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Record W2568073323 · doi:10.1109/iwsm-mensura.2016.036

Evaluating Security in Web Application Design Using Functional and Structural Size Measurements

2016· article· en· W2568073323 on OpenAlexfundno aff
Hela Hakim, Asma Sellami, Hanêne Ben‐Abdallah

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWeb Data Mining and Analysis
Canadian institutionsnot available
FundersÉcole de technologie supérieure
KeywordsComputer science

Abstract

fetched live from OpenAlex

Because of software requirements play a critical role in software development projects, measuring the non-functional requirements as well as functional requirements is therefore not to be trifled with. Software security as a non-functional requirement is one of the most important quality characteristic that is recently added in the ISO 25010 quality models (previously defined as sub characteristics in ISO 9126). This characteristic must be evaluated cautiously and precisely during all the software life-cycle and especially early in the design phase. The purpose of this paper is early evaluating security in web application. To achieve this purpose, we propose to measure the quality attributes of authenticity through a combination of functional and structural size of the authenticity sequence diagram at the design phase. This combination of measurement can be used to identify the risk of violation of authenticity in web application design. An example of GeoNetwork web application is used to illustrate our proposed measurement for evaluating security as defined by ISO/IEC 25010.

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)0.025
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.025
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.158
GPT teacher head0.339
Teacher spread0.181 · 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

Citations6
Published2016
Admission routes1
Has abstractyes

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