Mathematic Principles for Performance
Chapter 15 Key Mathematic Principles for Performance
Testers
Objectives
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Learn the uses, meanings of, and concepts underlying common mathematical and
statistical principles as they apply to performance test analysis and reporting.
Overview
Members of software development teams, developers, testers, administrators, and
managers alike need to know how to apply mathematics and interpret statistical data in
order to do their jobs effectively. Performance analysis and reporting are particularly
math-intensive. This chapter describes the most commonly used, misapplied, and
misunderstood mathematical and statistical concepts in performance testing, in a way that
will benefit any member of the team.
Even though there is a need to understand many mathematical and statistical concepts,
many software developers, testers, and managers either do not have strong backgrounds
in or do not enjoy mathematics and statistics. This leads to significant misrepresentations
and misinterpretation of performance-testing results. The information presented in this
article is not intended to replace formal training in these areas, but rather to provide
common language and commonsense explanations for mathematical and statistical
operations that are valuable to understanding performance testing.
How to Use This Chapter
Use this chapter to understand the different metrics and calculations that are used for
analyzing performance data results and preparing performance results reports. To get the
most from this chapter:
·
Use the "Exemplar Data Sets" section to gain an understanding of the exemplars,
which are used to illustrate the key mathematical principles explained throughout the
chapter.
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Use the remaining sections to learn about key mathematical principles that will help
you to understand and present meaningful performance testing reports.
Exemplar Data Sets
This chapter refers to three exemplar data sets for the purposes of illustration, namely.
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Data Set A
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Data Set B
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Data Set C