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Counting subgraphs is, however, computationally very expensive, and there has been a large body of work on efficient algorithms and strategies to make subgraph counting feasible for larger subgraphs and networks.<\/jats:p>\n          <jats:p>This survey aims precisely to provide a comprehensive overview of the existing methods for subgraph counting. Our main contribution is a general and structured review of existing algorithms, classifying them on a set of key characteristics, highlighting their main similarities and differences. We identify and describe the main conceptual approaches, giving insight on their advantages and limitations, and we provide pointers to existing implementations. We initially focus on exact sequential algorithms, but we also do a thorough survey on approximate methodologies (with a trade-off between accuracy and execution time) and parallel strategies (that need to deal with an unbalanced search space).<\/jats:p>","DOI":"10.1145\/3433652","type":"journal-article","created":{"date-parts":[[2021,3,6]],"date-time":"2021-03-06T04:09:57Z","timestamp":1615003797000},"page":"1-36","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":96,"title":["A Survey on Subgraph Counting"],"prefix":"10.1145","volume":"54","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5768-1383","authenticated-orcid":false,"given":"Pedro","family":"Ribeiro","sequence":"first","affiliation":[{"name":"INESC TEC &amp; Faculty of Sciences, University of Porto, Portugal"}]},{"given":"Pedro","family":"Paredes","sequence":"additional","affiliation":[{"name":"INESC TEC &amp; Faculty of Sciences, University of Porto, Portugal and Carnegie Mellon University, Pittsburgh, PA, USA"}]},{"given":"Miguel E. P.","family":"Silva","sequence":"additional","affiliation":[{"name":"INESC TEC &amp; Faculty of Sciences, University of Porto, Portugal and University of Manchester, UK"}]},{"given":"David","family":"Aparicio","sequence":"additional","affiliation":[{"name":"INESC TEC &amp; Faculty of Sciences, University of Porto, Portugal"}]},{"given":"Fernando","family":"Silva","sequence":"additional","affiliation":[{"name":"INESC TEC &amp; Faculty of Sciences, University of Porto, Portugal"}]}],"member":"320","published-online":{"date-parts":[[2021,3,5]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1162\/artl_a_00045"},{"key":"e_1_2_1_2_1","unstructured":"Nesreen K. Ahmed. 2018. A Parallel Graphlet Decomposition Library for Large Graphs. Retrieved from https:\/\/github.com\/nkahmed\/PGD.  Nesreen K. Ahmed. 2018. A Parallel Graphlet Decomposition Library for Large Graphs. 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