{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T16:28:49Z","timestamp":1783096129802,"version":"3.54.6"},"reference-count":63,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T00:00:00Z","timestamp":1772150400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T00:00:00Z","timestamp":1772150400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100008007","name":"Universit\u00e4t Paderborn","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100008007","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Autom Softw Eng"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Android apps collecting data from users must comply with legal frameworks to ensure data protection. This requirement has become even more important since the implementation of the General Data Protection Regulation (GDPR) by the European Union in 2018. Moreover, with the proposed Cyber Resilience Act on the horizon, stakeholders will soon need to assess software against even more stringent security and privacy standards. Effective privacy assessments require collaboration among groups with diverse expertise to function effectively as a cohesive unit. This paper presents an interview-based study (N=16) exploring the challenges these experts encounter during privacy assessments and their views on automation as potential support. To ground the discussion, we use\n                    <jats:italic>Assessor View<\/jats:italic>\n                    , a prototype developed for this work that integrates static analysis to extract privacy-relevant information directly from Android Application Packages (APKs), as a research probe. Its design provides dedicated views for both technical and non-technical stakeholders, enabling reflection on how automation can enhance assessment practice. Our study identifies key challenges in conducting privacy assessments, including knowledge and communication gaps between experts, the privacy\u2013innovation trade-off, delayed involvement of privacy professionals, and the lack of source code analysis-based tools. The user study conducted alongside the interviews reveals that the GDPR warnings and guidance provided by Assessor View are valuable to Data Protection Officers and privacy experts, and its design is particularly well suited for these stakeholders. Overall, our findings indicate that Assessor View represents a significant step toward improving communication between legal and technical experts and automating privacy assessments.\n                  <\/jats:p>","DOI":"10.1007\/s10515-026-00601-4","type":"journal-article","created":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T11:52:45Z","timestamp":1772193165000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Between law and code: challenges and opportunities for automating privacy assessments"],"prefix":"10.1007","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-0434-381X","authenticated-orcid":false,"given":"Mugdha","family":"Khedkar","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6600-6171","authenticated-orcid":false,"given":"Michael","family":"Schlichtig","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-0347-5304","authenticated-orcid":false,"given":"Nihad","family":"Atakishiyev","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3470-3647","authenticated-orcid":false,"given":"Eric","family":"Bodden","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,2,27]]},"reference":[{"key":"601_CR1","doi-asserted-by":"publisher","unstructured":"Arzt, S., Rasthofer, S., Fritz, C., Bodden, E., Bartel, A., Klein, J., Le Traon, Y., Octeau, D., McDaniel, P.: Flowdroid: Precise context, flow, field, object-sensitive and lifecycle-aware taint analysis for android apps. 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