Towards a Robust Quality Assurance Framework for Cloud Computing Environments

Trends such as cloud computing raise issues regarding stable and uniform quality assurance (QA) and validation of software requirements. Current QA frameworks are poorly defined, often not automated, and lack the flexibility needed for on-demand, cloud-based environments. These gaps lead to inconsistencies in service delivery, challenges in scaling organizational capacity, and internal and external inefficiencies that affect the reliability and effectiveness of cloud services. This paper presents a detailed framework for QA in cloud computing systems and advocates for standardized, automated, and adaptable systems to address these challenges. It aims to establish generic QA policies, incorporate intelligent techniques to enhance extendibility, and create adaptive solutions to manage the inherent attributes of cloud computing environments. The proposed framework is evaluated through survey questionnaires from industry practitioners, and descriptive statistics summarize the results. The study demonstrates the promise, effectiveness, and potential applicability of integrating a single QA framework to enhance the software’s functionality, dependability, and future adaptability in cloud computing systems.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-01-26
DOI
https://doi.org/10.5281/zenodo.14929516
Primary Topic
Software System Performance and Reliability
Type
article
Field-Weighted Citation Impact
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article

Towards a Robust Quality Assurance Framework for Cloud Computing Environments

Zenodo (CERN European Organization for Nuclear Research)
Software System Performance and Reliability
article

Towards a Robust Quality Assurance Framework for Cloud Computing Environments

article en

Abstract

Trends such as cloud computing raise issues regarding stable and uniform quality assurance (QA) and validation of software requirements. Current QA frameworks are poorly defined, often not automated, and lack the flexibility needed for on-demand, cloud-based environments. These gaps lead to inconsistencies in service delivery, challenges in scaling organizational capacity, and internal and external inefficiencies that affect the reliability and effectiveness of cloud services. This paper presents a detailed framework for QA in cloud computing systems and advocates for standardized, automated, and adaptable systems to address these challenges. It aims to establish generic QA policies, incorporate intelligent techniques to enhance extendibility, and create adaptive solutions to manage the inherent attributes of cloud computing environments. The proposed framework is evaluated through survey questionnaires from industry practitioners, and descriptive statistics summarize the results. The study demonstrates the promise, effectiveness, and potential applicability of integrating a single QA framework to enhance the software’s functionality, dependability, and future adaptability in cloud computing systems.

Zenodo (CERN European Organization for Nuclear Research)
Russian Academy of Advocacy and Notaries (RU)
Industry, innovation and infrastructure
Openalex Percentile: Top 53%
Software System Performance and Reliability
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