Brigham Young University BYU ScholarsArchive Theses and Dissertations 2010-12-16 A Reusable Persistence Framework for Replicating Empirical Studies on Data from Open Source Repositories Scott Bong-Soo Chun Brigham Young University - Provo Follow this and additional works at: https://scholarsarchive.byu.edu/etd Part of the Computer Sciences Commons BYU ScholarsArchive Citation Chun, Scott Bong-Soo, "A Reusable Persistence Framework for Replicating Empirical Studies on Data from Open Source Repositories" (2010). Theses and Dissertations. 2371. https://scholarsarchive.byu.edu/etd/2371 This Thesis is brought to you for free and open access by BYU ScholarsArchive. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of BYU ScholarsArchive. For more information, please contact
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[email protected]. A Reusable Persistence Framework for Replicating Empirical Studies on Data From Open Source Repositories Scott B. Chun A thesis submitted to the faculty of Brigham Young University in partial fulfillment of the requirements for the degree of Master of Science Charles D. Knutson, Chair Christophe G. Giraud-Carrier William A. Barrett Department of Computer Science Brigham Young University April 2011 Copyright c 2011 Scott B. Chun All Rights Reserved ABSTRACT A Reusable Persistence Framework for Replicating Empirical Studies on Data From Open Source Repositories Scott B. Chun Department of Computer Science Master of Science Empirical research is inexact and error-prone leading researchers to agree that repli- cation of experiments is a necessary step to validating empirical results. Unfortunately, replicating experiments requires substantial investments in manpower and time. These re- source requirements can be reduced by incorporating component reuse when building tools for empirical experimentation.