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Event-Based Analysis of Timed Rebeca Models using SQL

Published: 20 October 2014 Publication History

Abstract

In this paper, we present a simulation-based approach for analysis of Timed Rebeca models to tackle the state space explosion problem. We present a simulation toolkit, TRSim, which uses McErlang as a back-end simulator and stores the occurrences of events while executing the model in a relational database. We also present TeProp, a timed event-based property language, which is designed to be easy-to-use for specifying and reasoning about timed occurrences of events in an actor system. One can check TeProp formulas against multiple simulation runs by transforming the formulas to SQL queries and executing the queries over the event database. Using this approach, the correctness of large models can be analyzed to a bounded degree of confidence. To illustrate the applicability of TRSim toolkit and TeProp we provide a number of case studies.

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cover image ACM Conferences
AGERE! '14: Proceedings of the 4th International Workshop on Programming based on Actors Agents & Decentralized Control
October 2014
146 pages
ISBN:9781450321891
DOI:10.1145/2687357
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 20 October 2014

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Author Tags

  1. action based property
  2. actor model
  3. database
  4. realtime systems
  5. simulation
  6. teprop
  7. timed-rebeca
  8. verification

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SPLASH '14
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AGERE! '14 Paper Acceptance Rate 9 of 14 submissions, 64%;
Overall Acceptance Rate 19 of 35 submissions, 54%

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