{"type":"ScholarlyArticle","title":"Model-Based Diagnosis with Multiple Observations","authors":[{"name":"Alexey Ignatiev","slug":"alexey-ignatiev","given":"Alexey","family":"Ignatiev","affiliation":"Faculty of Science , University of Lisbon , Portugal; ISDCT SB RAS , Irkutsk , Russia"},{"name":"Antonio Morgado","slug":"antonio-morgado","given":"Antonio","family":"Morgado","affiliation":"Faculty of Science , University of Lisbon , Portugal"},{"name":"Georg Weissenbacher","slug":"georg-weissenbacher","given":"Georg","family":"Weissenbacher","affiliation":"TU Wien , Vienna , Austria"},{"name":"Joao Marques-Silva","slug":"joao-marques-silva","given":"Joao","family":"Marques-Silva","affiliation":"Faculty of Science , University of Lisbon , Portugal"}],"abstract":"Existing automated testing frameworks require multiple observations to be jointly diagnosed with the purpose of identifying common fault locations. This is the case for example with continuous integration tools. This paper shows that existing solutions fail to compute the set of minimal diagnoses, and as a result run times can increase by orders of magnitude. The paper proposes not only solutions to correct existing algorithms, but also conditions for improving their run times. Nevertheless, the diagnosis of multiple observations raises a number of important computational challenges, which even the corrected algorithms are often unable to cope with. As a result, the paper devises a novel algorithm for diagnosing multiple observations, which is shown to enable significant performance improvements in practice.","doi":"10.24963/ijcai.2019/155","url":"https://ijcai.org/proceedings/2019/155","pdf":"https://ijcai.org/proceedings/2019/0155.pdf","markdown":"https://ijcai.org/proceedings/2019/155.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/155","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Constraints and SAT","track":"Main track","number":155,"pages":{"first":1108,"last":1115},"keywords":["Heuristic Search and Game Playing: Combinatorial Search and Optimisation","Constraints and SAT: SAT: Applications","Knowledge Representation and Reasoning: Diagnosis and Abductive Reasoning","Constraints and SAT: MaxSAT, MinSAT"],"videos":[],"references":[{"position":1,"raw":"[Ardissono et al., 2005] L. 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