From Grammar Inference to Semantic Inference of Domain-Specific Languages

Monday, 16. June 4pm
Room D 238

This talk describes research work on Semantic Inference, which can be regarded as an extension of Grammar Inference. The main task of Grammar Inference is to induce a grammatical structure from a set of positive samples (programs), which can sometimes also be accompanied by a set of negative samples. Successfully applying Grammar Inference can result only in identifying the correct syntax of a language. With the Semantic Inference, a further step is realised, namely, towards inducing language semantics. To solve the problem of Semantic Inference successfully, the Genetic Programming approach was employed, which is an evolutionary search applied to the population of Attribute Grammars. However, automatically generated Attribute Grammars might be harder to comprehend. A controlled classroom experiment that involved two groups of students from two universities was conducted, comparing comprehension between manually written and automatically generated Attribute Grammars.

About Marjan Mernik

Marjan Mernik received the MSc and PhD degrees in Computer Science from the University of Maribor in 1994 and 1998, respectively. He is a professor at the University of Maribor, Faculty of Electrical Engineering and Computer Science. He was a visiting professor at the University of Alabama at Birmingham, Department of Computer and Information Sciences. His research interests include programming languages, domain-specific (modelling) languages, grammar-based systems, and evolutionary computation. He is the Editor-in-Chief of the Journal of Computer Languages, as well as Associate Editor of the Applied Soft Computing Journal and the Swarm and Evolutionary Computation Journal. He has been named a Highly Cited Researcher for 2017 and 2018. More information about his work is available at https://lpm.feri.um.si/en/members/mernik/.

This talk is supported by the Carl Zeiss Stiftung.