Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 134 tok/s
Gemini 2.5 Pro 41 tok/s Pro
GPT-5 Medium 31 tok/s Pro
GPT-5 High 27 tok/s Pro
GPT-4o 73 tok/s Pro
Kimi K2 199 tok/s Pro
GPT OSS 120B 434 tok/s Pro
Claude Sonnet 4.5 37 tok/s Pro
2000 character limit reached

Bounded Model Checking of an MITL Fragment for Timed Automata (1304.7209v1)

Published 26 Apr 2013 in cs.LO

Abstract: Timed automata (TAs) are a common formalism for modeling timed systems. Bounded model checking (BMC) is a verification method that searches for runs violating a property using a SAT or SMT solver. MITL is a real-time extension of the linear time logic LTL. Originally, MITL was defined for traces of non-overlapping time intervals rather than the "super-dense" time traces allowing for intervals overlapping in single points that are employed by the nowadays common semantics of timed automata. In this paper we extend the semantics of a fragment of MITL to super-dense time traces and devise a bounded model checking encoding for the fragment. We prove correctness and completeness in the sense that using a sufficiently large bound a counter-example to any given non-holding property can be found. We have implemented the proposed bounded model checking approach and experimentally studied the efficiency and scalability of the implementation.

Citations (12)

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.