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Record W4251245562 · doi:10.1002/stvr.396

Transition covering tests for systems with queues

2008· article· en· W4251245562 on OpenAlexaff
Jiale Huo, Alexandre Petrenko

Bibliographic record

VenueSoftware Testing Verification and Reliability · 2008
Typearticle
Languageen
FieldComputer Science
TopicSoftware Testing and Debugging Techniques
Canadian institutionsComputer Research Institute of MontréalNortel (Canada)
Fundersnot available
KeywordsContext (archaeology)Computer scienceQueueMetric (unit)ConcurrencyCover (algebra)Model-based testingTest (biology)Test caseReliability engineeringDistributed computingProgramming languageEngineeringOperations managementMechanical engineering

Abstract

fetched live from OpenAlex

Abstract This paper introduces a method to cover transitions of a concurrent system under test through a context consisting of infinite‐capacity queues. Concurrent systems have many important applications, but they are very difficult and expensive to test. One of the difficulties in testing concurrent systems is caused by the fact that queues in the test context can distort the behaviour of a concurrent system under test and can cause state explosion in test derivation. The proposed method derives transition covering tests directly from the specification of a concurrent system, not its composition with queues. As transition coverage is an important industrial metric of test quality, the results of the paper have practical applications. A case study is presented to illustrate one of the applications. Copyright © 2008 John Wiley & Sons, Ltd.

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)0.002
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.043
GPT teacher head0.260
Teacher spread0.216 · 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 designSimulation or modeling
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

Citations24
Published2008
Admission routes1
Has abstractyes

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