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Record W2164059708 · doi:10.1109/wse.2005.11

REGoLive: Building a Web Site Comprehension Tool by Extending GoLive

2005· article· en· W2164059708 on OpenAlexaff
G. Gui, Holger M. Kienle, Hausi Müller

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Research
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsProgram comprehensionComputer scienceComprehensionClass hierarchySoftware engineeringWorld Wide WebSoftwareCompilerHuman–computer interactionProgramming languageSoftware systemObject-oriented programming

Abstract

fetched live from OpenAlex

Traditionally, program comprehension functionality is implemented with stand-alone tools. As a result, software engineers typically have to switch between various tools during comprehension activities. Each of these tools has its own idiosyncratic user interface and interaction paradigm, causing an unfavorable learning curve. As a result, many program comprehension tools fail to be adopted. Software engineering activities that involve program comprehension (e.g., maintenance) require the use of forward engineering tools (e.g., compilers) as well as reverse engineering tools (e.g., class hierarchy visualizers). Thus, extending forward engineering tools such as IDEs (e.g., Eclipse) or Web authoring tools (e.g., GoLive) by seamlessly adding program comprehension functionality helps software engineers and improves the adoption of comprehension functionality. In this paper, we introduce an adoption-centric tool development approach that leverages a Web authoring tool, GoLive, by grafting functionality for Web site comprehension on top. The benefits and drawbacks of this approach from the tool-user's as well as the tool-builder's perspective are discussed.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.819
Threshold uncertainty score0.587

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.011
GPT teacher head0.270
Teacher spread0.259 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations6
Published2005
Admission routes1
Has abstractyes

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