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Record W4210866930 · doi:10.36227/techrxiv.12094230

Spring Framework for Testing

2020· preprint· en· W4210866930 on OpenAlexaff
Darshak Mota, Neel Zadafiya, Jinan Fiaidhi

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldComputer Science
TopicSoftware System Performance and Reliability
Canadian institutionsLakehead University
Fundersnot available
KeywordsComputer scienceJavaSoftware engineeringSystems development life cycleWeb applicationModel–view–controllerJava annotationProgramming languageTest caseWeb application developmentOperating systemReal time JavaSoftwareSoftware developmentSoftware development processWeb serviceWeb developmentUser interface

Abstract

fetched live from OpenAlex

Java Spring is an application development framework for enterprise Java. It is an open source platform which is used to develop robust Java application easily. Spring can also be performed using MVC structure. The MVC architecture is based on Model View and Controller techniques, where the project structure or code is divided into three parts or sections which helps to categorize the code files and other files in an organized form. Model, View and Controller code are interrelated and often passes and fetches information from each other without having to put all code in a single file which can make testing the program easy. Testing the application while and after development is an integral part of the Software Development Life Cycle (SDLC). Different techniques have been used to test the web application which is developed using Java Spring MVC architecture. And compares the results among all the three different techniques used to test the web application.

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)0.006
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Software · Consensus signal: none
Teacher disagreement score0.048
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.011
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0030.002
Science and technology studies0.0010.002
Scholarly communication0.0040.003
Open science0.0060.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0480.022

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 head0.084
GPT teacher head0.309
Teacher spread0.225 · 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 designNot applicable
Domainnot available
GenreSoftware

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".

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Citations1
Published2020
Admission routes1
Has abstractyes

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