{"id":"https://openalex.org/W7162210980","doi":"https://doi.org/10.1145/3748522.3779865","title":"A Subjective Logic-based method for runtime confidence updates in safety arguments","display_name":"A Subjective Logic-based method for runtime confidence updates in safety arguments","publication_year":2026,"publication_date":"2026-03-23","ids":{"openalex":"https://openalex.org/W7162210980","doi":"https://doi.org/10.1145/3748522.3779865"},"language":null,"primary_location":{"id":"doi:10.1145/3748522.3779865","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3748522.3779865","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 41st ACM/SIGAPP Symposium on Applied Computing","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3748522.3779865","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051998406","display_name":"Benjamin Herd","orcid":null},"institutions":[{"id":"https://openalex.org/I4210127444","display_name":"Fraunhofer Institute for Cognitive Systems","ror":"https://ror.org/02fez3815","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210127444","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Benjamin Herd","raw_affiliation_strings":["Fraunhofer IKS, Munich, Germany"],"raw_orcid":"https://orcid.org/0000-0001-6439-8845","affiliations":[{"raw_affiliation_string":"Fraunhofer IKS, Munich, Germany","institution_ids":["https://openalex.org/I4210127444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136777442","display_name":"Jessica Kelly","orcid":null},"institutions":[{"id":"https://openalex.org/I4210127444","display_name":"Fraunhofer Institute for Cognitive Systems","ror":"https://ror.org/02fez3815","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210127444","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jessica Kelly","raw_affiliation_strings":["Fraunhofer IKS, Munich, Germany"],"raw_orcid":"https://orcid.org/0009-0003-0508-2367","affiliations":[{"raw_affiliation_string":"Fraunhofer IKS, Munich, Germany","institution_ids":["https://openalex.org/I4210127444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119303206","display_name":"Clarissa Heinemann","orcid":null},"institutions":[{"id":"https://openalex.org/I4210127444","display_name":"Fraunhofer Institute for Cognitive Systems","ror":"https://ror.org/02fez3815","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210127444","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Clarissa Heinemann","raw_affiliation_strings":["Fraunhofer IKS, Munich, Germany"],"raw_orcid":"https://orcid.org/0009-0004-4974-1608","affiliations":[{"raw_affiliation_string":"Fraunhofer IKS, Munich, Germany","institution_ids":["https://openalex.org/I4210127444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011540519","display_name":"Jo\u00e3o-Vitor Zacchi","orcid":"https://orcid.org/0009-0002-6975-6829"},"institutions":[{"id":"https://openalex.org/I4210127444","display_name":"Fraunhofer Institute for Cognitive Systems","ror":"https://ror.org/02fez3815","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210127444","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jo\u00e3o Vitor Zacchi","raw_affiliation_strings":["Fraunhofer IKS, Munich, Germany"],"raw_orcid":"https://orcid.org/0009-0002-6975-6829","affiliations":[{"raw_affiliation_string":"Fraunhofer IKS, Munich, Germany","institution_ids":["https://openalex.org/I4210127444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5051998406"],"corresponding_institution_ids":["https://openalex.org/I4210127444"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.84178553,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1478","last_page":"1485"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13295","display_name":"Safety Systems Engineering in Autonomy","score":0.9824000000953674,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13295","display_name":"Safety Systems Engineering in Autonomy","score":0.9824000000953674,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10142","display_name":"Formal Methods in Verification","score":0.004399999976158142,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11357","display_name":"Risk and Safety Analysis","score":0.0019000000320374966,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6157000064849854},{"id":"https://openalex.org/keywords/confidence-interval","display_name":"Confidence interval","score":0.40529999136924744},{"id":"https://openalex.org/keywords/low-confidence","display_name":"Low Confidence","score":0.3337000012397766},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.319599986076355},{"id":"https://openalex.org/keywords/safety-assurance","display_name":"Safety assurance","score":0.3181000053882599},{"id":"https://openalex.org/keywords/credible-interval","display_name":"Credible interval","score":0.2962999939918518}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6690999865531921},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6157000064849854},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.40529999136924744},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40130001306533813},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.3686000108718872},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.3598000109195709},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34929999709129333},{"id":"https://openalex.org/C2909755999","wikidata":"https://www.wikidata.org/wiki/Q4751126","display_name":"Low Confidence","level":2,"score":0.3337000012397766},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.319599986076355},{"id":"https://openalex.org/C112805685","wikidata":"https://www.wikidata.org/wiki/Q10566551","display_name":"Safety assurance","level":2,"score":0.3181000053882599},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3043999969959259},{"id":"https://openalex.org/C121117317","wikidata":"https://www.wikidata.org/wiki/Q4439221","display_name":"Credible interval","level":3,"score":0.2962999939918518},{"id":"https://openalex.org/C2780234205","wikidata":"https://www.wikidata.org/wiki/Q2281276","display_name":"Safety case","level":2,"score":0.2937999963760376},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.29089999198913574},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.2822999954223633}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3748522.3779865","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3748522.3779865","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 41st ACM/SIGAPP Symposium on Applied Computing","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2605.22530","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2605.22530","pdf_url":"https://arxiv.org/pdf/2605.22530","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3748522.3779865","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3748522.3779865","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 41st ACM/SIGAPP Symposium on Applied Computing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320323803","display_name":"Bundesministerium f\u00fcr Wirtschaft und Energie","ror":"https://ror.org/02vgg2808"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,88],"present":[1],"a":[2,40,60,93],"method":[3,19,91],"for":[4],"dynamic":[5],"quantitative":[6],"assurance":[7,45],"that":[8,62],"enhances":[9],"static":[10],"safety":[11],"cases":[12],"with":[13],"continuous,":[14],"runtime-driven":[15],"confidence":[16,23,64,110],"updates.":[17,87],"The":[18],"quantifies":[20],"and":[21,32,54,70,107],"propagates":[22],"across":[24],"the":[25,66,90],"development":[26],"lifecycle":[27],"by":[28],"integrating":[29],"design-time":[30],"evidence":[31,50,114],"windowed":[33],"runtime":[34],"Safety":[35],"Performance":[36],"Indicators":[37],"(SPIs)":[38],"within":[39],"single":[41],"Subjective":[42],"Logic":[43],"(SL)-based":[44],"case.":[46],"At":[47],"runtime,":[48],"SPI":[49,113],"is":[51,115],"continuously":[52],"evaluated,":[53],"targeted":[55],"claims":[56],"are":[57],"updated":[58],"using":[59,92],"rule":[61],"increases":[63],"in":[65,117],"absence":[67],"of":[68],"violations":[69,75],"imposes":[71],"prompt":[72],"penalties":[73],"when":[74],"occur.":[76],"This":[77],"design":[78],"prioritizes":[79],"safety-relevant":[80],"responsiveness":[81],"over":[82],"exact":[83],"classical":[84],"Bayesian":[85],"posterior":[86],"demonstrate":[89],"simulation-based":[94],"construction":[95,103],"zone":[96],"assist":[97],"function,":[98],"focusing":[99],"on":[100],"an":[101],"ML-based":[102],"cone":[104],"detection":[105],"component,":[106],"show":[108],"how":[109],"evolves":[111],"as":[112],"observed":[116],"operation.":[118]},"counts_by_year":[],"updated_date":"2026-06-10T14:10:52.464848","created_date":"2026-05-24T00:00:00"}