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https://hdl.handle.net/1822/89924
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Campo DC | Valor | Idioma |
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dc.contributor.author | Macedo, José Nuno Castro | por |
dc.contributor.author | Rodrigues, Emanuel | por |
dc.contributor.author | Viera, Marcos | por |
dc.contributor.author | Saraiva, João | por |
dc.date.accessioned | 2024-03-25T10:06:02Z | - |
dc.date.available | 2024-03-25T10:06:02Z | - |
dc.date.issued | 2023 | - |
dc.identifier.citation | José Nuno Macedo, Emanuel Rodrigues, Marcos Viera, and João Saraiva. 2023. Efficient Embedding of Strategic Attribute Grammars via Memoization. In Proceedings of the 2023 ACM SIGPLAN International Workshop on Partial Evaluation and Program Manipulation (PEPM ’23), January 16–17, 2023, Boston, MA, USA. ACM, New York, NY, USA, 14 pages. https://doi.org/10.1145/3571786.3573019 | por |
dc.identifier.isbn | 979-8-4007-0011-8 | - |
dc.identifier.uri | https://hdl.handle.net/1822/89924 | - |
dc.description.abstract | Strategic term re-writing and attribute grammars are two powerful programming techniques widely used in language engineering. The former relies on strategies to apply term rewrite rules in defining large-scale language transformations, while the latter is suitable to express context-dependent language processing algorithms. These two techniques can be expressed and combined via a powerful navigation abstraction: generic zippers. This results in a concise zipper-based embedding offering the expressiveness of both techniques. Such elegant embedding has a severe limitation since it recomputes attribute values. This paper presents a proper and efficient embedding of both techniques. First, attribute values are memoized in the zipper data structure, thus avoiding their re-computation. Moreover, strategic zipper based functions are adapted to access such memoized values. We have implemented our memoized embedding as the Ztrategic library and we benchmarked it against the state-of-the-art Strafunski and Kiama libraries. Our first results show that we are competitive against those two well established libraries. | por |
dc.description.sponsorship | This work is financed by National Funds through the Portuguese funding agency, FCT - Fundação para a Ciência e a Tecnologia, within project LA/P/0063/2020. The first author is also sponsored by FCT grant 2021.08184.BD. | por |
dc.language.iso | eng | por |
dc.publisher | Association for Computing Machinery (ACM) | por |
dc.relation | LA/P/0063/2020 | por |
dc.relation | 2021.08184.BD | por |
dc.rights | openAccess | por |
dc.subject | Strategic programming | por |
dc.subject | Attribute grammars | por |
dc.subject | Zippers | por |
dc.subject | Generic traversals | por |
dc.title | Efficient embedding of strategic attribute grammars via memoization | por |
dc.type | conferencePaper | por |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | https://dl.acm.org/doi/10.1145/3571786.3573019 | por |
oaire.citationStartPage | 41 | por |
oaire.citationEndPage | 54 | por |
oaire.citationConferencePlace | Boston MA, USA | por |
dc.identifier.doi | 10.1145/3571786.3573019 | por |
sdum.conferencePublication | PEPM 2023 - Proceedings of the 2023 ACM SIGPLAN International Workshop on Partial Evaluation and Program Manipulation, co-located with POPL 2023, | por |
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3571786.3573019.pdf | 967,14 kB | Adobe PDF | Ver/Abrir |