Model Clone Detector Evaluation Using Mutation Analysis. Stephan, M. In International Conference on Software Maintenance and Evolution (ICSME), pages 633-638, Sept, 2014. ![Model Clone Detector Evaluation Using Mutation Analysis [pdf]](https://bibbase.org/img/filetypes/pdf.svg "pdf")
Paper doi abstract bibtex Model Clone Detection is a growing area within the field of software model maintenance. New model clone detection techniques and tools for different types of models are being created, however, there is no clear way of objectively and quantitatively evaluating and comparing them. In this paper, we provide a synopsis of our work in devising and validating an evaluation framework that uses Mutation Analysis to provide such a facility. In order to demonstrate the framework's feasibility and also walk through its steps, we implement a framework implementation for evaluating Simulink model clone detectors. This includes a taxonomy of Simulink mutations, Simulink clone report transformations, and more. We outline how the framework calculates precision and recall, and do so on multiple Simulink model clone detectors. In addition, we also discuss areas of future work, including semantic clone mutations, and developing framework implementations for other model types, like UML. Lastly, we address some lessons we learned during the Ph.D. Process, such as partitioning the work into logical, self-contained, milestones, and being open and willing to engage in other research. We hope that our framework will help cultivate further research gains in Model Clone Detection.
@InProceedings{Stephan2014b,
author = {Stephan, Matthew},
title = {{Model Clone Detector Evaluation Using Mutation Analysis}},
booktitle = {International Conference on Software Maintenance and Evolution (ICSME)},
year = {2014},
pages = {633-638},
month = {Sept},
abstract = {Model Clone Detection is a growing area within the field of software model maintenance. New model clone detection techniques and tools for different types of models are being created, however, there is no clear way of objectively and quantitatively evaluating and comparing them. In this paper, we provide a synopsis of our work in devising and validating an evaluation framework that uses Mutation Analysis to provide such a facility. In order to demonstrate the framework's feasibility and also walk through its steps, we implement a framework implementation for evaluating Simulink model clone detectors. This includes a taxonomy of Simulink mutations, Simulink clone report transformations, and more. We outline how the framework calculates precision and recall, and do so on multiple Simulink model clone detectors. In addition, we also discuss areas of future work, including semantic clone mutations, and developing framework implementations for other model types, like UML. Lastly, we address some lessons we learned during the Ph.D. Process, such as partitioning the work into logical, self-contained, milestones, and being open and willing to engage in other research. We hope that our framework will help cultivate further research gains in Model Clone Detection.},
doi = {10.1109/ICSME.2014.113},
issn = {1063-6773},
keywords = {Unified Modeling Language;software maintenance;Simulink clone report transformations;Simulink model clone detectors;Simulink mutation taxonomy;UML;model clone detector evaluation;mutation analysis;semantic clone mutations;software model maintenance;Analytical models;Cloning;Detectors;Mathematical model;Semantics;Software packages;Unified modeling language;Clone Detection;Model Clone Detection;Mutation Analysis;Simulink},
url_paper = {papers/stephanCameraReadyPDS.pdf},
}
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