Overall Objectives
Application Domains
New Software and Platforms
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
Bibliography
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## Section: New Results

### Timed, Probabilistic, and Stochastic Extensions

#### Tools for Probabilistic and Stochastic Systems

Participants : Hubert Garavel, Jean-Philippe Gros, Frédéric Lang, Julie Parreaux, Wendelin Serwe.

The CADP toolbox already implements some of these probabilistic/stochastic models, namely DTMCs and CTMCs (Discrete-Time and Continuous-Time Markov Chains), and IMCs (Interactive Markov Chains) [41]. Our long-term goal is to increase the capability and flexibility of the CADP tools, so as to support other quantitative models more easily.

In 2017, we undertook a systematic review of the existing theoretical models and built a comprehensive list of more than 70 software tools implementing these models [37]. The results of this study have been made widely available as a Web catalog (http://cadp.inria.fr/resources/zoo).

In parallel, we also undertook a systematic review [50] of the benchmarks made available for these tools. We downloaded more than $21\phantom{\rule{0.166667em}{0ex}}000$ files from the web and developed triage scripts to analyze these files and classify them automatically, separating various kinds of automata-based models (e.g., Markov chains, Markov automata, hybrid automata, etc.) from temporal-logic formulas. One finding of this “big data” study is the present lack of diversity, as four tools (PRISM, MRMC, STORM, and SiSAT) provide nearly $60%$ of the models.

To address this issue, we started investigating the probabilistic and stochastic models of complex industrial systems produced by former PhD students of the VASY and CONVECS teams. We analyzed these models (written in BCG, EXP, LOTOS, LNT, SVL, and/or Makefiles) to separate functional aspects from performance ones, leading to a collection of DTMCs, CTMCs, IMCs, and IPCs (Interactive Probabilistic Chains). We updated these models to ensure compatibility with the latest versions of CADP and C compilers, and we started enhancing EXP.OPEN with new features that simplify the parallel composition of IPCs (see § 6.4.1).