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Annual Conference on Artificial Intelligence

KI 2012: KI 2012: Advances in Artificial Intelligence pp 13–24Cite as

Formal Semantics of Model Fields in Annotation-Based Specifications

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 7526)

Abstract

It is widely recognized that abstraction and modularization are indispensable for specification of real-world programs. In source-code level program specification and verification, model fields are a common means for those goals. However, it remains a challenge to provide a well-founded formal semantics for the general case in which the abstraction relation defining a model field is non-functional.

In this paper, we discuss and compare several possibilities for defining model field semantics, and we give a complete formal semantics for the general case. Our analysis and the proposed semantics is based on a generalization of Hilbert’s ε terms.

Keywords

  • Model Field
  • Choice Function
  • Formal Semantic
  • Valuation Function
  • Frame Condition

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.

This work was supported by the German National Science Foundation (DFG) under project “Program-level Specification and Deductive Verification of Security Properties” within priority programme 1496 “Reliably Secure Software Systems – RS3”.

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Author information

Authors and Affiliations

  1. Department of Informatics, Karlsruhe Institute of Technology (KIT), Germany

    Bernhard Beckert & Daniel Bruns

Authors
  1. Bernhard Beckert
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  2. Daniel Bruns
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Editor information

Editors and Affiliations

  1. Institute of Artificial Intelligence, University of Ulm, 89069, Ulm, Germany

    Birte Glimm

  2. Saarland University and German Research Center for Artificial Intelligence (DFKI), Stuhlsatzenhausweg 3, 66123, Saarbrücken, Germany

    Antonio Krüger

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Beckert, B., Bruns, D. (2012). Formal Semantics of Model Fields in Annotation-Based Specifications. In: Glimm, B., Krüger, A. (eds) KI 2012: Advances in Artificial Intelligence. KI 2012. Lecture Notes in Computer Science(), vol 7526. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33347-7_2

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  • DOI: https://doi.org/10.1007/978-3-642-33347-7_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33346-0

  • Online ISBN: 978-3-642-33347-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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