Asynchronous Learning for Service Composition

  • Casandra Holotescu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7221)

Abstract

Correctness of system compositions is automatically ensured by using formal behavioural models of services. However, such models are not always provided. We present a model inference technique for black-box asynchronous services, that interleaves behavioural exploration and incremental model refinement. To save learning effort, only behaviour relevant to the desired system specification is explored. Compared to existing inference techniques that assume only controllable behaviour, our method addresses also uncontrollable events. Experimental results show that obtained models can be successfully used for a safe composition.

Keywords

Service Composition Automaton Learn Uncontrollable Event Equivalence Query Error Trace 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Casandra Holotescu
    • 1
  1. 1.Dept. of Computer and Software EngineeringPolitehnica University of TimişoaraRomania

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