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Record W2126443595 · doi:10.1109/ccece.2004.1347573

On the extension of SystemC by SystemVerilog assertions

2004· article· en· W2126443595 on OpenAlexaff
A. Habibi, Sofiène Tahar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicEmbedded Systems Design Techniques
Canadian institutionsConcordia University
Fundersnot available
KeywordsSystemCComputer scienceVerilogProgramming languageAssertionHardware description languageAbstractionExtension (predicate logic)Computer architectureEmbedded systemField-programmable gate array

Abstract

fetched live from OpenAlex

In this paper, we present an extension to the SystemC library by SystemVerilog assertions. SystemC is an emerging system level design and verification language based on C++ object oriented paradigms. It enables the modelling and simulation of a complete system-on-a-chip. We propose to extend the SystemC library with assertion based verification (ABV) which is a higher abstraction mechanism that allows a concise capturing of design specification. In order to do so, we consider the same ABV structure as defined for the SystemVerilog language. We propose to add ABV as SystemC monitors on top of the original design. Doing so, an important goal is achieved, namely a unified language which brings together enhanced design and assertion features that deliver increased designer productivity and smarter verification. In the same time, considering SystemVerilog's standard assertions will take advantage from the result of an industry-wide effort to extend the Verilog language to include enhanced modelling and verification features.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.006
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.004
Open science0.0020.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.003

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 head0.018
GPT teacher head0.242
Teacher spread0.224 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations21
Published2004
Admission routes1
Has abstractyes

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