Well Defined Load Testing Structure
Testing functional requirements of your system in the way how it behaves under different types of load is a basic explanation for performance testing. However we test the functions of the system, performance testing is classified under "non-functional testing" because we don't aim to test the functions we want to test how the system is functioning under different amount of loads. Therefore performance testing should be performed after the functional testing has been completed. Performance testing is crucial if you are testing an application which has an un-predictable load of user or if you have specified the quality of service in your Service-Level Agreement (SLA). Performance can not be defined by one of testing criteria since there are number of parameters in the system. I mean by this, there are subsets for performance testing which can be listed as
- Performance Testing
- Load Testing
- Endurance Testing
- Stress Testing
We can explain the differences between the performance testing activities as: performance testing is an general approach for performing testing to investigate CPU usage, memory, response time, speed, stability and scalability of the system under test (SUT), however the load testing aims to show the behaviour of the SUT for optimal and peak level of load and the endurance testing is to find how long can be the SUT available without error under specific loads and to find how long the time between two error point as mean time between failure (MTBF) and Spike testing is to find how the SUT behave when the load is suddenly increased to peak level. Stress testing finds how much load can be eligible for the SUT and to find the break point in terms of load for the SUT.
Since the performance testing is a detailed testing activity, in this post, I want to give some basic information about structure of load testing. Using realistic data for load testing is important to define user profile and distribution of data efficiently and correctly. Statistical variables can be used for this study; for example, any web application can be tracked by Google Analytics or Yandex Metrica in a very detail form of data. These application can show you how many users have been used the link and how many of them came as a first time and how many of them came as returning user. With this info number of users for each function of the SUT can be easily estimated.
Well Defined Load Testing
- log in: 80
- product detail view: 40
- search: 30
- basket showing: 20
- sign-up: 10
- buying: 5
|Number of Virtual Users for Each Function|
Load testing should be performed at least 3 times and taken the average values so that the SUT is behave consistent for the load testing scenarios. The important point for load testing, the result should be compared to the threshold value which has been defined by result of healthy system. So if the result is better than the threshold, the newly added feature/release can go live!