Blog
About

  • Record: found
  • Abstract: found
  • Article: found
Is Open Access

Using Process Mining Metrics to Measure Noisy Process Fidelity

,

13th International Conference on Evaluation and Assessment in Software Engineering (EASE) (EASE)

Evaluation and Assessment in Software Engineering (EASE)

20 - 21 April 2009

process fidelity, empirical, multiple case study, metric, evaluation

Read this article at

Bookmark
      There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

      Abstract

      Background: When teams follow a software development process they do not follow the process consistently. We need a method to measure their fidelity to that process. Objective: To evaluate Rozinat and Aalst’s metrics for process conformance to a state based model on noisy data (Rozinat and van der Aalst, 2008). Method: We instructed 14 teams that were developing a software system using Extreme Programming (XP) to record the events of their project (for example writing code, or testing). We calculated the values of the proposed metrics by comparing the data collected to a process model of XP. Results: 13 teams recoded data that we treat as a multiple case study. The fitness metric gave varying results over the teams that corresponded to the number of event types used in the correct order. The appropriateness metrics measured the same values for all teams. Conclusion: The fitness metric is useful for measuring fidelity, but the appropriateness metrics do not measure over fitting well with noisy data. In addition neither metric gave useful information about other aspects like iteration.

      Related collections

      Author and article information

      Affiliations
      Department of Computer Science, University of Sheffield, Regent Court, 211 Portobello, Sheffield S1 4DP
      Contributors
      Conference
      April 2009
      April 2009
      : 1-4
      10.14236/ewic/EASE2009.16
      © Chris Thomson et al. Published by BCS Learning and Development Ltd. 13th International Conference on Evaluation and Assessment in Software Engineering (EASE), Durham University, UK

      This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

      13th International Conference on Evaluation and Assessment in Software Engineering (EASE)
      EASE
      13
      Durham University, UK
      20 - 21 April 2009
      Electronic Workshops in Computing (eWiC)
      Evaluation and Assessment in Software Engineering (EASE)
      Product
      Product Information: 1477-9358 BCS Learning & Development
      Self URI (journal page): https://ewic.bcs.org/
      Categories
      Electronic Workshops in Computing

      Comments

      Comment on this article