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Record W4252445205 · doi:10.21236/ada611617

Proceedings of the Fourth International Workshop on a Research Agenda for Maintenance and Evolution of Service-Oriented Systems (MESOA 2010)

2011· report· en· W4252445205 on OpenAlexfundno aff
Grace A. Lewis, Dennis B. Smith, Kostas Kontogiannis

Bibliographic record

Venuenot available
Typereport
Languageen
FieldComputer Science
TopicService-Oriented Architecture and Web Services
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversidad ICESICA TechnologiesInternational Business Machines Corporation
KeywordsService (business)Engineering managementLibrary scienceRegional sciencePolitical scienceEngineeringComputer scienceBusinessGeographyMarketing

Abstract

fetched live from OpenAlex

The Fourth International Workshop on Maintenance and Evolution of Service-Oriented Systems (MESOA 2010), organized by members of the Carnegie Mellon Software Engineering Institute's technical staff, was held at the 26th International Conference on Software Maintenance (ICSM 2010) in Timisoara, Romania, on September 17, 2010. The goal for MESOA 2010 was to share current research efforts and discuss emerging technologies in the maintenance and evolution of service-oriented systems. A second goal of the workshop was to identify areas of future work needed to address existing gaps and problems in the taxonomy of research topics in service-oriented architecture (SOA). This report summarizes the workshop and includes the accepted papers that were the basis for the presentations given during the workshop. Topics include using simulation models to evolve business processes, a requirements-driven framework for root cause analysis in SOA environments, SOA integration as an alternative to source migration, proactive adaptation as illustrated by the S-Cube service life cycle, a dynamic framework for quality web-service discovery, a characterization of policies that govern SOAs, and context-driven adaptive monitoring for supporting SOA governance. The report concludes with highlights from the discussions among workshop attendees.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.827
Threshold uncertainty score0.875

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.001
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 head0.078
GPT teacher head0.318
Teacher spread0.240 · 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 designNot applicable
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

Citations4
Published2011
Admission routes1
Has abstractyes

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