4.6 Article

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

Publisher

ASSOC COMPUTING MACHINERY
DOI: 10.1145/3387909

Keywords

System comparison; behavioural comparison; behavioural analysis; entropy; process mining; conformance checking; precision; recall; fitness; coverage

Funding

  1. Australian Research Council [DP180102839]
  2. Universities Australia (UA)
  3. German Academic Exchange Service (DAAD)
  4. EU [645751]
  5. Austrian Research Promotion Agency (FFG) [861213]
  6. MIUR of the Department of Computer Science at Sapienza University of Rome

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The behavioural comparison of systems is an important concern of software engineering research. For example, the areas of specification discoveryand 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.

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