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Record W2144383476 · doi:10.5626/jcse.2014.8.1.57

Addressing User Requirements in Open Source Software: The Role of Online Forums

2014· article· en· W2144383476 on OpenAlexaff
Arif Raza, Luiz Fernando Capretz

Bibliographic record

VenueJournal of Computing Science and Engineering · 2014
Typearticle
Languageen
FieldComputer Science
TopicOpen Source Software Innovations
Canadian institutionsWestern University
Fundersnot available
KeywordsComputer sciencePopularityOpen source softwareWorld Wide WebOpen sourceSoftwareUSableUser satisfactionSoftware peer reviewWork (physics)Software developmentHuman–computer interactionSoftware constructionEngineering

Abstract

fetched live from OpenAlex

User satisfaction has always been important in the success of software, regardless of whether it is closed and proprietary or open source software (OSS). OSS users are geographically distributed and include technical as well as novice users. However, it is generally believed that if OSS was more usable, its popularity would increase tremendously. Hence, users and their requirements need to be addressed in the priorities of an OSS environment. Online public forums are a major medium of communication for the OSS community. The research model of this work studies the relationship between user requirements in open source software and online public forums. To conduct this research, we used a dataset consisting of 100 open source software projects in different categories. The results show that online forums play a significant role in identifying user requirements and addressing their requests in open source software.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.106
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.106
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0030.006
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.029
GPT teacher head0.294
Teacher spread0.266 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2014
Admission routes1
Has abstractyes

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