dFlow: A Domain Specific Language for the Rapid Development of open-source Virtual Assistants
Nikolaos Malamas, Konstantinos Panayiotou, Andreas L. Symeonidis

TL;DR
dFlow is a domain-specific language designed to simplify and accelerate the development of virtual assistants, making it accessible to non-experts through a low-code, framework-agnostic approach with cloud deployment.
Contribution
It introduces a novel textual DSL for VA development that is reusable, framework-independent, and supports rapid, low-code creation of task-specific virtual assistants.
Findings
Accelerates VA development process for users
Enables non-experts to create VAs with minimal experience
Positive feedback from over 200 junior developers
Abstract
An increasing number of models and frameworks for Virtual Assistant (VA) development exist nowadays, following the progress in the Natural Language Processing (NLP) and Natural Language Understanding (NLU) fields. Regardless of their performance, popularity, and ease of use, these frameworks require at least basic expertise in NLP and software engineering, even for simple and repetitive processes, limiting their use only to the domain and programming experts. However, since the current state of practice of VA development is a straightforward process, Model-Driven Engineering approaches can be utilized to achieve automation and rapid development in a more convenient manner. To this end, we present \textit{dFlow}, a textual Domain-Specific Language (DSL) that offers a simplified, reusable, and framework-agnostic language for creating task-specific VAs in a low-code manner. We describe a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAI in Service Interactions · Ethics and Social Impacts of AI · Open Source Software Innovations
