Résumé
Nowadays, data-intensive applications tend to access their underlying database in an increasingly dynamic way. The queries that they send to the database server are usually built at runtime, through String concatenation, or Object-Relational-Mapping (ORM) frameworks. This level of dynamicity significantly complicates the task of adapting application programs to database schema changes. Failing to correctly adapt programs to an evolving database schema results in program inconsistencies, which in turn may cause program failures. In this paper, we present a tool-supported approach, that allows developers to (1) analyze how the source code and database schema co-evolved in the past and (2) simulate a database schema change and automatically determine the set of source code locations that would be impacted by this change. Developers are then provided with recommendations about what they should modify at those source code locations in order to avoid inconsistencies. The approach has been designed to deal with Java systems that use dynamic data access frameworks such as JDBC, Hibernate and JPA. We motivate and evaluate the proposed approach, based on three real-life systems of different size and nature.
langue originale | Anglais |
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titre | Proceedings - 2016 IEEE International Conference on Software Quality, Reliability and Security, QRS 2016 |
Editeur | Institute of Electrical and Electronics Engineers Inc. |
Pages | 262-273 |
Nombre de pages | 12 |
ISBN (Electronique) | 9781509041275 |
Les DOIs | |
Etat de la publication | Publié - 12 oct. 2016 |
Evénement | 2nd IEEE International Conference on Software Quality, Reliability and Security, QRS 2016 - Vienna, Autriche Durée: 1 août 2016 → 3 août 2016 |
Une conférence
Une conférence | 2nd IEEE International Conference on Software Quality, Reliability and Security, QRS 2016 |
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Pays/Territoire | Autriche |
La ville | Vienna |
période | 1/08/16 → 3/08/16 |
Empreinte digitale
Examiner les sujets de recherche de « Detecting and Preventing Program Inconsistencies under Database Schema Evolution ». Ensemble, ils forment une empreinte digitale unique.Thèses de l'étudiant
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Analyzing, Understanding and Supporting the Evolution of Dynamic and Heterogeneous Data-Intensive Software Systems
Meurice, L. (Auteur), Cleve, A. (Promoteur), Englebert, V. (Président), Lanza, M. (Jury), Mens, T. (Jury), Frenay, B. (Jury) & Vanhoof, W. (Jury), 22 juin 2017Student thesis: Doc types › Docteur en Sciences
Fichier
Prix
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Best Paper Award at the 2016 International Conference on Software Quality, Reliability and Security (QRS 2016)
Meurice, L. (Bénéficiaire), Nagy, C. (Bénéficiaire) & Cleve, A. (Bénéficiaire), 2016
Prix: Prix (y compris les médailles et récompenses)