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RemembERR

Tool
First seen 7/26/2026
Last seen 7/26/2026
Evidence 7 chunks

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RELATIONSHIPS

13 connections
RemembERR: Leveraging Microprocessor Errata for Design Testing and Validation ← introduces 100% 2e
The paper introduces RemembERR as a new large-scale database of microprocessor errata.
errata classification scheme uses → 95% 2e
RemembERR uses the errata classification scheme to annotate entries at multiple abstraction levels.
triggers uses → 95% 2e
RemembERR annotates each entry with triggers extracted from errata.
contexts uses → 95% 2e
RemembERR annotates each entry with contexts extracted from errata.
observable effects uses → 95% 2e
RemembERR annotates each entry with observable effects extracted from errata.
concrete classification level uses → 95% 2e
RemembERR classifies entries at the concrete level to capture exact actions from errata.
abstract classification level uses → 95% 2e
RemembERR classifies entries at the abstract level to generalize triggers, contexts, and effects.
four-eyes manual classification uses → 95% 2e
RemembERR was built using four-eyes manual classification for errata that could not be classified automatically.
software-assisted classification uses → 90% 2e
RemembERR uses software-assisted classification to reduce manual workload.
design testing and validation part of → 85% 1e
RemembERR is created to guide design testing and validation.
regular expression filtering uses → 90% 1e
RemembERR uses regular expression filtering to automatically classify certain errata categories.
class classification level uses → 95% 1e
RemembERR classifies entries at the class level, the highest level of abstraction.
syntax highlighting engine uses → 90% 1e
RemembERR uses a syntax highlighting engine to assist human classifiers.