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Record W7112709870

ВИКОРИСТАННЯ АГРЕГОВАНИХ КРИТЕРІЇВ ДЛЯ ОЦІНКИ ЯКОСТІ ТЕСТІВ ПРОГРАМНОГО ЗАБЕЗПЕЧЕННЯ

2024· article· en· W7112709870 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

VenueThe Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogy · 2024
Typearticle
Languageen
FieldComputer Science
TopicStatistical and Computational Modeling
Canadian institutionsCollège Montmorency
Fundersnot available
KeywordsSoftwareSoftware qualitySet (abstract data type)Quality (philosophy)Software metricSelection (genetic algorithm)Software system
DOInot available

Abstract

fetched live from OpenAlex

An approach to evaluating the software tests quality using aggregated quality criteria is proposed. The article considers the finding of such characteristics of software tests that can be used to judge their quality and their need for improvement. The subject of the study is the formation of a software tests quality evaluation system, which can be used in the software development process. It is proposed to consider a software test as a multiattribute object. It is emphasized that it is necessary to take into account both quantitative and qualitative characteristics of tests and test coverage, which greatly complicates the construction of a model for evaluating the software tests quality. Various approaches to solving the problem of evaluating complex, multiattribute objects are considered. The problem of comparing and ordering complex objects taking into account different criteria is considered. The choice of the method of sequential aggregation of classified states to solve the problem of multi-criteria selection and assessment is justified. The stages of the procedure for solving the estimation problem using the method of sequential aggregation of classified states are considered. An activity diagram is constructed that reflects an algorithm for constructing a hierarchical system of criteria. The criteria for evaluating software tests are given, which belong to three groups - efficiency, coverage, and software implementation. For a hierarchical system of criteria aggregation, a set of indicators, their qualitative gradations with corresponding numerical intervals, are allocated. At the highest level of the hierarchy, it is proposed to use three composite criteria that correspond to the groups of efficiency, coverage and implementation, which will allow to obtain an integral indicator of the software tests quality. The resulting integral indicator includes five quality classes, each of which corresponds to a multitude of low-level indicator estimates. Tests quality evaluation will improve the testing process, which purpose is to ensure the specified quality of the software being developed.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.742
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0030.001
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 head0.077
GPT teacher head0.344
Teacher spread0.268 · 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