Just-in-time learning for bottom-up enumerative synthesis

A key challenge in program synthesis is the astronomical size of the search space the synthesizer has to explore. In response to this challenge, recent work proposed to guide synthesis using learned probabilistic models. Obtaining such a model, however, might be infeasible for a problem domain where...

Celý popis

Podrobná bibliografia

Vydané v:	Proceedings of ACM on programming languages Ročník 4; číslo OOPSLA; s. 1 - 29
Hlavní autori:	Barke, Shraddha, Peleg, Hila, Polikarpova, Nadia
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York, NY, USA ACM 13.11.2020
Predmet:	Context specific languages Domain specific languages Programming by example Software and its engineering Software notations and tools Probabilistic models Domain-specific languages Program Synthesis
ISSN:	2475-1421, 2475-1421
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!