Mining of DSLs and generator templates from reference applications

Abstract

Domain-Specific Languages (DSLs) found application in different domains. The development of Model-Driven Development (MDD) components is facilitated by a wealth of frameworks like EMF, Xtext, and Xtend. However, the development of the necessary IDE components still can take up to several weeks or even months until it can be used in a production environment. The first step during the development of such an MDD infrastructure is to analyse a set of reference applications to deduce the DSL used by the domain experts and the templates used in the generator. The analysis requires technical expertise and is usually performed by MDD infrastructure developers, who have to adhere to a close communication with domain experts and are exposed to high cognitive load and time-consuming tasks. The objective of this PhD project is to reduce the initial effort during the creation of new MDD infrastructure facilities for either a new domain or newly discovered platforms within a known domain. This should be made possible by the (semi-)automatic analysis of multiple codebases using Code Clone Detection (CCD) tools in a defined process flow. Code clones represent schematically redundant and generic code fragments which were found in the provided codebase. In the process, the key steps include (i) choosing appropriate reference applications (ii) distinguishing the codebase by clustering the files, (iii) reviewing the quality of the clusters, (iv) analysing the cluster by tailored CCD, and (v) transforming of the code clones, depending on the code clone type, to extract a DSL and the corresponding generator templates.