Synthesis of trigger properties

Orna Kupferman*, Moshe Y. Vardi

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations


In automated synthesis, we transform a specification into a system that is guaranteed to satisfy the specification. In spite of the rich theory developed for temporal synthesis, little of this theory has been reduced to practice. This is in contrast with model-checking theory, which has led to industrial development and use of formal verification tools. We address this problem here by considering a certain class of PSL properties; this class covers most of the properties used in practice by system designers. We refer to this class as the class of trigger properties. We show that the synthesis problem for trigger properties is more amenable to implementation than that of general PSL properties. While the problem is still 2EXPTIME-complete, it can be solved using techniques that are significantly simpler than the techniques used in general temporal synthesis. Not only can we avoid the use of Safra's determinization, but we can also avoid the use of progress ranks. Rather, the techniques used are based on classical subset constructions. This makes our approach amenable also to symbolic implementation, as well as an incremental implementation, in which the specification evolves over time.

Original languageAmerican English
Title of host publicationLogic for Programming, Artificial Intelligence, and Reasoning - 16th International Conference, LPAR-16, Revised Selected Papers
Number of pages20
StatePublished - 2010
Event16th International Conference on Logic for Programming, Artificial Intelligence, and Reasoning, LPAR-16 - Dakar, Senegal
Duration: 25 Apr 20101 May 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6355 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference16th International Conference on Logic for Programming, Artificial Intelligence, and Reasoning, LPAR-16

Bibliographical note

Funding Information:
Work supported in part by NSF grant CCF-0728882, by BSF grant 9800096, and by gift from Intel. Part of this work was done while the second author was on sabbatical at the Hebrew University of Jerusalem.


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