Evaluating Surprise Adequacy for Deep Learning System Testing.
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| Title: | Evaluating Surprise Adequacy for Deep Learning System Testing. |
|---|---|
| Authors: | JINHAN KIM1, jinhankim@kaist.ac.kr, FELDT, ROBERT2, shin.yoo@kaist.ac.kr, SHIN YOO1, robert.feldt@chalmers.se |
| Source: | ACM Transactions on Software Engineering & Methodology; Mar2023, Vol. 32 Issue 2, p1-29, 29p |
| Database: | Applied Science & Technology Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 163051926 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=163051926 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1145/3546947 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 29 StartPage: 1 Titles: – TitleFull: Evaluating Surprise Adequacy for Deep Learning System Testing. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: JINHAN KIM – PersonEntity: Name: NameFull: FELDT, ROBERT – PersonEntity: Name: NameFull: SHIN YOO IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2023 Type: published Y: 2023 Identifiers: – Type: issn-print Value: 1049331X Numbering: – Type: volume Value: 32 – Type: issue Value: 2 Titles: – TitleFull: ACM Transactions on Software Engineering & Methodology Type: main |
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