Audvik Labs

Performance Testing – Types, Stages and Advantages

Performance testing is a testing measure that evaluates the speed, responsiveness and stability of a computer, network, software program or device under a workload. Organizations will run performance tests in order to identify performance-related bottlenecks.

Without some form of performance testing in place, system performance will likely be affected with slow response times, experiences that are inconsistent between users and the operating system, creating an overall poor user experience. Determining if the developed system meets speed, responsiveness and stability requirements while under workloads will help ensure a more positive user experience.

Why to opt for performance testing

Organizations run performance testing for at least one of the following reasons:

  • To determine whether the application satisfies performance requirements (for instance, the system should handle up to 1,000 concurrent users).
  • To locate computing bottlenecks within an application.
  • To establish whether the performance levels claimed by a software vendor are indeed true.
  • To compare two or more systems and identify the one that performs best.
  • To measure stability under peak traffic events.

Types of performance testing

Load Testing is type of performance testing to check system with constantly increasing the load on the system until the time load is reaches to its threshold value. Here Increasing load means increasing number of concurrent users, transactions & check the behavior of application under test. It is normally carried out underneath controlled environment in order to distinguish between two different systems. It is also called as “Endurance testing” and “Volume testing”. The main purpose of load testing is to monitor the response time and staying power of application when system is performing well under heavy load. 

Stress Testing is performance testing type to check the stability of software when hardware resources are not sufficient like CPU, memory, disk space etc. Stress testing is Negative testing where we load the software with large number of concurrent users/processes which cannot be handled by the systems hardware resources. This testing is also known as Fatigue testing, this testing should capture the stability of the application by testing it beyond its bandwidth capacity.

Spike testing is subset of Stress Testing. A spike test is carried out to validate the performance characteristics when the system under test subjected to workload models and load volumes that repeatedly increase beyond anticipated production operations for short periods of time.

Endurance testing is a non functional type of testing. Endurance testing involves testing a system with a expected amount of load over a long period of time to find the behaviour of system. 

 

Scalability Testing is type of non-functional tests and it is the testing of a software application for determine its capability to scale up in terms of any of its non-functional capability like the user load supported, the number of transactions, the data volume etc.

Volume testing is non-functional testing which refers to testing a software application with a large amount of data to be processed to check the efficiency of the application.

 

Stages of performance testing

Developers can use these seven stages :

1. Identify the testing environment.

Identifying the hardware, software, network configurations and tools available allows the testing team to design the test and identify performance testing challenges early on. Performance testing environment options include:

  • Subset of production system with fewer servers of lower specification
  • Subset of production system with fewer servers of the same specification
  • Replica of productions system
  • Actual production system                                                                                                                                                  

2. Identify performance metrics

In addition to identifying metrics such as response time, throughput and constraints, identify what are the success criteria for performance testing.

3. Plan and design performance tests

Identify performance test scenarios that take into account user variability, test data, and target metrics. This will create one or two models.

4. Configure the test environment

Prepare the elements of the test environment and instruments needed to monitor resources.

5. Implement your test design

Develop the tests.

6. Execute tests

In addition to running the performance tests, monitor and capture the data generated.

7. Analyze, report, retest

Analyze the data and share the findings. Run the performance tests again using the same parameters and different parameters.

Performance Testing Benefits

  • Performance testing gives the client very important information about their application.
  • Developers can’t improve something if they don’t know it needs improvement. That’s where performance testing comes in. It tells the developers how the fast, stable, and scalable their software is so the client can decide if it needs to improve or not.
  • It is crucial to make your applications faster, more stable, and more scalable.  When applications run as expected, even under less-than-ideal conditions, then the user experience is improved. When applications don’t perform well, they cause frustration, hurt your reputation, and ultimately lose users.
  • It helps test the quality of the code and functionality. Every layer of testing helps ensure that code is quality and that functionalities and features do what they are supposed to do. This helps the client know that they’ve invested in software that does what they expected.

Conclusion

Performance testing helps to assess the amenability of the system to growth & identify weak points in the architecture. Also detect bugs in the software that could not have been identified otherwise. Also it tunes up the system and verify resilience and reliability of the system.

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