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Record W2772423550 · doi:10.1109/iemcon.2017.8117128

Comparison between traditional plan-based and agile software processes according to team size & project domain (A systematic literature review)

2017· article· en· W2772423550 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Techniques and Practices
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsAgile software developmentComputer scienceSoftware development processSoftware project managementProcess managementTeam software processSoftware developmentScrumDomain (mathematical analysis)Software engineeringPlan (archaeology)Project managementProject teamLean software developmentAgile Unified ProcessBest practiceSoftwareKnowledge managementSystems engineeringEngineeringSoftware construction

Abstract

fetched live from OpenAlex

Background: Agile Software development is becoming the most preferred approach for the process of software development. Since the traditional plan-based methods are rigorous and not flexible with changing requirements, some projects are postponed, go over budget, and are sometimes canceled or started from scratch. Questions remain on whether the traditional plan-based approaches will be replaced by agile. For effective, flexible and high-quality projects, organizations are shifting to flexible methods, where they can change the requirements at any stage of the development process. The purpose of this paper is to compare the plan-based and agile software development processes. The paper will discuss the art of deciding which methodology should be used with regard to the team size and the project domain. In the paper a systematic literature review covers 26 papers between 2000 and 2016. The papers are selected with reference to the size of the team and the domain of the project. The result of the paper illustrate that each methodology has a specific area which it best fits in. An organization should consider all factors and choose the methodology according to the situation. Finally, Agile best fits with small team sizes, for exploratory, and software & web-based projects. Traditional methods best fit large team sizes, for predictable, and reusable artifacts projects. However, they can co-exist.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.211
Threshold uncertainty score0.948

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.071
GPT teacher head0.341
Teacher spread0.270 · 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