MétaCan
Menu
Back to cohort
Record W2163109394 · doi:10.1109/tns.2004.839110

Software detection mechanisms providing full coverage against single bit-flip faults

2004· article· en· W2163109394 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Nuclear Science · 2004
Typearticle
Languageen
FieldEngineering
TopicRadiation Effects in Electronics
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsComputer scienceBenchmark (surveying)Transient (computer programming)MicroprocessorFault injectionFault detection and isolationEmbedded systemSoftwareSet (abstract data type)Error detection and correctionFault toleranceReliability engineeringComputer engineeringComputer hardwareAlgorithmDistributed computingOperating systemEngineering

Abstract

fetched live from OpenAlex

Increasing design complexity for current and future generations of microelectronic technologies leads to an increased sensitivity to transient bit-flip errors. These errors can cause unpredictable behaviors and corrupt data integrity and system availability. This work proposes new solutions to detect all classes of faults, including those that escape conventional software detection mechanisms, allowing full protection against transient bit-flip errors. The proposed solutions, particularly well suited for low-cost safety-critical microprocessor-based applications, have been validated through exhaustive fault injection experiments performed on a set of real and synthetic benchmark programs. The fault model taken into consideration was single bit-flip errors corrupting memory cells accessible to the user by means of the processor instruction set. The obtained results demonstrate the effectiveness of the proposed solutions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.585
Threshold uncertainty score0.861

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.190
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it