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Nevertheless, a considerable amount of pull requests (PRs) with valid contributions are abandoned by their\n            <jats:italic>contributors<\/jats:italic>\n            , wasting the effort and time put in by both the contributors and maintainers. To better understand the underlying dynamics of contributor-abandoned PRs, we conduct a mixed-methods study using both quantitative and qualitative methods. We curate a dataset consisting of 265,325 PRs including 4,450 abandoned ones from ten popular and mature GitHub projects and measure 16 features characterizing PRs, contributors, review processes, and projects. Using statistical and machine learning techniques, we find that complex PRs, novice contributors, and lengthy reviews have a higher probability of abandonment and the rate of PR abandonment fluctuates alongside the projects\u2019 maturity or workload. To identify why contributors abandon their PRs, we also manually examine a random sample of 354 abandoned PRs. We observe that the most frequent abandonment reasons are related to the obstacles faced by contributors, followed by the hurdles imposed by maintainers during the review process. Finally, we survey the top core maintainers of the studied projects to understand their perspectives on dealing with PR abandonment and on our findings.\n          <\/jats:p>","DOI":"10.1145\/3530785","type":"journal-article","created":{"date-parts":[[2022,5,11]],"date-time":"2022-05-11T11:56:41Z","timestamp":1652270201000},"page":"1-39","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":21,"title":["On Wasted Contributions: Understanding the Dynamics of Contributor-Abandoned Pull Requests\u2013A Mixed-Methods Study of 10 Large Open-Source Projects"],"prefix":"10.1145","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0615-9242","authenticated-orcid":false,"given":"Sayedhassan","family":"Khatoonabadi","sequence":"first","affiliation":[{"name":"Concordia University, Montreal, QC, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7084-2594","authenticated-orcid":false,"given":"Diego Elias","family":"Costa","sequence":"additional","affiliation":[{"name":"Concordia University, Montreal, QC, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9914-5434","authenticated-orcid":false,"given":"Rabe","family":"Abdalkareem","sequence":"additional","affiliation":[{"name":"Carleton University, Ottawa, ON, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1285-9878","authenticated-orcid":false,"given":"Emad","family":"Shihab","sequence":"additional","affiliation":[{"name":"Concordia University, Montreal, QC, Canada"}]}],"member":"320","published-online":{"date-parts":[[2023,2,13]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1111\/rssb.12377"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.21105\/joss.02815"},{"issue":"170","key":"e_1_3_2_4_2","first-page":"1","article-title":"mlr: Machine learning in R","volume":"17","author":"Bischl Bernd","year":"2016","unstructured":"Bernd Bischl, Michel Lang, Lars Kotthoff, Julia Schiffner, Jakob Richter, Erich Studerus, Giuseppe Casalicchio, and Zachary M. 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