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A Quantitative Partial Model-Checking Function and Its Optimisation

19 pagesPublished: May 4, 2017

Abstract

Partial Model-Checking (PMC) is an efficient tool to reduce the combinatorial explosion of a state-space, arising in the verification of loosely-coupled software systems. At the same time, it is useful to consider quantitative temporal-modalities. This allows for checking whether satisfying such a desired modality is too costly, by comparing the final score consisting of how much the system spends to satisfy the policy, to a given threshold. We stir these two ingredients together in order to provide a Quantitative PMC function (QPMC), based on the algebraic structure of semirings. We design a method to extract part of the weight during QPMC, with the purpose to avoid the evaluation of a modality as soon as the threshold is crossed. Moreover, we extend classical heuristics to be quantitative, and we investigate the complexity of QPMC.
Keyword: Partial Model Checking, Semirings, Optimisation, Quantitative Modal Logic Quantitative Process Algebra, Quantitative Evaluation of Systems.

Keyphrases: partial model checking, quantitative reasoning, semiring

In: Thomas Eiter and David Sands (editors). LPAR-21. 21st International Conference on Logic for Programming, Artificial Intelligence and Reasoning, vol 46, pages 319-337.

BibTeX entry
@inproceedings{LPAR-21:Quantitative_Partial_Model_Checking,
  author    = {Stefano Bistarelli and Fabio Martinelli and Ilaria Matteucci and Francesco Santini},
  title     = {A Quantitative Partial Model-Checking Function and Its Optimisation},
  booktitle = {LPAR-21. 21st International Conference on Logic for Programming, Artificial Intelligence and Reasoning},
  editor    = {Thomas Eiter and David Sands},
  series    = {EPiC Series in Computing},
  volume    = {46},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/n7j},
  doi       = {10.29007/rb2p},
  pages     = {319-337},
  year      = {2017}}
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