Paper Info
Title
Dark Knowledge and Graph Grammars in Automated Software Design.
Abstract
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.
Year
DOI
Venue
2013
10.1007/978-3-319-02654-1_1
Lecture Notes in Computer Science
Field
DocType
Volume
Rule-based machine translation,Visual language,Software design,Programming language,Software engineering,Computer science,Dataflow,Software,Graph rewriting,Software construction,Software development
Conference
8225
ISSN
Citations 
PageRank 
0302-9743
5
0.45
References 
Authors
38
4
Name
Order
Citations
PageRank
Don S. Batory156041237.66
Rui Gonçalves281.52
Bryan Marker317811.58
Janet Siegmund433827.69