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English Information

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Authors
# Name
1 Alessandro dos Santos(alesan.2000@alunos.utfpr.edu.br)
2 Eduardo Henrique Monteiro Pena(eduardopena@utfpr.edu.br)

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Reference
# Reference
1 Chu, X., Ilyas, I. F., Krishnan, S., and Wang, J. (2016). Data cleaning: Overview and emerging challenges. In SIGMOD, page 2201–2206.
2 Dallachiesa, M., Ebaid, A., Eldawy, A., Elmagarmid, A., Ilyas, I. F., Ouzzani, M., and Tang, N. (2013). Nadeef: a commodity data cleaning system. In Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data, SIGMOD ’13, page 541–552, New York, NY, USA. Association for Computing Machinery.
3 Fan, W., Geerts, F., Jia, X., and Kementsietsidis, A. (2008). Conditional functional de- pendencies for capturing data inconsistencies. ACM Trans. Database Syst., 33(2).
4 Kersten, T., Leis, V., Kemper, A., Neumann, T., Pavlo, A., and Boncz, P. (2018). Ev- erything you always wanted to know about compiled and vectorized queries but were afraid to ask. Proc. VLDB Endow., 11(13):2209–2222.
5 Livshits, E., Kochirgan, R., Tsur, S., Ilyas, I. F., Kimelfeld, B., and Roy, S. (2021). Proper- ties of inconsistency measures for databases. In Proceedings of the 2021 International Conference on Management of Data, SIGMOD ’21, page 1182–1194, New York, NY, USA. Association for Computing Machinery.
6 Neumann, T. and Freitag, M. J. (2020). Umbra: A disk-based system with in-memory per- formance. In 10th Conference on Innovative Data Systems Research, CIDR 2020, Am- sterdam, The Netherlands, January 12-15, 2020, Online Proceedings. www.cidrdb.org.
7 Pena, E. H. M., de Almeida, E. C., and Naumann, F. (2021). Fast detection of denial constraint violations. Proc. VLDB Endow., 15(4):859–871.
8 Pena, E. H. M., Porto, F., and Naumann, F. (2022). Fast algorithms for denial constraint discovery. Proc. VLDB Endow., 16(4):684–696.
9 Raasveldt, M. and Mu ̈hleisen, H. (2019). Duckdb: an embeddable analytical database. In Proceedings of the 2019 International Conference on Management of Data, SIGMOD ’19, page 1981–1984, New York, NY, USA. Association for Computing Machinery.
10 Rekatsinas, T., Chu, X., Ilyas, I. F., and Re ́, C. (2017). HoloClean: Holistic data repairs with probabilistic inference. Proc. VLDB Endow., 10(11):1190–1201.