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Record W2115513993 · doi:10.1109/wcre.2011.26

Useful, But Usable? Factors Affecting the Usability of APIs

2011· article· en· W2115513993 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 Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsUsabilityComputer sciencePluralistic walkthroughUSableCognitive walkthroughUsability inspectionUsability engineeringUsability labUsability goalsWorld Wide WebWeb usabilityQuality (philosophy)Heuristic evaluationSoftware engineeringHuman–computer interaction

Abstract

fetched live from OpenAlex

Software development today has been largely dependent on the use of API libraries, frameworks, and reusable components. However, the API usability issues often increase the development cost (e.g., time, effort) and lower code quality. In this regard, we study 1,513 bug-posts across five different bug repositories, using both qualitative and quantitative analysis. We identify the API usability issues that are reflected in the bug-posts from the API users, and distinguish relative significance of the usability factors. Moreover, from the lessons learned by manual investigation of the bug-posts, we provide further insight into the most frequent API usability issues.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.182
Threshold uncertainty score0.211

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.065
GPT teacher head0.263
Teacher spread0.197 · 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

Quick stats

Citations78
Published2011
Admission routes1
Has abstractyes

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