Using Process Mining Metrics to Measure Noisy Process Fidelity

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.

Affiliations

Department of Computer Science, University of Sheffield, Regent Court, 211 Portobello, Sheffield S1 4DP

Contributors

Chris Thomson

Marian Gheorghe

Conference

Publication date: April 2009

Publication date (Print): April 2009

Pages: 1-4

ID: 10.14236/ewic/EASE2009.16

Copyright statement: © 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

License:

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/

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

Conference acronym: EASE

Conference number: 13

Conference location: Durham University, UK

Conference date: 20 - 21 April 2009

Conference sponsor: Electronic Workshops in Computing (eWiC)

Conference theme: Evaluation and Assessment in Software Engineering (EASE)

Product

Product Information: 1477-9358 BCS Learning & Development

Self URI (article page): https://www.scienceopen.com/hosted-document?doi=10.14236/ewic/EASE2009.16

Self URI (journal page): https://ewic.bcs.org/

Categories

Series title: Electronic Workshops in Computing