On the granularity of linguistic reuse

Programming languages are complex software systems integrated across an ecosystem of different applications such as language compilers or interpreters but also an integrated development environ- ment comprehensive of syntax highlighting, code completion, error recovery, and a debugger. The complexity of language ecosystems can be faced using language workbenches—i.e., tools that tackle the development of programming languages, domain specific languages and their ecosystems in a modular way. As with any other software system, one of the priorities that developers struggle to achieve when developing programming languages is reusability. After all, the capacity to easily reuse and adapt existing components to new scenarios can dramatically improve development times. Therefore, as programming languages offer features to reuse existing code, language workbenches should offer tools to reuse existing language assets. However, reusability can be achieved in many different ways. In this work, we identify six forms of linguistic reusability, ordered by level of granularity: (i) sub- languages composition, (ii) language features composition, (iii) syntax and semantics assets composition, (iv) semantic assets composition, (v) actions composition, and. (vi) action extension. We use these mechanisms to extend the taxonomy of language composition proposed by Erdweg et al. To show a concrete application of this taxonomy, we evaluate the capabilities provided by the Neverlang language workbench with regards to our taxonomy and extend it by adding explicit support for any granularity level that was originally not supported. This is done by instantiating two levels of reusability as actual operators—desugaring, and delegation. We evaluate these operators against the clone-and-own approach, which was the only form of reuse at that level of granularity prior to the introduction of explicit operators. We show that with the clone-and-own approach the design quality of the source code is negatively affected. We conclude that language workbenches can benefit from the introduction of mechanisms to explicitly support reuse at all granularity levels.