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Volume Testing in Software Testing: Definition & Examples
Since no testing activities, other than volume tests, check the ability of the system to process large data pools, there’s no reasonable way for teams to skip volume testing. If undetected, issues like data processing and storage issues can lead to security jeopardy or system shutdown.
It’s a volume tester’s job to ensure the software can handle any estimated data loads.
This post provides business managers, developers, and beginner testers with an understanding of the volume testing, the objectives it helps accomplish, its best practices, and challenges to take into account when preparing for testing sessions.
Volume testing definition refers to validating the performance of the software when it processes large data volumes. Volume testing is also a subset of comparative load testing. The benchmark test is carried out based on the current data volume (usually corresponding to the current filling of the industrial environment). Then, a QA team performs a different test, after filling the database so that it corresponds the forecasted values. Volume testing can be both short-term and long-term.
The Objectives of Volume Testing
Volume tests cover a wide range of operations and infrastructure components — databases, online systems, file exchanges, file systems, and system memory. Validating such a wide range of elements helps testers achieve the following objectives.
Identifying the capacity of the system. Volume testing provides developers and project stakeholders with insights that can be used to predict how much data the system can process without fail. Knowing the capacity of the system facilitates scalability planning and comes in handy when creating contingency plans.
Detecting errors induced by pressure on the system components. One of the objectives of software volume testing is to detect issues that only show when the data load increases — higher response time, system failure, or security exploits.
Testing system response time. Volume testing is effective as it helps company managers ensure that software performance is not disrupted and the system response speed keeps to be consistently high regardless of the amount of data users share via software.
Ensuring there’s no data loss. Only through volume testing in software testing, the project team can ensure that no data is lost as the size of the database and the pressure on the system increases;
Reducing operating costs by identifying load issues on time. By analyzing system response to increasing data volumes, QA professionals will be able to capture the warning signs of downtimes and crashes. In real-world conditions, businesses can manage data loads proactively, increasing the amount of disc space or expanding the database as soon as the amount of data nears the established threshold.
Helps design scalability plans. Volume tests help business managers understand if scaling up (increasing the size or the speed of existing infrastructure components) or scaling out (adding more components to support the system) is a suitable strategy.
Getting insights on the system behavior under low, medium, and high data loads. Volume testing assesses system’s performance under low and medium loads to make sure it works as it should and no performance issues are there. Under high data loads, the risk of data loss or overwriting is skyrocketing — volume testing is needed to ensure that the system is not at risk of overflow or data security issues.
Challenges in Volume Testing
All the major considerations in volume testing have to do with data. This is why there are a few things to always keep in mind when starting a volume testing.
Populating a database is especially challenging if you’re dealing with the relational databases — they have a robust structure and dozens of adjacent tables. To ensure the high quality of test data, QA specialists need to collect diverse fields, both the required the optional ones that include large binary files.
Understanding the data types and connections between them. QA professionals have to deal with a wide range of data — valid, invalid, absent, boundary, or wrong. Understanding the differences between the types, the connections between them, and the way the software reacts to each of those is challenging for novice testers.
Volume testing deals with large data volumes compared to other types of performance testing. Having to manage extensive data sets complicates automation and increases the amount of the workforce involved (refreshing a data source, for one, requires an extensive team). Also, developers have to deal with handling the data that has piled up as a result of regular testing sessions.
Differences Between Load Testing and Volume Testing
Despite rather clear differences between load and volume testing, it’s common for business managers and beginner QA testers to confuse the two. First things first, take a look at the definition of each term:
Load testing validates the performance of the system under normal loads.
Volume testing is conducted to assess the behavior of the software under large data volumes.
Thus, the type of test data, as well as the range of use cases for testing, are different for load testing vs volume testing. To get a better understanding of the differences between the two, take a look at the table below:
Focuses on validating the stability of the software
Focuses on validating the system’s capacity
Tests the system under normal conditions
Tests the system both under normal and abnormal conditions
Primarily focuses on security issues
Primarily focuses on data storage and data loss
When You Might Need Volume Testing in Real life
To get a better understanding of the use of volume testing for websites, apps, and web application projects, here are a few volume testing examples that illustrate how it is used in real life.
When the product or a user database on the website increases. If you are about to load a number of items into a shopping website database, volume testing is crucial to ensure that your infrastructure is capable of handling an extended data load.
When a company wants to estimate if the infrastructure is capable of supporting forecasted data volumes. Volume testing helps plan the processor and disc capacity, the amount of system memory and network bandwidth needed to securely process an estimated amount of data.
When building contingency plans, it’s crucial to know what are the red flags of system failure. As a result of volume testing, the project team will be able to notice patterns and trends in system behavior as the data volume increases. This knowledge is crucial for creating an informed contingency strategy.
Volume testing prepares the system for dealing with extreme data loads (e.g. when a set of branches are attached to the system). No other type of testing can replace the insights volume testing provides project teams and testers with.
To make sure your product is well-protected from data-volume-induced downtimes and crashes, request a team of QA professionals, with a ready-to-deploy volume testing checklist.
PerformanceLab has years of testing experience — we worked with dozens of products across all major industries. Take a look at our portfolio to see the projects we worked on. You will benefit from a flexible framework, a robust testing toolkit, and a high-level workforce. If you want to ensure that the software you’re bringing to the market is bug free, leave us a message and our reps will get back to you A-S-A-P!