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ACM Program. Lang."],"published-print":{"date-parts":[[2023,1,9]]},"abstract":"<jats:p>\n            This paper introduces\n            <jats:italic>corpus-guided top-down synthesis<\/jats:italic>\n            as a mechanism for synthesizing library functions that capture common functionality from a corpus of programs in a domain specific language (DSL). The algorithm builds abstractions directly from initial DSL primitives, using syntactic pattern matching of intermediate abstractions to intelligently prune the search space and guide the algorithm towards abstractions that maximally capture shared structures in the corpus. We present an implementation of the approach in a tool called Stitch and evaluate it against the state-of-the-art deductive library learning algorithm from DreamCoder. Our evaluation shows that Stitch is 3-4 orders of magnitude faster and uses 2 orders of magnitude less memory while maintaining comparable or better library quality (as measured by compressivity). We also demonstrate Stitch\u2019s scalability on corpora containing hundreds of complex programs that are intractable with prior deductive approaches and show empirically that it is robust to terminating the search procedure early\u2014further allowing it to scale to challenging datasets by means of early stopping.\n          <\/jats:p>","DOI":"10.1145\/3571234","type":"journal-article","created":{"date-parts":[[2023,1,11]],"date-time":"2023-01-11T21:58:14Z","timestamp":1673474294000},"page":"1182-1213","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":24,"title":["Top-Down Synthesis for Library Learning"],"prefix":"10.1145","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8450-7033","authenticated-orcid":false,"given":"Matthew","family":"Bowers","sequence":"first","affiliation":[{"name":"Massachusetts Institute of Technology, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6653-2227","authenticated-orcid":false,"given":"Theo X.","family":"Olausson","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8814-7629","authenticated-orcid":false,"given":"Lionel","family":"Wong","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1920-0021","authenticated-orcid":false,"given":"Gabriel","family":"Grand","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1925-2035","authenticated-orcid":false,"given":"Joshua B.","family":"Tenenbaum","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6586-0632","authenticated-orcid":false,"given":"Kevin","family":"Ellis","sequence":"additional","affiliation":[{"name":"Cornell University, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7604-8252","authenticated-orcid":false,"given":"Armando","family":"Solar-Lezama","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology, USA"}]}],"member":"320","published-online":{"date-parts":[[2023,1,11]]},"reference":[{"key":"e_1_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/96709.96712"},{"key":"e_1_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3212695"},{"key":"e_1_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/2635868.2635901"},{"key":"e_1_2_2_4_1","volume-title":"Deepcoder: Learning to write programs. arXiv preprint arXiv:1611.01989.","author":"Balog Matej","year":"2016","unstructured":"Matej Balog , Alexander L Gaunt , Marc Brockschmidt , Sebastian Nowozin , and Daniel Tarlow . 2016 . 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