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A review on cloud computing-based quality assurance: Challenges, opportunities, and best practices
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There are many parts of software development and deployment that have been transformed by cloud computing, one of which is quality assurance (QA). The use of cloud computing into quality assurance procedures provides enterprises with numerous benefits, including flexibility, scalability, and efficiency, which in turn enables them to more efficiently guarantee the quality of their software products. The fundamental objective of this study is to determine what components of cloud computing QA are most crucial. More specifically, the research will concentrate on the identification and analysis of key quality parameters. Specifically, the study highlights the distinct quality assurance issues and requirements that are associated with each cloud computing model by analyzing a variety of cloud computing models, such as SaaS, PaaS, and IaaS. Further, the work discusses potential future directions in cloud quality assurance including automation and multi-cloud approaches and how these directions might be applied to improve the quality assurance processes. One more contribution of the study is that it reveals critical challenges that quality assurance teams face when operating in cloud environments and discusses the possibility of enhancement through the use of innovative technologies. In result, a collection of best practices to facilitate efficient quality assurance in cloud environments is provided. The purpose of this set of practices is to optimize quality assurance procedures, reduce costs, and guarantee the delivery of high-quality cloud services.
Title: A review on cloud computing-based quality assurance: Challenges, opportunities, and best practices
Description:
There are many parts of software development and deployment that have been transformed by cloud computing, one of which is quality assurance (QA).
The use of cloud computing into quality assurance procedures provides enterprises with numerous benefits, including flexibility, scalability, and efficiency, which in turn enables them to more efficiently guarantee the quality of their software products.
The fundamental objective of this study is to determine what components of cloud computing QA are most crucial.
More specifically, the research will concentrate on the identification and analysis of key quality parameters.
Specifically, the study highlights the distinct quality assurance issues and requirements that are associated with each cloud computing model by analyzing a variety of cloud computing models, such as SaaS, PaaS, and IaaS.
Further, the work discusses potential future directions in cloud quality assurance including automation and multi-cloud approaches and how these directions might be applied to improve the quality assurance processes.
One more contribution of the study is that it reveals critical challenges that quality assurance teams face when operating in cloud environments and discusses the possibility of enhancement through the use of innovative technologies.
In result, a collection of best practices to facilitate efficient quality assurance in cloud environments is provided.
The purpose of this set of practices is to optimize quality assurance procedures, reduce costs, and guarantee the delivery of high-quality cloud services.
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