Analysis of timed and stochastic Petri nets


Release 2.3.8 (ask for support).

Unzip and launch run.sh (Linux/macOS) or run.bat (Windows).

Java 17 is recommended (Java >= 11 is supported): get the installer for Windows, run brew install --cask temurin on macOS, or apt-get install openjdk-17-jre on Linux.

The Sirio library is now available! The library implements the symbolic calculus and analysis methods of ORIS. STPN models can be exported from the GUI editor as "Java code" and analyzed in Sirio to conduct parametric studies.

To get started with ORIS and Stochastic Time Petri Nets (STPNs), check our tool paper or the tutorial.


ORIS Tool screenshot
  • Graphical Petri net editor
    Petri nets can be edited graphically, associating transitions with earliest and latest time to fire (time Petri nets), or with a deterministic or expolynomial probability density function with finite or infinite support (stochastic time Petri nets). The editor includes features such as undo, cut-and-paste, zoom, magnetic grid, alignment and even spacing of elements, SVG export, sticky notes.
  • Non-deterministic analysis of time Petri nets
    The state class graph of time Petri nets can be computed and visualized graphically. For stochastic time Petri nets, the state class graph can highlight regeneration points and exclude firings with null probability.
  • Transient analysis of non-Markovian stochastic Petri nets
    Transient state probabilities of stochastic time Petri nets can be computed through the forward enumeration of stochastic state classes (distributions of time-to-fires after each firing) within a time-bound. Regenerative analysis combines the enumeration of stochastic state classes up to regeneration points with integral equation systems, in order to exploit the repetitive structure of the underlying stochastic process.

Check our video presentations at ICSE'20 and TOSME'21.

A previous release of ORIS, with support for the analysis of non-deterministic preemptive models, can be found at stlab.dinfo.unifi.it/oris1.0.

Citing ORIS

To cite ORIS, please use the most recent tool paper:

M. Paolieri, M. Biagi, L. Carnevali, and E. Vicario.
The ORIS Tool: Quantitative Evaluation of Non-Markovian Systems.
IEEE Trans. Software Eng. 47(6): 1211-1225 (2021)
  author    = {Marco Paolieri and
               Marco Biagi and
               Laura Carnevali and
               Enrico Vicario},
  title     = {{The {ORIS} Tool: Quantitative Evaluation of Non-Markovian Systems}},
  journal   = {{IEEE} Trans. Software Eng.},
  volume    = {47},
  number    = {6},
  pages     = {1211--1225},
  year      = {2021},
  doi       = {10.1109/TSE.2019.2917202}