vIntroduction Volume Testing
The software application is developed keeping in mind about the end users and the volume of requests send to the application by these end users. Actual scenario for data volume could only be achieved when the application is into production mode and if such application is not volume tested then it can lead to an application crash or malfunctioning. In order to mitigate such unseen surprises, volume test is always recommended.
Volume testing can be defined as non-functional testing (NFT) or performance testing where the software application is subjected to the large volume of data in order to make sure that application is operating smoothly under the legitimate data volume condition.
Volume Testing is also termed as flood testing. Such Testing is conducted by increasing number of user requests to the system in terms of database calls, messages over queues or topics, files writing, etc. and study the impact on the response time as well as system behavior under different volume conditions i.e. normal, low, medium and high volume conditions. For example, the stock market software application is volume tested as it receives a high volume of buy and sells requests within the fraction of seconds from multiple sources.
Volume testing can be defined as non-functional testing (NFT) or performance testing where the software application is subjected to the large volume of data in order to make sure that application is operating smoothly under the legitimate data volume condition. This testing is also termed as flood testing. Volume testing is conducted by increasing number of user requests to the system in terms of database calls, messages over queues or topics, files writing, etc. and study the impact on the response time as well as system behavior under different volume conditions i.e. normal, low, medium and high volume conditions. For example, the stock market software application is volume tested as it receives a high volume of buy and sells requests within the fraction of seconds from multiple sources.
Advantages of Volume Testing
The following are the advantages of volume or flood testing for any software application.
- It provides a clear picture of the type of hardware required to run the software application in terms of CPU, memory, etc.
- Scalability plan can be identified very early.
- It helps to save lots of money that might be spent on a contingency plan.
- It helps to detect the bottlenecks at application operations very early.
- It provides confidence that the volume tested application is ready for real-world usage.
- It helps in making go or no go call for an application go live.
Disadvantages of Volume Testing
- Such testing adds extra cost to the project as it is done on top of functional testing by different performance testing team.
Why Volume Testing Is Often Recommended?
Volume testing is often recommended because of the following reasons.
- It helps to keep a check on the system performance when data volume has increased into the database.
- To study Software application behavior with a large amount of data.
- To evaluate the point at which the application stability starts to degrade.
- It enables to identify the application capability under normal, low, medium and heavy volumes.
Volume Testing Checks
The following parameters are evaluated and checked during volume or flood testing.
- Volume test aims to check if there is any data loss.
- Volume test is conducted to record the response time under different volume conditions and evaluate an average response time.
- It aims to evaluate if the data in the database has persisted correctly or not.
- It aims to verify if the data is overwritten with or without any notification.
- It aims to check for warning and error messages, and their association at a different level of volumes.
- It aims to check if high data volume in any way affecting the speed of requests processing in the system under test.
Volume Testing Best Practices
The following are the best practices which are widely followed for the best volume testing outcome.
- Don’t forget to stop all servers while checking all logs i.e. logs for server and application.
- Make sure that the happy scenario is working fine before starting the volume test.
- In order to procure the best result out of volume tes, staggering of the number of users is always recommended.
- Balance your volume test time in order to overcome license constraints.
- Any new build introduced should be handled very cautiously.
- After the baseline is established, the use case should be analyzed for any performance improvement.
- In the case of a performance bottleneck, the volume test should be repeated over and over in order to take the deep dive into the performance issue.
Volume Testing vs Load Testing
Given below is the comparison between volume and Load testing.
| Load Testing | Volume testing |
| Load testing is the type of performance testing where an application is subjected to a certain level of load in order to analyze the behavior of the software application. | Volume testing is the type of performance testing when an application is subjected to a large volume of data in a database or other system resources. |
| Load testing is conducted to check the system performance when the user`s request load is increased. It may include the increase of a number of files, messages, etc. | This testing is conducted to verify if the system is responding as expected to a certain volume of data. It may include an increase in file size, message volume, etc. |
Day To Day Challenges In Volume Testing
Conducting volume test is not a piece of cake as the testers sometimes face lots of challenges. Some of those challenges are listed below.
- Test data set required for volume test requires lots of time in its actual generation.
- Memory Fragmentation is quite difficult to generate during volume test.
- Volume test may require keys where the Dynamic generation of such keys could be quite difficult.
- Relational Integrity of generated data needs to be ensured which is not quite very straightforward.
- System behavior needs to be studied and recorded very frequently which requires extreme attention and caution in order to procure an accurate result.
- Application build should be well tested functionally before this testing could be started. In case, any functional issue is observed at the later stage that requires code fix then the new build should be tested for all volume test data volume scenario. Such practices incur lots of testing effort and therefore extra caution is required in SDLC.
Conclusion
In this article, we discussed the Volume Testing, its recommendation, checks, advantages, disadvantages, best practices, and challenges. It is very clear that the this esting is always recommended which helps to get an opinion whether the software application can withstand the load in the real world operational usages.
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