When does abstraction help?

Guy Avni*, Orna Kupferman

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Abstraction is a leading technique for coping with large state spaces. Abstraction over-approximates the transitions of the original system or the automaton that models it and may introduce nondeterminism. In applications where determinism is essential, we say that an abstraction function is helpful if, after determining and minimizing the abstract automaton, we end up with fewer states than the original automaton. We show that abstraction functions are not always helpful; in fact, they may introduce an exponential blow-up. We study the problem of deciding whether a given abstraction function is helpful for a given deterministic automaton and show that it is PSPACE-complete.

Original languageEnglish
Pages (from-to)901-905
Number of pages5
JournalInformation Processing Letters
Volume113
Issue number22-24
DOIs
StatePublished - 2013

Keywords

  • Abstraction
  • Deterministic finite automata
  • Formal methods

Fingerprint

Dive into the research topics of 'When does abstraction help?'. Together they form a unique fingerprint.

Cite this