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Record W4238850792 · doi:10.1145/1449955.1449786

The impact of static-dynamic coupling on remodularization

2008· article· en· W4238850792 on OpenAlexaff
Rick Chern, Kris De Volder

Bibliographic record

VenueACM SIGPLAN Notices · 2008
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer scienceStatic analysisModular designCoupling (piping)JavaProgramming languageProcess (computing)Point (geometry)Mathematics

Abstract

fetched live from OpenAlex

We explore the concept of static-dynamic coupling --the degree to which changes in a program's static modular structure imply changes to its dynamic structure. This paper investigates the impact of static-dynamic coupling in a programming language on the effort required to evolve the coarse modular structure of programs written in that language. We performed a series of remodularization case studies in both Java and SubjectJ. SubjectJ is designed to be similar to Java, but have strictly less static-dynamic coupling. Our results include quantitative measures-time taken and number of bugs introduced--as well as a more subjective qualitative analysis of the remodularization process. All results point in the same direction and suggest that static-dynamic coupling causes substantial accidental complexity for the remodularization of Java programs.

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)0.002
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score0.245

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.025
GPT teacher head0.304
Teacher spread0.278 · 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

Citations1
Published2008
Admission routes1
Has abstractyes

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