Optimizing Testing-Resource Allocation Using Architecture-Based Software Reliability Model

المؤلفون المشاركون

Dohi, Tadashi
Okamura, Hiroyuki

المصدر

Journal of Optimization

العدد

المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-7، 7ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2018-09-27

دولة النشر

مصر

عدد الصفحات

7

التخصصات الرئيسية

الرياضيات

الملخص EN

In the management of software testing, testing-recourse allocation is one of the most important problems due to the tradeoff between development cost and reliability of released software.

This paper presents the model-based approach to design the testing-resource allocation.

In particular, we employ the architecture-based software reliability model with operational profile to estimate the quantitative software reliability in operation phase and formulate the multiobjective optimization problems with respect to cost, testing effort, and software reliability.

In numerical experiment, we investigate the difference of the presented optimization problem from the existing testing-resource allocation model.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Okamura, Hiroyuki& Dohi, Tadashi. 2018. Optimizing Testing-Resource Allocation Using Architecture-Based Software Reliability Model. Journal of Optimization،Vol. 2018, no. 2018, pp.1-7.
https://search.emarefa.net/detail/BIM-1197284

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Okamura, Hiroyuki& Dohi, Tadashi. Optimizing Testing-Resource Allocation Using Architecture-Based Software Reliability Model. Journal of Optimization No. 2018 (2018), pp.1-7.
https://search.emarefa.net/detail/BIM-1197284

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Okamura, Hiroyuki& Dohi, Tadashi. Optimizing Testing-Resource Allocation Using Architecture-Based Software Reliability Model. Journal of Optimization. 2018. Vol. 2018, no. 2018, pp.1-7.
https://search.emarefa.net/detail/BIM-1197284

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1197284