MétaCan
Menu
Back to cohort
Record W4242581305 · doi:10.1109/icse.2015.83

Why Good Developers Write Bad Code: An Observational Case Study of the Impacts of Organizational Factors on Software Quality

2015· article· en· W4242581305 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

Venue2015 IEEE/ACM 37th IEEE International Conference on Software Engineering · 2015
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Techniques and Practices
Canadian institutionsPolytechnique Montréal
FundersDivision of Civil, Mechanical and Manufacturing Innovation
KeywordsSoftware qualityQuality (philosophy)SoftwareComputer scienceObservational studyAction (physics)Knowledge managementSoftware developmentProcess managementBusiness

Abstract

fetched live from OpenAlex

How can organizational factors such as structure and culture have an impact on the working conditions of developers? This study is based on ten months of observation of an in-house software development project within a large telecommunications company. The observation was conducted during mandatory weekly status meetings, where technical and managerial issues were raised and discussed. Preliminary results show that many decisions made under the pressure of certain organizational factors negatively affected software quality. This paper describes cases depicting the complexity of organizational factors and reports on ten issues that have had a negative impact on quality, followed by suggested avenues for corrective action.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-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 score0.259
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.202
GPT teacher head0.377
Teacher spread0.175 · 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