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...
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| Published in: | Proceedings of ACM on programming languages Vol. 4; no. OOPSLA; pp. 1 - 29 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
New York, NY, USA
ACM
13.11.2020
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| Subjects: | |
| ISSN: | 2475-1421, 2475-1421 |
| Online Access: | Get full text |
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