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

Artem Polyvyanyy, Andreas Solti, Matthias Weidlich, Claudio Di Ciccio, Jan Mendling

Research output: Contribution to journalArticleAcademicpeer-review

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 article, we address this research problem by introducing a new framework for the definition of behavioural quotients. We prove 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.
Original languageEnglish
Article number17
Number of pages41
JournalACM Transactions on Software Engineering and Methodology
Volume29
Issue number3
DOIs
Publication statusPublished - Jun 2020

Keywords

  • Process mining
  • Behavioural analysis
  • Fitness
  • Recall
  • Precision
  • Coverage
  • Behavioural comparison
  • System comparison
  • Entropy
  • Conformance checking

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