Mechanizing the development of hard-to-write and costly-to-maintain software is the core problem of automated software design. Encoding expert knowledge (a.k.a. dark knowledge) about a software domain is central to its solution. We assert that a solution can be cast in terms of the ideas of language design and engineering. Graph grammars can be a foundation for modern automated software development. The sentences of a grammar are designs of complex dataflow systems. We explain how graph grammars provide a framework to encode expert knowledge, produce correct-by-construction derivations of dataflow applications, enable the generation of high-performance code, and improve how software design of dataflow applications can be taught to undergraduates. © 2013 Springer International Publishing.
CITATION STYLE
Batory, D., Gonçalves, R., Marker, B., & Siegmund, J. (2013). Dark knowledge and graph grammars in automated software design. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8225 LNCS, pp. 1–18). https://doi.org/10.1007/978-3-319-02654-1_1
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