ESR 8: Capability Discovery and Reuse in Low-code System Models
Different systems within similar domains tend to share capabilities (e.g. retail systems tend to share capabilities related to the management of customers, products, orders and payments), which in the absence of effective discovery and reuse mechanisms are wastefully re-invented from scratch. This can hamper both productivity and feature-completeness. As such, facilities for automated discovery and recommendation of relevant capabilities through semantic analysis of models of other low-code systems are much desired.
The aim of this project is to facilitate model-level component discovery and reuse through automated identification of relevant low-code system model fragments from other, related system models. To achieve this aim, the project will investigate the use of a graph-based repository that can accommodate models from different low-code systems and establish probabilistic links between their components, as well as a reinforcement learning-based approach to improve the accuracy of such links.
The project will facilitate the discovery and reuse of relevant capabilities for low-code systems. It will achieve this by introducing a graph-based repository that will accommodate and analyse models of different low-code systems, in order to produce accurate recommendations about missing or underdeveloped features. This will enhance both the productivity or low-code system engineers and the feature-completeness of the produced low-code systems.
This position has been filled.
Please note that the vacancy on the institutionnal website must be considered as the official version of this PhD position.