MétaCan
Menu
Back to cohort
Record W6998995058

Can Microservice-Based Online-Retailers be Used as an SPL? A study of six reference architectures

2020· other· en· W6998995058 on OpenAlexfundno aff

Bibliographic record

VenueArchipelago (University of Quebec in Montreal) · 2020
Typeother
Languageen
FieldComputer Science
TopicSoftware System Performance and Reliability
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMicroservicesReuseFeature (linguistics)InterchangeabilitySoftwareSoftware versioningSet (abstract data type)Service (business)Feature model
DOInot available

Abstract

fetched live from OpenAlex

Microservices are deployable software artifacts that combine a set of business features and expose them to other microservices. Ideally, the reuse and interchanging of microservices should be easy as they are supposed to be independent of each other, both conceptually and technologically. Selecting a service to fulfill a given feature (e.g., managing a cart in a website) recalls the way Software Product Lines (SPL) allow variability. However, in practice, interchanging microservices requires knowing the features that the services propose, how they communicate with other services and their types. In this work, we propose to analyze service dependencies as feature dependencies, at the feature, structural, technological, and versioning level, to assess the interchangeability of services. We analyze six community-selected use-cases and report that services are non-interchangeable systematically.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.318
Threshold uncertainty score0.631

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.229
Teacher spread0.210 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueArchipelago (University of Quebec in Montreal)Same topicSoftware System Performance and ReliabilityFrench-language works237,207