{"type":"ScholarlyArticle","title":"An Iterative Approach to Synthesize Data Transformation Programs","authors":[{"name":"Bo Wu","slug":"bo-wu","given":"Bo","family":"Wu","affiliation":""},{"name":"Craig A. Knoblock","slug":"craig-a-knoblock","given":"Craig A.","family":"Knoblock","affiliation":""}],"abstract":"Programming-by-Example approaches allow users to transform data by simply entering the target data. However, current methods do not scale well to complicated examples, where there are many examples or the examples are long.In this paper, we present an approach that exploits the fact that users iteratively provide examples.It reuses the previous subprograms to improve the efficiency in generating new programs.We evaluated the approach with a variety of transformation scenarios.The results show that the approach significantly reduces the time used to generate the transformation programs, especially in complicated scenarios.","doi":null,"url":"https://ijcai.org/proceedings/2015/246","pdf":"https://ijcai.org/proceedings/2015/0246.pdf","markdown":"https://ijcai.org/proceedings/2015/246.md","bibtex":"https://ijcai.org/proceedings/2015/bibtex/246","volume":{"slug":"2015","title":"Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2015","url":"https://ijcai.org/proceedings/2015/","year":2015,"location":"Buenos Aires, Argentina","dates":"25–31 July 2015","editors":"Qiang Yang and Michael Wooldridge","isbn":"978-1-57735-738-4","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Planning","track":"Main Track","number":246,"pages":{"first":1726,"last":1731},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}