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Record W1994492702 · doi:10.1145/1022494.1022542

Continuous evolutionary one-step-ahead testing

2004· article· en· W1994492702 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueACM SIGSOFT Software Engineering Notes · 2004
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Research
Canadian institutionsWestern UniversityUniversity of Waterloo
Fundersnot available
KeywordsVendorComputer scienceSoftware engineeringSoftware release life cycleSoftwareSoftware developmentBackportingReliability engineeringSoftware reliability testingSoftware constructionEngineeringOperating systemBusiness

Abstract

fetched live from OpenAlex

The traditional software development life cycle considers testing to be an activity that occurs between the implementation phase of development and software release [4]. With this approach any testing subsequent to release is done in reaction to failures reported by software users. The realities of software in operation however causes questions about this approach to arise. Adams [1] showed that organizations developing significant software applications often provide several fixes after their software has been released as the result of errors found in the field. This work also showed that the most serious and frequently recurring errors are usually found by users soon after a product has been released. These are referred to by Adams [1] as virulent errors. The negative effects of remaining defects implies that post-release activities should be proactive. These post-release activities must include continued testing by the vendor to find errors even after release. This paper proposes a solution to this requirement.

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)0.000
metaresearch head score (Gemma)0.378
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.377
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.378
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0030.001
Research integrity0.0000.001
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 head0.029
GPT teacher head0.248
Teacher spread0.219 · 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