MétaCan
Menu
Back to cohort
Record W2594649443

Microservices in the modern software world

2016· article· en· W2594649443 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

VenueComputer Science and Software Engineering · 2016
Typearticle
Languageen
FieldComputer Science
TopicSoftware System Performance and Reliability
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMicroservicesComputer scienceSoftware architectureSoftware engineeringService-oriented architectureFlexibility (engineering)ScalabilityResource-oriented architectureArchitectural styleArchitectureSoftwareSoftware developmentReference architectureComputer architectureOperating systemComponent-based software engineeringWorld Wide WebWeb serviceCloud computing
DOInot available

Abstract

fetched live from OpenAlex

In today's fast-paced markets, frequently changing requirements are asking for innovative software architecture styles that accommodate application scalability, development flexibility and adaptivity to change. The most recent trends that have caught the attention of many organizations is the microservices architecture that supersedes plain old service-oriented architectures (SOA) as well as the monolithic software architecture. Many organizations have begun transforming their traditional monolithic software systems, in which the entire application's functionality is bundled within a single process, to microservices architectures, where an application's functionality is broken into a small set of services, each running independently, often flexibly deployed in a virtualized environment. From the user's perspective, the interaction with the system remains the same, however, the microservices architecture style brings forth numerous benefits compared to a monolithically styled architecture.

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)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.879
Threshold uncertainty score0.427

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0020.001
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 head0.008
GPT teacher head0.203
Teacher spread0.196 · 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