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Record W2504514184 · doi:10.1109/wcre.1996.558936

A cliche-based environment to support architectural reverse engineering

2002· article· en· W2504514184 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 institutionsPolytechnique Montréal
Fundersnot available
KeywordsComputer scienceSoftware engineeringArchitectural patternArchitectural geometrySoftwareSoftware architectureArchitectural modelArchitectureReverse engineeringSoftware systemSet (abstract data type)ClichéProgramming languageSystems engineeringSoftware constructionEngineering

Abstract

fetched live from OpenAlex

Paper reprinted from ICSM '96. When programmers perform maintenance tasks, program understanding is required. One of the first activities in understanding a software system is identifying its subsystems and their relations, i.e. its software architecture. Since a large part of the effort is spent in creating a mental model of the system under study, tools can help maintainers in managing the evolution of legacy systems, by showing them architectural information. In this paper, an environment for the architectural analysis of software systems is described. The environment is based on a hierarchical architectural model that drives the application of a set of recognizers, each producing a different architectural view of the system or of some of its parts. Recognizers embody knowledge about architectural cliches and use flow analysis techniques to make their output more accurate.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.704
Threshold uncertainty score0.999

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.020
GPT teacher head0.218
Teacher spread0.198 · 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

Citations67
Published2002
Admission routes1
Has abstractyes

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