Internship: data-centric software engineering.
Context
A broad spectrum of application domains are increasingly making use of heterogeneous and large volumes of data with varying degrees of humans in the loop. The recent success of Artificial Intelligence (AI) and, in particular, Machine Learning (ML) further amplifies the relevance of data in the development, maintenance, evolution, and execution management of systems. While system development makes use of both models and data, it differs in the types and uses of models and data, and the degree and role of humans in the loop.
To capture these differences, we recently defined the MODA framework [1]. MODA supports the system life-cycle of socio-technical systems, and is intended to handle a broad range of stakeholders and community groups. The framework provides a vision for how to explicitly integrate the three roles played by models – prescriptive, predictive, and descriptive [2,3] – as well as their respective data sources and highlights related actions to integrate them.
Description of the work
The main objective of this internship is to document and analyze the various practices (methods, processes, appraoches, and frameworks) in software engineering using the newly defined MODA framework. For such a purpose, the candidate will perform a review of the litterature about the modern software development practices, formalize them using the MODA framework, and propose a classification according to a set of criteria to be defined.
Environment
The candidate will work at Inria in the DiverSE team. Inria is the French national institute for research in computer science. There are 8 Inria research centres located throughout France, hosting more than 200 research teams. The DiverSE team is located in Rennes. DiverSE’s research is in the area of software engineering. The team is actively involved in European, French and industrial projects and is composed of 9 faculty members, 20 PhD students, 2 post-docs and 4 engineers. The candidate will work in the context of a collaboration with McGill University (Canada). The main supervisor will be Prof. Benoit Combemale (University of Rennes 1, DiverSE team).
References
- Benoit Combemale, Jörg Kienzle, Gunter Mussbacher, Hyacinth Ali, Daniel Amyot, et al.. A Hitchhiker’s Guide to Model-Driven Engineering for Data-Centric Systems. IEEE Software, Institute of Electrical and Electronics Engineers, 2020, pp.1-9. Cf. https://hal.inria.fr/hal-02612087
- T. Kühne, “Unifying explanatory and constructive modeling: towards removing the gulf between ontologies and conceptual models,” in MODELS 2016. ACM, 2016, pp. 95–102.
- E. A. Lee, “Modeling in engineering and science,” Commun. ACM, vol. 62, no. 1, pp. 35–36, Dec. 2018.
