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Record W1974238428 · doi:10.1076/csed.11.1.73.3841

Software Engineering as a Professional Discipline

2001· article· en· W1974238428 on OpenAlexfundno aff
Donald J. Bagert, Nancy R. Mead

Bibliographic record

VenueComputer Science Education · 2001
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Techniques and Practices
Canadian institutionsnot available
FundersCompute Canada
KeywordsAccreditationCertificationSoftware engineering professionalismComputer scienceEngineering ethicsSocial software engineeringProfessional certification (computer technology)Field (mathematics)Software engineeringSoftwareFocus (optics)Engineering managementSoftware Engineering Process GroupSoftware peer reviewSoftware developmentProfessional developmentSoftware constructionProfessional studiesPolitical scienceEngineeringSociologyPedagogy

Abstract

fetched live from OpenAlex

In this paper we discuss some of the aspects of software engineering as a professional discipline. After a brief discussion of software engineering as a profession, we focus on accreditation, licensing, and certification. We examine historic trends, current status, and the future outlook in each of these areas. We anticipate that this will continue to be an area that sparks professional interest and debate, as the field of software engineering matures.

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)0.009
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.011
Scholarly communication0.0090.007
Open science0.0010.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0050.002

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 head0.011
GPT teacher head0.298
Teacher spread0.287 · 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
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

Citations8
Published2001
Admission routes1
Has abstractyes

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