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In order for results to be consolidated, both the test and the test environment must be identical, and the test results must be statistically equivalent. One approach to determining if results are similar enough to be consolidated is to compare results from at least five test executions and apply the following rules: If more than 20 percent (or one out of five) of the test execution results appear not to be similar to the rest, something is generally wrong with the test environment, the application, or the test itself. If a 95th percentile value for any test execution is greater than the maximum or less than the minimum value for any of the other test executions, it is not statistically similar. If every page/timer result in a test execution is noticeably higher or lower on the chart than the results of all the rest of the test executions, it is not statistically similar. If a single page/timer result in a test execution is noticeably higher or lower on the chart than all the rest of the test execution results, but the results for all the rest of the pages/timers in that test execution are not, the test executions are probably statistically similar.
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Summarize Data Effectively
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Summarizing results frequently makes it much easier to demonstrate meaningful patterns in the test results. Summary charts and tables present data from different test executions side by side so that trends and patterns are easy to identify. The overall point of these tables and charts is to show team members how the test results compare to the performance goals of the system so they can make important decisions about taking the system live, upgrading the system, or even, in some cases, completely reevaluating the project.
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Keep the following key points in mind when summarizing test data: Use charts and tables that make your findings clear. Use text to supplement tables and charts, not the other way around. If a chart or table is confusing to the reader, don t use it.
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Customize Reports for the Intended Audience
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Performance test results are most commonly read by one of three audiences: technical team members, non-technical team members, and stakeholders outside of the core team. These three groups tend to look for very different things in a performance report and are inclined to prefer different presentation methods. When reporting, make sure that you identify which group or groups you are reporting to and what their expectations are before deciding on the best way to present the results you have collected.
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Use Concise Verbal Summaries
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Results should have at least a short verbal summary associated with them, and some results are best or most easily presented in writing alone. What you decide to include in that text depends entirely on your intended audience. Some audiences may require just one or two sentences capturing the key point(s) you are trying to make with the graphic. For example: From observing this graph, you can see that the system under test meets all stated performance goals up to 150 hourly users but at that point degrades quickly to an essentially unusable state. Other audiences may also require a detailed explanation of the graph being presented. For example: In this graph, you see the average response time in seconds, portrayed vertically on the left side of the graph, plotted against the total number of hourly users simulated during each test execution, portrayed horizontally along the bottom of the graph. The intersection points depict
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Make the Data Available
There is a disturbingly popular belief that performance testing (or other testing) data should not be shared in its raw form out of fear that the consumers of that data will use or analyze it improperly. While this concern is not invalid, of much greater concern is the fact that it is simply not reasonable to expect any one person or team to be able to extract all of the value from a set of data at one point in time. Data provides different value to different people at different times, and the only way to get the most out of the data is to make that data continually available to the team. Additionally, making the data available tends to minimize some people s perception that the performance results are simply fabrications based on a set of tools and processes that they do not understand.
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