

“US. President”

d₁) Person

Name

“Obama”

d3) Person

Name

“B. Obama”

Origin

“Kenya”

e₂

e₃

e₄

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Versioning on the Web is Uncertain (IV)

d2) Person

Name

“Obama”

Origin

“Tanzania”

d4) Person

Name

“Obama

Origin

“Tanzania”

Function

“US. President”

d1) Person

Name

“Obama”

d3) Person

Name

“B. Obama”

Origin

“Kenya”

d5) Person

Name

“B. Obama”

Origin

“Kenya”

Function

“US. President”

F={e1,e₃,e₄}

e₂

e₃

e₄

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Versioning on the Web is Uncertain (IV)

d2) Person

Name

“Obama”

Origin

“Tanzania”

d4) Person

Name

“Obama

Origin

“Tanzania”

Function

“US. President”

d1) Person

Name

“Obama”

d3) Person

Name

“B. Obama”

Origin

“Kenya”

d5) Person

Name

“B. Obama”

Origin

“Kenya”

Function

“US. President”

F={e1,e₃,e₄}

e₂

e₃

e₄

c

P) Person

Name

e₁

“Obama”

¬e3

“B. Obama”

e₃

Origin e₂∨e3

“Tanzania”

¬e3

“Kenya”

e₃

Function e₄

“US. President”

Mapping Probabilistic Encoding

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Uncertain Tree-Structured Data Model

Plan

Uncertain Tree-Structured Data Model Uncertain Multi-Version XML Document Conclusion and Further work

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Uncertain Tree-Structured Data

Probabilistic XML [Kimelfeld & Senellart.(2013)]

c P) r

p₁ e₁∨e₂

t₁ p₂

¬e₂

t₂

d₁) r

p₁

t₁ p₂

t₂ v₁= (e₁∧ ¬e₂)

d₂) r

p₁

t₁ v₂= (¬e₁∧e₂) v^′

2= (e₁∧e₂)

d₃) r

p₂

t2

v₃= (¬e₁∧ ¬e₂)

Pr(e₁) = 0.2; Pr(e₂) = 0.8 Pr(d₁) = Pr(e₁)×Pr(¬e₂)

Pr(d₂) = (Pr(¬e₁)×Pr(e₂)) + (Pr(e₁)×Pr(e₂)) Pr(d₃) = Pr(¬e₁)×Pr(¬e₂)

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Uncertain Tree-Structured Data

c P) r

p₁ e₁∨e₂

t₁ p₂

¬e₂

t₂

d₁) r

p₁

t₁ p₂

t₂ v₁= (e₁∧ ¬e₂)

d₂) r

p₁

t₁ v₂= (¬e₁∧e₂) v^′

2= (e₁∧e₂)

d₃) r

p₂

t2

v₃= (¬e₁∧ ¬e₂)

Pr(e₁) = 0.2; Pr(e₂) = 0.8 Pr(d₁) = 0.04

Pr(d₂) = 0.80 Pr(d₃) = 0.16

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Uncertain Tree-Structured Data

c P) r

p₁ e₁∨e₂

t₁ p₂

¬e₂

t₂

d₁) r

p₁

t₁ p₂

t₂ v₁= (e₁∧ ¬e₂)

d₂) r

p₁

t₁ v₂= (¬e₁∧e₂) v^′

2= (e₁∧e₂)

d₃) r

p₂

t2

v₃= (¬e₁∧ ¬e₂)

➤ Pc=<T,C(E),fie,Pr>

➤ [[Pc]] =<D,Pr>; Σ{Pr(d) |d ∈D}= 1

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Uncertain Multi-Version XML Document

Plan

Uncertain Tree-Structured Data Model Uncertain Multi-Version XML Document

Uncertain Version Control Model Probabilistic XML Encoding

Updating Uncertain Multi-version XML documents Performance Analysis

Conclusion and Further work

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Uncertain Multi-Version XML Document Uncertain Version Control Model

Uncertain Multi-Version XML Document

Uncertain Version Control Model

◮ Probability space (PSV) over Uncertain versions of XML documents

◮ Randomderivation graph (DG) over the document versions produced Intuition: states in DG are complex variablese_i’s calledversion control events based on simpler variables b₁. . .b_m managing uncertainty in data

<G,Ω> defines a multi-version XML document with uncertain data

◮ G is DG over a set of versioning eventsV ∪e₀ withV ={e₁. . .e_n}

◮ Ω : 2^V^\{e⁰^}→D a mapping computing the PSV according to sets of valid events

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Uncertain Multi-Version XML Document Uncertain Version Control Model

Uncertain Multi-Version XML Document

Possible versions and Probabilities

Possible versions

◮ Version control events come with edit scripts updating content

◮ ∀i,∀F⊆2^V^\{eⁱ^}, the possible version Ω({e_i} ∪F) = [Ω(F)]^∆ⁱ Probability of possible versions

◮ Assume a prior probability distribution over simple variables b₁. . .b_m

◮ The probability of a given possible version Ω(F) is the probability of W

F⊆V,Ω(F)F

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Uncertain Multi-Version XML Document Probabilistic XML Encoding

