Résumé
The increasing data volume and the variety of data formats of modern data-intensive systems unveiled the boundaries of traditional relational database management systems. NoSQL technologies aim to fulfill shortcomings through
numerous features such as allowing unstructured, schema-less data storage. However, new features also pose challenges to software engineering techniques that used to work well for relational databases.
In this paper, we present an approach to retrieve database accesses in JavaScript applications that use MongoDB. The approach handles JavaScript’s highly dynamic and typeless nature through heuristics to avoid collision with third-party libraries. The aim is to identify the part of the source code involved in the
database communication as the first step towards additional static analysis approaches. We evaluated the approach on an oracle of 307 open-source projects and reached a precision of 78%. We demonstrate potential use cases of the approach through case studies on the evolution of open-source systems.
numerous features such as allowing unstructured, schema-less data storage. However, new features also pose challenges to software engineering techniques that used to work well for relational databases.
In this paper, we present an approach to retrieve database accesses in JavaScript applications that use MongoDB. The approach handles JavaScript’s highly dynamic and typeless nature through heuristics to avoid collision with third-party libraries. The aim is to identify the part of the source code involved in the
database communication as the first step towards additional static analysis approaches. We evaluated the approach on an oracle of 307 open-source projects and reached a precision of 78%. We demonstrate potential use cases of the approach through case studies on the evolution of open-source systems.
| langue originale | Anglais |
|---|---|
| titre | Proceedings of the 29th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2022) |
| Editeur | IEEE Computer Society |
| Pages | 930-934 |
| Nombre de pages | 5 |
| ISBN (Electronique) | 9781665437868 |
| Les DOIs | |
| Etat de la publication | Publié - 2022 |
Série de publications
| Nom | Proceedings - 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering, SANER 2022 |
|---|