Detecting and Preventing Program Inconsistencies under Database Schema Evolution

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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 originaleAnglais
titreProceedings - 2016 IEEE International Conference on Software Quality, Reliability and Security, QRS 2016
EditeurInstitute of Electrical and Electronics Engineers Inc.
Pages262-273
Nombre de pages12
ISBN (Electronique)9781509041275
Les DOIs
Etat de la publicationPublié - 12 oct. 2016
Evénement2nd IEEE International Conference on Software Quality, Reliability and Security, QRS 2016 - Vienna, Autriche
Durée: 1 août 20163 août 2016

Une conférence

Une conférence2nd IEEE International Conference on Software Quality, Reliability and Security, QRS 2016
PaysAutriche
La villeVienna
période1/08/163/08/16

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  • Thèses de l'étudiant

    Analyzing, Understanding and Supporting the Evolution of Dynamic and Heterogeneous Data-Intensive Software Systems

    Author: Meurice, L., 22 juin 2017

    Superviseur: Cleve, A. (Promoteur), Englebert, V. (Président), Lanza, M. (Personne externe) (Jury), Mens, T. (Personne externe) (Jury), Frenay, B. (Jury) & Vanhoof, W. (Jury)

    Thèse de l'étudiant: Doc typesDocteur en Sciences

    Fichier

    Prix

    Best Paper Award

    Meurice, Loup (Bénéficiaire), Cleve, Anthony (Bénéficiaire) & NAGY, CSABA (Bénéficiaire), 2016

    Prix: Prix ​​(y compris les médailles et récompenses)

    Contient cette citation

    Meurice, L., Nagy, C., & Cleve, A. (2016). Detecting and Preventing Program Inconsistencies under Database Schema Evolution. Dans Proceedings - 2016 IEEE International Conference on Software Quality, Reliability and Security, QRS 2016 (p. 262-273). [7589806] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/QRS.2016.38