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Record W2133339195 · doi:10.1109/vlhcc.2008.4639063

Towards the next generation of bug tracking systems

2008· article· en· W2133339195 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

VenueProceedings/Proceedings -- IEEE Symposium on Visual Languages and Human-Centric Computing · 2008
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordssortComputer scienceEclipseCard sortingSoftware bugTracking systemWorld Wide WebTracking (education)Data scienceComputer securityDatabaseSoftwareOperating systemEngineering

Abstract

fetched live from OpenAlex

Developers typically rely on the information submitted by end-users to resolve bugs. We conducted a survey on information needs and commonly faced problems with bug reporting among several hundred developers and users of the APACHE, ECLIPSE and MOZILLA projects. In this paper, we present the results of a card sort on the 175 comments sent back to us by the responders of the survey. The card sort revealed several hurdles involved in reporting and resolving bugs, which we present in a collection of recommendations for the design of new bug tracking systems. Such systems could provide contextual assistance, reminders to add information, and most important, assistance to collect and report crucial information to developers.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.795
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.069
GPT teacher head0.317
Teacher spread0.248 · 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