{"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/anonymizing-test-data-in-android-does-it-hurt","title":"Anonymizing Test Data in Android: Does It Hurt?","arxiv_id":"2402.07460","date":"2024-02-12","proceeding":null,"authors":["Elena Masserini","Davide Ginelli","Daniela Micucci","Daniela Briola","Leonardo Mariani"],"abstract":"Failure data collected from the field (e.g., failure traces, bug reports, and memory dumps) represent an invaluable source of information for developers who need to reproduce and analyze failures. Unfortunately, field data may include sensitive information and thus cannot be collected indiscriminately. Privacy-preserving techniques can address this problem anonymizing data and reducing the risk of disclosing personal information. However, collecting anonymized information may harm reproducibility, that is, the anonymized data may not allow the reproduction of a failure observed in the field. In this paper, we present an empirical investigation about the impact of privacy-preserving techniques on the reproducibility of failures. In particular, we study how five privacy-preserving techniques may impact reproducibilty for 19 bugs in 17 Android applications. Results provide insights on how to select and configure privacy-preserving techniques.","url_abs":"https://arxiv.org/abs/2402.07460v1","url_pdf":"https://arxiv.org/pdf/2402.07460v1.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":"anonymizing-test-data-in-android-does-it-hurt","repo_url":"https://gitlab.com/sal-unimib-anonymization/anonymization-android-tool","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null},{"paper_slug":"anonymizing-test-data-in-android-does-it-hurt","repo_url":"https://gitlab.com/sal-unimib-anonymization/experimentation","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}