Identifying manual changes to generated code: Experiences from the industrial automation domain

Abstract

In this paper, we report on a case study in an industrial setting where code is generated from models, and, for various reasons, that generated code is then manually modified. To enhance the maintainability of both models and code, consistency between them is imperative. A first step towards establishing that consistency is to identify the manual changes that were made to the code after it was generated and deployed. Identifying the delta is not straightforward and requires pre-processing of the artifacts. The main mechanics driving our solution are higher-order transformations, which make the implementation scalable and robust to small changes in the modeling language. We describe the specific industrial setting of the problem, as well as the experiences and lessons learned from developing, implementing, and validating our solution together with our industrial partner.