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Record W2168462212 · doi:10.1145/2382756.2382786

Issue ownership activity in two large software projects

2012· article· en· W2168462212 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

VenueACM SIGSOFT Software Engineering Notes · 2012
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Research
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsSoftware developmentWorkloadSoftware project managementComputer scienceProduct (mathematics)SoftwareSoftware qualityProcess managementRisk analysis (engineering)Software engineeringBusinessSoftware construction

Abstract

fetched live from OpenAlex

Issue management is one of the major challenges of software development teams. Balanced workload allocation of developers who are responsible for the maintenance of the software product would impact the long-term reliability of the product. In this paper, we analyse the issue report, issue ownership, and issue resolve patterns of two large software products over a period of time. We use GINI index to estimate the inequalities in issue ownership over time. Our results indicate that a small group of developers tends to take the ownership of a large portion of new issues especially when the active issue count is relatively high in the software development life cycle. We discuss the implications of this trend and propose long-term issue management strategies to deal with them.

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)0.274
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.272
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.274
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0030.001
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 head0.031
GPT teacher head0.294
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