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What happens in case of complex data types??

Service Similarity

Based on URBE (UDDI Registry By Example)

  • performs content based query
  • user submits a WSDL expressing the requirements
  • URBE returns a list of Web services close to the request

Similarity function fSim is the core of URBE

  • semantic analysis
  • structural analysis

Motivation

For more info: P. Plebani, B. Pernici, "URBE: Web service Retrieval based on Similarity Evaluation", IEEE Transaction on Knowledge and Data Engineering, 21(11): 1629-1642 (2009)

Code available at SourceForge: http://sourceforge.net/projects/urbe/

Thousands of Web services are out there:

  • Seekda indexed 30'000 entries
  • More than 3'000 registered API on www.programmableweb.com

To improve the reuse of service, Service Discovery (a.k.a. Service Retrieval) becomes a critical step

Semantic analysis

fSim

Structural analysis

  • We assume that the WSDL is automatically generated
  • Names reflect coding conventions
  • Stemming and tokenization are required before comparing names

State of the art

What we propose

Service Compatibility

Merging

  • Service similarity
  • Service compatibility

Thus, we can find a service

  • achieving a given goal
  • exposing a compatible interface

Two dimensions:

  • horizontal compatibility (interoperability)
  • vertical compatibility (replaceability)

Two types:

  • backward compatibility (in case of new consumer)
  • forward compatibility (in case of new producer)

Retrieving Compatible Web services

For more info: V. Andrikopoulos, S. Benbernou, and M.P. Papazoglou, "On the evolution of services", IEEE Transactions on Software Engineering (to appear), 2011.

Vasilios Andrikopoulos

Tilburg University, The Netherlands

<V.Andrikopoulos@uvt.nl>

Pierluigi Plebani

Politecnico di Milano, Italy

<plebani@elet.polimi.it>

T-Shaped changes 1/2

T-Shaped changes 2/2

Type of service compatibility

Example of subtyping

  • Set of changes applied to a service S that results in a service S' fully compatible with S
  • Based on type theory
  • May require some adapter generation
  • Add (optional) message data types, add (new) opera- tion & add (new) port type
  • Remove one-way (only) operations
  • Add (obligatory or optional) data types to output messages
  • Remove (obligatory or optional) data types from input messages
  • Add output message parts to operations
  • Remove input message parts from operations

Merging similarity and compatibility

Future work

Questions?

Retrieving Compatible Web services

Vasilios Andrikopoulos

Tilburg University, The Netherlands

<V.Andrikopoulos@uvt.nl>

Pierluigi Plebani

Politecnico di Milano, Italy

<plebani@elet.polimi.it>

  • Compatibility relies on a binary (on/off) approach
  • Similarity has a more fuzzy-oriented evaluation
  • Considering the Semantic Annotation to improve the precision-recall
  • Exploiting the distance analysis to generate mediators

parSim, by means of dataSim, will be influenced by the compatibility analysis

Modifying parSim

Fuzzy vs. binary

dtSim

dtSim'

  • Cutting variant
  • Sigmoid variant

dtSim

dtSim'

Assignment in bipartite graph

Validation

Benchmark: SAWSDL-TC3

  • 1080 WSDL
  • 42 queries

Machine:

  • Mac OS X 10.6
  • Intel Core 2 Duo 2.33 Ghz
  • 8 Gbyte RAM

Precision Recall chart

Response Time

Average Precision and Top-X

AP

Sigmoid-variant: +1.6%

Cutting-variant: +5.5%

Average query response time

  • Baseline: 53.26 s
  • Sigmoid-variant: 35.29 s (-33.7%)
  • Cutting-variant: 31.80 s (-40.3 %)

Top-5

Sigmoid-variant: +0.6%

Cutting-variant: +3.7%

Top-10

Sigmoid-variant: +0.2%

Cutting-variant: +2.4%

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