ResyDuo: Combining data models and CF-based recommender systems to develop Arduino projects

TL;DR

ResyDuo is a prototype system that combines data models and collaborative filtering to assist Arduino developers in selecting hardware components and software libraries, simplifying IoT project development.

Contribution

The paper introduces ResyDuo, a novel system integrating MDE and CF-based recommender algorithms to support nonexpert Arduino developers in hardware and software selection.

Findings

Encouraging performance in cross-validation tests

Effective retrieval of hardware components via tags and projects

Room for improvement in recommendation accuracy

Abstract

While specifying an IoT-based system, software developers have to face a set of challenges, spanning from selecting the hardware components to writing the actual source code. Even though dedicated development environments are in place, a nonexpert user might struggle with the over-choice problem in selecting the proper component. By combining MDE and recommender systems, this paper proposes an initial prototype, called ResyDuo, to assist Arduino developers by providing two different artifacts, i. e. , hardware components and software libraries. In particular, we make use of a widely adopted collaborative filtering algorithm by collecting relevant information by means of a dedicated data model. ResyDuo can retrieve hardware components by using tags or existing Arduino projects stored on the ProjectHub repository. Then, the system can eventually retrieve corresponding software libraries based on the identified hardware devices. ResyDuo is equipped with a web-based interface that allows users to easily select and configure the under-developing Arduino project. To assess ResyDuos performances, we run the ten-fold crossvalidation by adopting the grid search strategy to optimize the hyperparameters of the CF-based algorithm. The conducted evaluation shows encouraging results even though there is still room for improvement in terms of the examined metrics.