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Record W1809117658 · doi:10.1002/smr.1718

A systematic review of distributed Agile software engineering

2015· review· en· W1809117658 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Software Evolution and Process · 2015
Typereview
Languageen
FieldComputer Science
TopicSoftware Engineering Techniques and Practices
Canadian institutionsToronto Metropolitan UniversityAthabasca University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAgile software developmentTimelineSystematic reviewComputer scienceWork (physics)Agile Unified ProcessSoftwareKnowledge managementSoftware developmentProcess managementEngineering managementData scienceRisk analysis (engineering)Software engineeringSoftware development processEngineeringBusinessPolitical science

Abstract

fetched live from OpenAlex

Abstract The combination of Agile methods and distributed software development via remote teams represents an emerging approach to address the challenges such as late feedback, slow project timelines, and high cost, typically associated with software development projects. However, when projects are implemented using an Agile model with distributed human resources, there are a number of challenges that need to be considered and mitigated. The objectives of our work are multifold. First, we would like to understand the reasons and conditions that lead to the adoption of distributed Agile software engineering (DASE) practices. Second, we would like to investigate and find out the most important risks that threaten a DASE approach and what mitigation strategies exist to address them. Finally, we would like to highlight which of the available approaches among the existing Agile methodologies has been successfully adopted by the community. We intend to solidify our findings by exploring the strength of the evidence that has been reported in the literature. We carried out a systematic literature review of DASE techniques and approaches. This systematic literature review found time zone difference, knowledge of resources, lack of infrastructure, missing roles, and responsibilities as being the primary challenges that needed to be addressed. Copyright © 2015 John Wiley & Sons, Ltd.

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)0.002
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.404
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.022
GPT teacher head0.311
Teacher spread0.289 · 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