Pregled bibliografske jedinice broj: 1095830
Inferring Absolutely Non-Circular Attribute Grammars with a Memetic Algorithm
Inferring Absolutely Non-Circular Attribute Grammars with a Memetic Algorithm // Applied Soft Computing, 100 (2020), 106956, 13 doi:10.1016/j.asoc.2020.106956 (međunarodna recenzija, članak, znanstveni)
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Naslov
Inferring Absolutely Non-Circular Attribute Grammars with a Memetic Algorithm
Autori
Ravber, Miha ; Kovačević, Željko ; Črepinšek, Matej ; Mernik, Marjan
Izvornik
Applied Soft Computing (1568-4946) 100
(2020);
106956, 13
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Semantic Inference ; Memetic Algorithm ; Attribute Grammars ; Domain-Specific Languages
Sažetak
When valid syntactical structures are additionally constrained with context-sensitive information the Grammar Inference needs to be extended to the Semantic Inference. In this paper, it is shown that a complete compiler/interpreter for small Domain-Specific Languages (DSLs) can be generated automatically solely from given programs and their associated meanings using Semantic Inference. In this work a wider class of Attribute Grammars has been learned, while only S-attributed and L-attributed Grammars have previously been inferred successfully. Inferring Absolutely Non-Circular Attribute Grammars (ANC-AG) with complex dependencies among attributes has been achieved by integrating a Memetic Algorithm (MA) into the LISA.SI tool. The results show that the proposed Memetic Algorithm is at least four times faster on the selected benchmark than the previous method.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo, Temeljne tehničke znanosti, Interdisciplinarne tehničke znanosti, Informacijske i komunikacijske znanosti
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus