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Record W2127127923 · doi:10.1109/ccece.2004.1349698

Exploring Java code generation based on formal specifications in RTPA

2004· article· en· W2127127923 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
TopicCognitive Computing and Networks
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsComputer scienceFormal specificationJavaProgramming languageFormal methodsSoftware engineeringCode generationCode (set theory)Operating systemKey (lock)Set (abstract data type)

Abstract

fetched live from OpenAlex

The use of formal specification techniques in developing large-scale software is considered as a necessary approach towards the implementation of efficient and reliable software systems. Barriers to the widespread adoption of formal methods in system development are attributed to the fact that many formal methods work only at the specification phase and it is still necessary to implement the code manually when specifications are ready. This paper explores the transformability between system specifications in real-time process algebra (RTPA) and code in Java. Automatic Java code generation on the basis of formal specifications in RTPA not only drastically reduce the effort and time spent in interpreting and translating the specifications by programmers, but also significantly improve the quality of code. Case studies on a number of real-world projects have shown the feasibility and efficiency of RTPA-based code generation methodology.

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)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.869
Threshold uncertainty score0.273

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 communication0.0000.000
Open science0.0000.000
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 head0.303
GPT teacher head0.274
Teacher spread0.029 · 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

Citations7
Published2004
Admission routes1
Has abstractyes

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