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Measuring the Gap: Algorithmic Approximation Bounds for the Space Complexity of Stream Specifications

15 pagesPublished: March 26, 2017

Abstract

In previous work we presented an algorithmic procedure for analysing the space complexity of monitor specifications written in a fragment of predicate logic. These monitor specifications were developed for runtime monitoring of event streams. Our procedure provides accurate results for a large fragment of the possible specifications, but overestimates the space complexity of precisely those specifications which are more likely to be found in real world applications. Experiments hinted at a relationship between the extent our procedure over-approximates the space requirements of a specification and the quantifier structure of the specification. In this paper we provide a formalization of this relationship as approximation ratios, and are able to pinpoint ``good'' constructions, that is specifications using less memory. These results are first steps towards categorizing specifications based on memory efficiency.

Keyphrases: approximation, predicate logic, runtime verification, space complexity, stream monitoring

In: Mohamed Mosbah and Michael Rusinowitch (editors). SCSS 2017. The 8th International Symposium on Symbolic Computation in Software Science 2017, vol 45, pages 1-15.

BibTeX entry
@inproceedings{SCSS2017:Measuring_Gap_Algorithmic_Approximation,
  author    = {David Cerna and Wolfgang Schreiner},
  title     = {Measuring the Gap: Algorithmic Approximation Bounds for the Space Complexity of Stream Specifications},
  booktitle = {SCSS 2017. The 8th International Symposium on Symbolic Computation in Software Science 2017},
  editor    = {Mohamed Mosbah and Michael Rusinowitch},
  series    = {EPiC Series in Computing},
  volume    = {45},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/Cvp},
  doi       = {10.29007/t3jg},
  pages     = {1-15},
  year      = {2017}}
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