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Record W2072481344 · doi:10.1080/10798587.2014.960229

Perception-Based Software Release Planning

2014· article· en· W2072481344 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

VenueIntelligent Automation & Soft Computing · 2014
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Research
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsComputer sciencePerceptionSoftwareSoftware engineeringHuman–computer interactionProgramming languagePsychology

Abstract

fetched live from OpenAlex

Release planning is a cornerstone of incremental software development. This paper proposes a novel framework that performs the prioritization aspect of the software release-planning process. The aim of this framework is to help software product managers to select the most promising requirements that will be implemented in the next release. Many variables affect release planning, including: The importance of requirements as perceived by the different stakeholders; decision weights of the stakeholders; the risk associated with each requirement as estimated by the development team; the effort needed to implement each requirement; the release size (the effort allocated to implement and deliver a software release); and the dependencies among requirements. We assume that there are no ambiguities in defining the dependencies among requirements. Also it is assumed that the estimation of the available effort is accurate. Because of human perception, such variables as importance, risk, and required effort have a hi...

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.667
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.022
GPT teacher head0.285
Teacher spread0.264 · 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