Linear-Time Verification of Data-Aware Processes Modulo Theories via Covers and Automata
Authors: Alessandro Gianola, Marco Montali, Sarah Winkler
AAAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Finally, we present an implementation and an experimental evaluation over a benchmark of real-world dataaware business processes. |
| Researcher Affiliation | Academia | 1INESC-ID/Instituto Superior T ecnico, Universidade de Lisboa, Lisbon, Portugal 2Faculty of Engineering, Free University of Bozen-Bolzano, Bolzano, Italy |
| Pseudocode | No | The paper describes algorithms and procedures textually but does not include any clearly labeled pseudocode or algorithm blocks. |
| Open Source Code | Yes | LINDMT is a command-line tool written in Python, but it is also accessible via a web interface (https://lindmt.unibz.it); sources and benchmarks are available as well. |
| Open Datasets | Yes | We curated a benchmark set using data-aware business processes from the literature, especially the VERIFAS problem set (Li, Deutsch, and Vianu 2017). |
| Dataset Splits | No | The paper mentions checking properties on a benchmark set but does not provide specific details on how data was split for training, validation, or testing. |
| Hardware Specification | No | The paper does not provide specific details about the hardware used for running experiments. |
| Software Dependencies | No | The tool interfaces CVC5 (Deters et al. 2014) for SMT checks, and QE in LIRA. ... LINDMT is a command-line tool written in Python... The paper mentions software used (CVC5, Python) but does not provide specific version numbers for these dependencies. |
| Experiment Setup | No | The paper mentions 'In the input files for Σ-DMTs, control states (like o1, o2 in Ex. 3) are supported for efficiency,' but it does not provide detailed experimental setup information such as specific hyperparameter values or comprehensive training configurations. |