{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/evaluating-the-performance-of-clone-detection","title":"Evaluating the Performance of Clone Detection Tools in Detecting Cloned Co-change Candidates","arxiv_id":"2201.07996","date":"2022-01-20","proceeding":null,"authors":["Md Nadim","Manishankar Mondal","Chanchal K. Roy","Kevin Schneider"],"abstract":"Co-change candidates are the group of code fragments that require a change if any of these fragments experience a modification in a commit operation during software evolution. The cloned co-change candidates are a subset of the co-change candidates, and the members in this subset are clones of one another. The cloned co-change candidates are usually created by reusing existing code fragments in a software system. Detecting cloned co-change candidates is essential for clone-tracking, and studies have shown that we can use clone detection tools to find cloned co-change candidates. However, although several studies evaluate clone detection tools for their accuracy in detecting cloned fragments, we found no study that evaluates clone detection tools for detecting cloned co-change candidates. In this study, we explore the dimension of code clone research for detecting cloned co-change candidates. We compare the performance of 12 different configurations of nine promising clone detection tools in identifying cloned co-change candidates from eight open-source C and Java-based subject systems of various sizes and application domains. A ranked list and analysis of the results provides valuable insights and guidelines into selecting and configuring a clone detection tool for identifying co-change candidates and leads to a new dimension of code clone research into change impact analysis.","url_abs":"https://arxiv.org/abs/2201.07996v1","url_pdf":"https://arxiv.org/pdf/2201.07996v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"evaluating-the-performance-of-clone-detection","repo_url":"https://github.com/mnadims/findcochangebyclone","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}