Uncertain Multi-Version XML Document

Probabilistic XML Encoding

◮ Compact representation of all possible versions (PSV) in Ω mapping Intuition: Represent PSV usingpropositional formulasof simple variables

b₁. . .b_m attached to nodes in a global treeT containing all provided data

A probabilistic XML encoding of <G,Ω>is a couple <G,Pc>with

◮ Pc=<T,C(V),fie,Pr>is a probabilistic XML document

Thm1: JPcKdefines the same probability distribution overD as Ω, i.e.,

<G,JPcK>=<G,Ω>

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Uncertain Multi-Version XML Document Updating Uncertain Multi-version XML documents

Uncertain Multi-Version XML Document

Updating Uncertain Versions (I)

◮ Uncertaineditions in ∆ over nodes of a possible tree version

An update is an uncertain version control event defined based on a triple

<e_i,e_j,∆> (e_i ∈G ande_j 6∈G) updOP(<e_i,e_j, ∆>)[<G,Ω>]

− G :=G ∪({e_j}, {(e_i, e_j)})

− Extension of Ω to a Ω^′ mapping with for each F ∈2⁽^V^\{e⁰^})∪{e^j^} Ω^′(F) = [Ω(F\ {e_j})]^∆ ife_j ∈F and Ω^′(F) = Ω(F) otherwise

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Uncertain Multi-Version XML Document Updating Uncertain Multi-version XML documents

Uncertain Multi-Version XML Document

Updating Uncertain Versions (II)

updPrXML(<e_i,e_j,∆>)[<Pc,Ω>]

− G :=G ∪({e_j}, {(e_i, e_j)})

− For all ins(x, i)in ∆

◮ Set(x,fie(x)∨(e_j))ifx already inPc

◮ Insertx inPcandSet(x,(e_j))otherwise

− For all del(x)in ∆

◮ Set(x,fie(x)∧ ¬(e_j))

Thm2: updOP(<e_i,e_j,∆>)≡updPrXML(<e_i,e_j,∆>) Thm3: updPrXMLruns inO(1) whilePcgrows linearly according to |∆|

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Uncertain Multi-Version XML Document Performance Analysis

Uncertain Multi-version XML documents

Performance Analysis (Metrics, datasets and baseline)

◮ Estimation of the commit time and checkout cost of the model

Baseline Systems

☞Versioning tools SubVersion and Git

− Use of their Java implementations based on the APIs SvnKit and JGit

Real Datasets

History of commits over two large file systems (shared tree-structured data)

☞ Linux kernel development

☞ Cassandra project

◮ Implementation of our system (PrXML) in Java

◮ Measures are obtained with all accesses in RAM Disk

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Evaluation of the model

Performance Analysis (Commit time)

0 50 100 150 200 250 300 10¹

10² 10³ 10⁴

Commit (Linux kernel)

Committime(ms)

Subversion Git PrXML

0 200 400 600

10¹ 10² 10³ 10⁴

Commit (Cassandra project)

Committime(ms)

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Evaluation of the model

Performance Analysis (Checkout time)

0 50 100 150 200 250 300 100

200 300 400

Revision (Linux kernel)

Checkouttime(ms)

0 200 400 600

100 200 300 400

Revision (Cassandra project)

Checkouttime(ms)

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Plan

Uncertain Tree-Structured Data Model Uncertain Multi-Version XML Document Conclusion and Further work

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Conclusion and Further work (i)

◮ Design of a probabilistic version control approach for uncertain tree-structured documents

◮ Both logical description and an efficient probabilistic compact XML encoding

◮ Set-up of the most used version control operation, i.e., update and with an efficient mapping algorithms

◮ Both theoretical and practical complexity analysis of the proposed model

◮ Extension of our model in [Ba et al.(DChanges, 2013)] with the merging operationover uncertain versions

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Conclusion and Further work (ii)

◮ Support of more complex versioning operations such as copying, renaming etc.

◮ Study the impact of introducing some constraints over the order of nodes in uncertain version control

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Merci!

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References

Kerstin Altmanninger, Martina Seidl, and Manuel Wimmer,A survey on model versioning approaches, IJWIS5(2009).

M. Lamine Ba, Talel Abdessalem, and Pierre Senellart,Towards a version control model with uncertain data, PIKM, 2011.

,Merging uncertain multi-version XML documents, Proc. DChanges (Florence, Italy), sep 2013.

,Uncertain version control in open collaborative editing of tree-structured documents, Proc. DocEng (Florence, Italy), sep 2013.

Evgeny Kharlamov, Werner Nutt, and Pierre Senellart,Updating Probabilistic XML, Updates in XML, 2010.

Benny Kimelfeld and Pierre Senellart,Probabilistic XML: Models and complexity, Advances in Probabilistic Databases for Uncertain Information Management (Zongmin Ma and Li Yan, eds.), Springer-Verlag, 2013.

Al Koc and Abdullah Uz Tansel,A survey of version control systems, ICEME, 2011.