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Record W2049047048 · doi:10.1145/376134.376180

More testing should be taught

2001· article· en· W2049047048 on OpenAlexaff
Terry Shepard, Margaret Lamb, Diane Kelly

Bibliographic record

VenueCommunications of the ACM · 2001
Typearticle
Languageen
FieldComputer Science
TopicDistributed and Parallel Computing Systems
Canadian institutionsQueen's UniversityRoyal Military College of Canada
Fundersnot available
KeywordsQueen (butterfly)CitationLibrary scienceEngine departmentOperations researchHistoryComputer scienceEngineeringEngineering management

Abstract

fetched live from OpenAlex

Recommends the improvement of teaching of testing to students of software development. Statement that testing typically takes 50 percent or more of the resources for software development projects; Teaching of Verification and Validation (V&V) techniques; Testing in an undergraduate software engineering specialization; Testing in a graduate course on V&V; Suggestions for improvements.

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)0.005
metaresearch head score (Gemma)0.033
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.079
Threshold uncertainty score0.264

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.005
Open science0.0020.002
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0790.042

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 head0.187
GPT teacher head0.343
Teacher spread0.156 · 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
GenreCommentary

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

Citations86
Published2001
Admission routes1
Has abstractyes

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Same venueCommunications of the ACMSame topicDistributed and Parallel Computing SystemsFrench-language works237,207