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Such framework defines the elements necessary to measure the performance of a CCS using software quality concepts.
This paper proposes a performance analysis model for Big Data Applications, which integrates software quality concepts from ISO 25010.
This work focuses on the performance analysis of BDA developed by means of the Hadoop MapReduce model, integrating software quality concepts from ISO 25010.
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For this, it is proposed the use of statistical methods to establish relationships between extracted performance measures from Big Data Applications, Cloud Computing platforms and the software engineering quality concepts.
For example, what is the extent of the relationship between the amounts of physical memory used by a BDA and the performance quality concepts of software engineering such as resource utilization or capacity?
The main goal of this work is to fill the gap that exists between quantitative (numerical) representation of quality concepts of software engineering and the measurement of performance of Big Data Applications.
The design of the framework is based on the concepts of metrology, along with aspects of software quality directly related to the performance concept, which are addressed in the ISO 25010 international standard.
Software Quality Assurance, delivered by painstakingly thorough (and slow) software testing, is predicated on the old fashioned notion that we have to release perfect software.
Software testing plays a crucial role in software quality assurance.
Many software quality attributes are highly interdependent.
Software quality issues are commonly reported when offshoring software development.
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