CITATION.cff

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cff-version: 1.2.0
title: >-
  Rust Process Mining Library with
  Python/Java Bindings
message: 'If you use this software, please cite it as below.'
type: software
authors:
  - family-names: Küsters
    given-names: Aaron
    orcid: 'https://orcid.org/0009-0006-9195-5380'
repository-code: 'https://github.com/aarkue/rust-bridge-process-mining/'
url: 'https://crates.io/crates/process_mining'
license: MIT
version: 2.0.4
date-released: '2023-12-13'
doi: 10.48550/arXiv.2401.14149
preferred-citation:
  type: generic
  authors:
    - family-names: 'Küsters'
      given-names: 'Aaron'
    - family-names: 'van der Aalst'
      given-names: 'Willibrordus Martinus Pancratius'
  doi: '10.48550/arXiv.2401.14149'
  title: 'Developing a High-Performance Process Mining Library with Java and Python Bindings in Rust'
  year: 2024
  abstract: >-
    The most commonly used open-source process mining software
    tools today are ProM and PM4Py, written in Java and
    Python, respectively. Such high-level, often interpreted,
    programming languages trade off performance with memory
    safety and ease-of-use. In contrast, traditional compiled
    languages, like C or C++, can achieve top performance but
    often suffer from instability related to unsafe memory
    management. Lately, Rust emerged as a highly performant,
    compiled programming language with inherent memory safety.
    In this paper, we describe our approach to developing a
    shared process mining library in Rust with bindings to
    both Java and Python, allowing full integration into the
    existing ecosystems, like ProM and PM4Py. By facilitating
    interoperability, our methodology enables researchers or
    industry to develop novel algorithms in Rust once and make
    them accessible to the entire community while also
    achieving superior performance.