Lessons Learned from Evaluating MDE Abstractions in an Industry Case Study

TL;DR

This paper discusses the challenges of evaluating Model-Driven Engineering abstractions in industry, emphasizing the importance of considering both technical and human factors within complex ecosystems.

Contribution

It provides five lessons learned from an empirical industry case study on evaluating MDE abstractions, highlighting practical challenges and considerations.

Findings

Evaluation of MDE abstractions is complex due to ecosystem factors.

Both technical and human aspects are crucial in empirical assessments.

Lessons learned guide future evaluations in industrial contexts.

Abstract

In a recent empirical study we found that evaluating abstractions of Model-Driven Engineering (MDE) is not as straight forward as it might seem. In this paper, we report on the challenges that we as researchers faced when we conducted the aforementioned field study. In our study we found that modeling happens within a complex ecosystem of different people working in different roles. An empirical evaluation should thus mind the ecosystem, that is, focus on both technical and human factors. In the following, we present and discuss five lessons learnt from our recent work.