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Record W1555024474

An experiment to investigate interacting versus nominal groups in software inspection

2003· article· en· W1555024474 on OpenAlexaff
Diane Kelly, Terry Shepard

Bibliographic record

VenueConference of the Centre for Advanced Studies on Collaborative Research · 2003
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Research
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsFagan inspectionSoftware inspectionComputer scienceContext (archaeology)SoftwarePsychologyArtificial intelligenceSoftware engineeringSoftware qualitySoftware developmentProgramming language
DOInot available

Abstract

fetched live from OpenAlex

Votta's 1993 question, Does Every Inspection Need a Meeting? signaled an examination of an important activity in inspection. Fagan considered meetings to be the primary defect detection activity, but research has generated results that both support and conflict with this. It is generally agreed that a better understanding is needed. Research on group behaviour has motivated Sauer et al to formulate eleven propositions regarding group performance in inspections. These are partially supported by existing research. The research described in this paper addresses the performance of the group versus the performance of the individual in the context of the use of a structured inspection technique. The main conclusion is that most findings eliminated as a result of meetings are subtle findings, while a smaller number added as a result of meetings are findings that are relatively easy to identify.

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 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)0.001
metaresearch head score (Gemma)0.021
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.665
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.131
GPT teacher head0.427
Teacher spread0.296 · 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 teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations5
Published2003
Admission routes1
Has abstractyes

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