Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash 99 tok/s
Gemini 2.5 Pro 43 tok/s Pro
GPT-5 Medium 28 tok/s
GPT-5 High 35 tok/s Pro
GPT-4o 94 tok/s
GPT OSS 120B 476 tok/s Pro
Kimi K2 190 tok/s Pro
2000 character limit reached

A Simple Methodology for Model-Driven Business Innovation and Low Code Implementation (2010.11611v1)

Published 22 Oct 2020 in cs.SE

Abstract: Low Code platforms, according to Gartner Group, represent one of the more disruptive technologies in the development and maintenance of enterprise applications. The key factor is represented by the central involvement of business people and domain expert, with a substantial disintermediation with respect to technical people. In this paper we propose a methodology conceived to support non-technical people in addressing business process innovation and developing enterprise software application. The proposed methodology, called EasInnova, is solidly rooted in Model-Driven Engineering and adopts a three staged model of an innovation undertaking. The three stages are: AsIs that models the existing business scenario; Transformation that consists in the elaboration of the actual innovation; ToBe that concerns the modeling of new business scenario. The core of EasInnova is represented by a matrix where columns are the three innovation stages and the rows are the three Model-Driven Architecture layers: CIM, PIM, PSM. The cells indicate the steps to be followed in achieving the sought innovation. Finally, the produced models will be transferred onto a BonitaSoft, the Low Code platform selected in our work. The methodology is described by means of a simple example in the domain of home food delivery.

Citations (3)
List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Summary

We haven't generated a summary for this paper yet.

Ai Generate Text Spark Streamline Icon: https://streamlinehq.com

Paper Prompts

Sign up for free to create and run prompts on this paper using GPT-5.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-up Questions

We haven't generated follow-up questions for this paper yet.

Authors (1)