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Separating Users' Views in a Development Process for Agile Methods

2009· article· en· W2146309717 on OpenAlexaff
Ammar Bessam, Mohamed Tahar Kimour, Ali Melit

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Techniques and Practices
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsAgile software developmentComputer scienceClass diagramProcess (computing)Unified Modeling LanguageSoftware engineeringSoftware development processUser storySoftware developmentSoftwareSystems engineeringProgramming languageEngineering

Abstract

fetched live from OpenAlex

Agile methods require a rigorous development process that takes into account a permanent involvement of user in all development steps. Several advanced researches have treated the various aspects of agile development methods. However, they lack rigorous and specific processes based on explicit and detailed definition of userspsila organization and interaction during development process. In this paper, we have suggested an approach that guides software projects managers in assignment of integrated users in development process. The basic definition of this process is based on a set of layers represented by nested circles. Circles from the center to the external surface represent, respectively, initial or starting userspsila requirements, software architecture, design level and codification level. These layers are decomposed into slices from the center to the external circle. Each slice represents a different view that corresponds to a specific class of users. In our process, developers have not constrained by a specific views approach, they can choose the appropriate views approach from the literature (e.g. 4+1 view approach). Initial requirements, in this process, are represented by an extension of use case diagram definition of UML. The proposed process is driven by requirements. It is used for large software systems developed by a numerous and heterogeneous development teams. The developed process is characterized by its simplicity, and it can be easily adapted for other agile processes.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.965
Threshold uncertainty score0.253

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.089
GPT teacher head0.446
Teacher spread0.357 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreMethods

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

Citations3
Published2009
Admission routes1
Has abstractyes

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