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Title:
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Predicting access to persistent objects through static code analysis
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Author:
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Touma, Rizkallah; Queralt Calafat, Anna; Cortés, Toni; Pérez Hernandez, María S.
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Other authors:
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Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors; Universitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions |
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Abstract:
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In this paper, we present a fully-automatic, high-accuracy approach to predict access to persistent objects through static code analysis of object-oriented applications. The most widely-used previous technique uses a simple heuristic to make the predictions while approaches that offer higher accuracy are based on monitoring application execution. These approaches add a non-negligible overhead to the application’s execution time and/or consume a considerable amount of memory. By contrast, we demonstrate in our experimental study that our proposed approach offers better accuracy than the most common technique used to predict access to persistent objects, and makes the predictions farther in advance, without performing any analysis during application execution |
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Abstract:
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This work has been supported by the European Union’s Horizon 2020 research and
innovation program (grant H2020-MSCA-ITN-2014-642963), the Spanish Government
(grant SEV2015-0493 of the Severo Ochoa Program), the Spanish Ministry of Science and Innovation (contract TIN2015-65316) and Generalitat de Catalunya (contract 2014-SGR-1051). The authors would also like to thank Alex Barceló for his feedback on the formalization included in this paper. |
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Abstract:
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Peer Reviewed |
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Subject(s):
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-Àrees temàtiques de la UPC::Informàtica::Sistemes d'informació::Bases de dades
-Database management
-Persistent objects
-Predictions
-Heuristic
-Bases de dades -- Gestió |
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Rights:
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Document type:
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Article - Submitted version
Conference Object |
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Published by:
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Springer
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Share:
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