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Record W965529893

Application of model-based approach for testing dynamic systems

2011· article· pl· W965529893 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAutomatyka / Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie · 2011
Typearticle
Languagepl
FieldComputer Science
TopicSoftware Testing and Debugging Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsSoftwareFiscal yearComputer scienceAeronauticsComputer securityEngineeringReliability engineeringOperations researchBusinessOperating system
DOInot available

Abstract

fetched live from OpenAlex

In today’s world, systems that contain software are everywhere. They may be observed in common devices employed in everyday living (e.g., coffee machines, washing machines, cell phones) as well as in sophisticated engineering systems (e.g., cars, planes, spacecrafts). As the complexity of control systems grows, testing becomes more and time consuming. Poorly tested systems may cost producers billions of dollars annually especially when defects are found by end users in production environments. Barry Boehm’s research analysis [5] indicates that the cost of removing a software defect grows exponentially for each stage of the development life cycle in which it remains undiscovered. Boris Beizer [2] estimates that 30 up to 90 percentage of the effort in put into testing. Another research project conducted by the United States Department of Commerce, National Institute of Standards and Technology [21] estimated that software defects cost the U.S. economy $60 billion per year. There are several facts that show clearly possible consequences of poorly tested systems. On February 25, 1991, an Iraqi Scud hit the barracks in Dhahran in Saudi Arabia, killing 28 soldiers from the US Army. This accident was caused by software error in the system’s clock [20]. The Patriot missile battery has been in operation for 100 hours, by which time the system’s internal clock had drifted by one third of a second. For a target moving as fast as Scud, this was equivalent to a position error of 600 meters. Another example is connected with Therac-25 radiation therapy machine that was produced by Atomic Energy of Canada Limited and CGR of France. The machine was involved with at least six known accidents between 1985 and 1987, in which patients were given massive overdoses of radiation, which were in some cases on the order of hundreds of grays [13]. At least five patients died of the overdoses. These accidents were caused by errors in software control application. One of the most infamous computer bugs in history was found during flight 501 that took place on June 4, 1996. This was the first, and unsuccessful, test flight of the European Ariane 5 expendable lunch system. Due to an error in the software design (inadequate protection from integer

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.702
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0050.001
Research integrity0.0010.001
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 head0.073
GPT teacher head0.296
Teacher spread0.223 · 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