A Visual Tool for Analysing IoT Trigger/Action Programming

Abstract

The Trigger-Action programming paradigm has been widely adopted in the last few years, especially in the Internet of Things (IoT) domain because it allows end users without programming experience to describe how their applications should react to the many events that can occur in such very dynamic contexts. Several end user development tools exist, in both the research and industrial fields, which aim to support the increasing need to specify such rules. Thus, it becomes important for application developers and domain experts to enrich such environments with functionalities able to monitor how users actually interact with such rule editors, and show useful information to analyse the end user activity. In this paper, we present a visual tool for monitoring and analysing how users interact with a trigger-action rule editor. The goal is to provide a tool useful to better understand what end users' personalization needs are, how they are expressed, how users actually specify rules, and whether users encounter any issues in interacting with the personalization features offered by the editors. The proposed solution supports the analysis through a dashboard and a set of timelines describing the actual use of the personalization tool, with the possibility to select specific events of interest. It moreover provides data useful for understanding the types of triggers, actions and rules actually composed by users, and whether they effectively exploit the personalization features offered.