Pregled bibliografske jedinice broj: 1188019
Automatic compiler/interpreter generation from programs for Domain-Specific Languages: Code bloat problem and performance improvement
Automatic compiler/interpreter generation from programs for Domain-Specific Languages: Code bloat problem and performance improvement // Journal of Computer Languages, 70 (2022), 101105, 12 doi:10.1016/j.cola.2022.101105 (međunarodna recenzija, članak, znanstveni)
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Naslov
Automatic compiler/interpreter generation from programs for Domain-Specific Languages: Code bloat problem and performance improvement
Autori
Kovačević, Željko ; Ravber, Miha ; Liu, Shih-Hsi ; Črepinšek, Matej
Izvornik
Journal of Computer Languages (2590-1184) 70
(2022);
101105, 12
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Semantic inference ; Genetic programming ; Attribute grammars ; Domain-Specific Languages ; Code bloat
Sažetak
Using advanced AI approaches, the development of Domain-Specific Languages (DSLs) can be facilitated for domain experts who are not proficient in programming language development. In this paper, we first addressed the aforementioned problem using Semantic Inference. However, this approach is very time-consuming. Namely, a lot of code bloat is present in the generated language specifications, which increases the time required to evaluate a solution. To improve this, we introduced a multi-threaded approach, which accelerates the evaluation process by over 9.5 times, while the number of fitness evaluations using the improved Long Term Memory Assistance (LTMA) was reduced by up to 7.3%. Finally, a reduction in the number of input samples (fitness cases) was proposed, which reduces CPU consumption further.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo, Temeljne tehničke 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