An updated software reliability model using the shanker model and failure data
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F24%3A10255614" target="_blank" >RIV/61989100:27740/24:10255614 - isvavai.cz</a>
Výsledek na webu
<a href="https://onlinelibrary.wiley.com/doi/10.1002/qre.3512" target="_blank" >https://onlinelibrary.wiley.com/doi/10.1002/qre.3512</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1002/qre.3512" target="_blank" >10.1002/qre.3512</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
An updated software reliability model using the shanker model and failure data
Popis výsledku v původním jazyce
Software developers' goal is to develop reliable and superior software. Due to the fact that software errors frequently generate large societal or financial losses, software reliability is essential. Software reliability growth models are a widely used technique for software reliability assessment. This study examines various nonhomogeneous Poisson process models with the newly developed software reliability distribution and evaluates the unknown model parameters based on frequentist and Bayesian methods of estimation. Finally, we conduct evaluations on real datasets using a variety of evaluation criteria to compare the results of previous software reliability growth models and show how the proposed model may be applied under both approaches in a practical setting. According to this study, the innovative model's mean square error, R2, (Formula presented.), bias, predicted relative variation, Theil statistic, and mean error of prediction values show the lowest values under the Bayesian approach for data sets II to IV, and both approaches perform well for data set I. These implementation findings demonstrate the effectiveness of our specific approach based on our examination of failure data. (C) 2024 John Wiley & Sons Ltd.
Název v anglickém jazyce
An updated software reliability model using the shanker model and failure data
Popis výsledku anglicky
Software developers' goal is to develop reliable and superior software. Due to the fact that software errors frequently generate large societal or financial losses, software reliability is essential. Software reliability growth models are a widely used technique for software reliability assessment. This study examines various nonhomogeneous Poisson process models with the newly developed software reliability distribution and evaluates the unknown model parameters based on frequentist and Bayesian methods of estimation. Finally, we conduct evaluations on real datasets using a variety of evaluation criteria to compare the results of previous software reliability growth models and show how the proposed model may be applied under both approaches in a practical setting. According to this study, the innovative model's mean square error, R2, (Formula presented.), bias, predicted relative variation, Theil statistic, and mean error of prediction values show the lowest values under the Bayesian approach for data sets II to IV, and both approaches perform well for data set I. These implementation findings demonstrate the effectiveness of our specific approach based on our examination of failure data. (C) 2024 John Wiley & Sons Ltd.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
10102 - Applied mathematics
Návaznosti výsledku
Projekt
—
Návaznosti
O - Projekt operacniho programu
Ostatní
Rok uplatnění
2024
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Quality and Reliability Engineering International
ISSN
0748-8017
e-ISSN
—
Svazek periodika
40
Číslo periodika v rámci svazku
4
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
17
Strana od-do
2078-2095
Kód UT WoS článku
001173266000001
EID výsledku v databázi Scopus
2-s2.0-85186912751