# Monotone Precision and Recall Measures for Comparing Executions and Specifications of Dynamic Systems

## TL;DR

This paper introduces a new framework for behavioral measures that ensure monotonicity and handle infinite behaviors, improving the comparison of system executions and specifications.

## Contribution

It proposes a novel framework for behavioral quotients that guarantee essential properties like monotonicity, addressing limitations of existing measures.

## Key findings

- New behavioral quotients satisfy monotonicity and handle infinite behaviors
- Application of quotients effectively measures precision and recall between executions and specifications
- Prototype implementation demonstrates improved assessment consistency

## Abstract

The behavioural comparison of systems is an important concern of software engineering research. For example, the areas of specification discovery and specification mining are concerned with measuring the consistency between a collection of execution traces and a program specification. This problem is also tackled in process mining with the help of measures that describe the quality of a process specification automatically discovered from execution logs. Though various measures have been proposed, it was recently demonstrated that they neither fulfil essential properties, such as monotonicity, nor can they handle infinite behaviour. In this paper, we address this research problem by introducing a new framework for the definition of behavioural quotients. We proof that corresponding quotients guarantee desired properties that existing measures have failed to support. We demonstrate the application of the quotients for capturing precision and recall measures between a collection of recorded executions and a system specification. We use a prototypical implementation of these measures to contrast their monotonic assessment with measures that have been defined in prior research.