Projets par an
Concept location in software engineering is the process of identifying where a specific concept is implemented in the source code of a software system. It is a very common task performed by developers during development or maintenance, and many techniques have been studied by researchers to make it more efficient. However, most of the current techniques ignore the role of a database in the architecture of a system, which is also an important source of concepts or dependencies among them. In this paper, we present a concept location technique for data-intensive systems, as systems with at least one database server in their architecture which is intensively used by its clients. Specifically, we present a static technique for identifying the exact source code location from where a given SQL query was sent to the database. We evaluate our technique by collecting and locating SQL queries from testing scenarios of two open source Java systems under active development. With our technique, we are able to successfully identify the source of most of these queries.
|titre||Proceedings of the 22nd IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER 2015)|
|Editeur||IEEE Computer Society Press|
|Nombre de pages||5|
|Etat de la publication||Publié - 8 avr. 2015|
|Evénement||22nd IEEE International Conference on Software Analysis, Evolution, and Reengineering, SANER 2015 - Montreal, Canada|
Durée: 2 mars 2015 → 6 mars 2015
|Une conférence||22nd IEEE International Conference on Software Analysis, Evolution, and Reengineering, SANER 2015|
|période||2/03/15 → 6/03/15|
Empreinte digitaleExaminer les sujets de recherche de « Where was this SQL query executed? a static concept location approach ». Ensemble, ils forment une empreinte digitale unique.
- 2 Terminé
Analyse empirique de la co-évolution et l'interaction sociale dans les systèmes logiciels orientés données
Cleve, A. & Mens, T.
1/07/13 → 30/06/17
Thèses de l'étudiant
Analyzing, Understanding and Supporting the Evolution of Dynamic and Heterogeneous Data-Intensive Software SystemsAuteur: Meurice, L., 22 juin 2017
Student thesis: Doc types › Docteur en SciencesFichier