Abstract. An oft-cited reason for lack of adoption of model-driven engineering (MDE) is poor tool support. However, studies have shown that adoption problems are as much to do with social and organizational factors as with tooling issues. This paper discusses the impact of tools on MDE adoption and places tooling within a broader organizational context.

Although poor tool support is often blamed for the low uptake of model-driven engineering (MDE), recent studies have shown that adoption problems are as likely to be down to social and organizational factors as with tooling issues. This article discusses the impact of tools on MDE adoption and practice and does so whilst placing tooling within a broader organizational context. The article revisits previous data on MDE use in industry (19 in-depth interviews with MDE practitioners) and re-analyzes that data through the specific lens of MDE tools in an attempt to identify and categorize the issues that users had with the tools they adopted. In addition, the article presents new data: 20 new interviews in two specific companies-and analyzes it through the same lens. A key contribution of the paper is a loose taxonomy of tool-related considerations, based on empirical industry data, which can be used to reflect on the tooling landscape as well as inform future research on MDE tools.

Hutchinson et al. recently carried out an interview-based study of how model-driven engineering is practiced in 17 companies. Their results are revealing: they found that successful MDE companies develop domain-specific languages; are motivated by a clear business case; and are committed at all levels of the organization. Whilst the results are useful, the study is a very broad one, with one or two interviewees per company. This paper supplements Hutchinson's study by focusing on three large companies, but studying the companies in depth through a number of interviews at each. These three companies have a number of things in common -they are all large companies applying MDE and are all undergoing a parallel transition to agile methods. The paper reflects on similarities and differences in the way these companies apply model-driven engineering, but also discusses how findings from this study either validate or refute those of Hutchinson et al.