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The most commonly used open-source process mining software tools today areProM and PM4Py, written in Java and Python, respectively. Such high-level,often interpreted, programming languages trade off performance with memorysafety and ease-of-use. In contrast, traditional compiled languages, like C orC++, can achieve top performance but often suffer from instability related tounsafe memory management. Lately, Rust emerged as a highly performant, compiledprogramming language with inherent memory safety. In this paper, we describeour approach to developing a shared process mining library in Rust withbindings to both Java and Python, allowing full integration into the existingecosystems, like ProM and PM4Py. By facilitating interoperability, ourmethodology enables researchers or industry to develop novel algorithms in Rustonce and make them accessible to the entire community while also achievingsuperior performance.

Developing a High-Performance Process Mining Library with Java and Python Bindings in Rust