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      Using Process Mining Metrics to Measure Noisy Process Fidelity

      proceedings-article
      ,
      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
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            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.

            Content

            Author and article information

            Contributors
            Conference
            April 2009
            April 2009
            : 1-4
            Affiliations
            [0001]Department of Computer Science, University of Sheffield, Regent Court, 211 Portobello, Sheffield S1 4DP
            Article
            10.14236/ewic/EASE2009.16
            088da338-95ab-4e9c-8426-e8211a6da0b2
            © 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)
            History
            Product

            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
            Electronic Workshops in Computing

            Applied computer science,Computer science,Security & Cryptology,Graphics & Multimedia design,General computer science,Human-computer-interaction
            process fidelity,metric,empirical,evaluation,multiple case study

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