Performance Test effort estimation is the initial challenge we face in the Performance Test Life cycle. As Performance Testing is more like an investigation activity which may take any direction, the ad-hoc estimation methodologies used for performance test estimation doesn’t seem fruitful. Because of the dynamism and varying scope, there are lots of issues in the test effort estimation. Based on our experience in the performance testing projects on the web based applications, we conjecture that the Performance Test Estimation approach using Test Factors could be more reliable. Our approach is based on the consideration of the various test factors involved in scripting, execution and analysis, thereby eliminating the use of ad-hoc estimation methodologies and it is architecture / technology independent.
This paper describes how to do effort estimation for a performance testing project. The paper focuses on the pre-requisites and the factors which need to be analyzed in order to arrive at the performance estimation model along with the details about how to use this estimation model. This approach is being implemented in Honeywell for the estimation of Performance Testing effort on web applications and is proven to be ninety-five percent accurate. It’s been used to estimate ten projects falling under simple, medium and high complex project categories. The case study illustrates the application of this technique to arrive at the estimation for a typical web application.
The readability of the paper covers Performance Test Engineers, Test Leads, Test Managers and others with the domain knowledge of performance testing.
This paper describes how to do effort estimation for a performance testing project. The paper focuses on the pre-requisites and the factors which need to be analyzed in order to arrive at the performance estimation model along with the details about how to use this estimation model. This approach is being implemented in Honeywell for the estimation of Performance Testing effort on web applications and is proven to be ninety-five percent accurate. It’s been used to estimate ten projects falling under simple, medium and high complex project categories. The case study illustrates the application of this technique to arrive at the estimation for a typical web application.
The readability of the paper covers Performance Test Engineers, Test Leads, Test Managers and others with the domain knowledge of performance testing.
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