Why do you need mobile app testing? In software testing, it’s not enough to test the system’s code functionality and compatibility, but it’s also imperative to check its non-functional parameters. These non-functional parameters are concerned with the system’s structure but with regard to the customer experience delivered. Seeing as customer satisfaction is a key ingredient […]
Why do you need mobile app testing?
In software testing, it’s not enough to test the system’s code functionality and compatibility, but it’s also imperative to check its non-functional parameters. These non-functional parameters are concerned with the system’s structure but with regard to the customer experience delivered.
Seeing as customer satisfaction is a key ingredient to a software’s success, one can see why non-functional testing is a major subset of software testing. Not only should the application work according to its set algorithm, it should also be able to handle the onslaught of colorful users and assorted amounts of data.
Among the non-functional categories are two tests that are essentially identical in nature but serve different purposes: load testing and stress testing. Both deal with system behavior and load management, but utilize differing methodologies.
What is the difference between load and stress testing? If this question still boggles your mind, then you are in the right place! Without further ado, let’s discuss the difference between these two types of software testing processes. Let’s start with load testing..
Load testing is a type of non-functional testing that checks how a system functions when encountering a simulated number of concurrent users. The testers evaluate the software’s capacity and its behavior when under the expected normal to maximum load, whether the performance remains constant or deteriorates.
In order to carry out the test, the application’s required functionalities must be available and working. For that reason, load testing is more suitably applied in the latter stages of the software development life cycle.
As an example, assume a development team constructed a social networking website for their company’s employees to utilize. The number of employees at the company in question ranges between 200 and 250. Each post is expected to support a file size of no more than 200 MB.
Test 1: A varying number of users, not exceeding 250, concurrently log in to the system.
Test 2: A varying number of users, not exceeding 250, concurrently publish a text post.
Test 3: A varying number of users, not exceeding 250, concurrently upload a photo.
Test 4: A varying number of users, not exceeding 250, concurrently upload a video.
Test 5: A varying number of users, not exceeding 250, concurrently publish a post with a combination of text, photo, and video formats.
Test 6: A varying number of users, not exceeding 250, concurrently download a file.
Test 7: The system is run alongside a varying number of other open applications.
Testing the system’s capacity and its corresponding behavior not only detects bugs, but also identifies performance bottlenecks that may be encountered when being actively used. Uncovering these bottlenecks then lessens the instances of system downtimes, providing ample time to come up with solutions and avoiding costly mistakes.
The test guarantees that the system can perform as stated while also detecting the system’s operating capacity restrictions. The information gathered is used to plan for future scalability and capacity modifications.
Let us now proceed to stress testing. Stress testing, which also falls under non-functional testing, is concerned with the stability and reliability of the system under stressful conditions. The test exceeds the expected or defined workload in order to discover the system’s limit and the conditions under which it will fail.
Not only will the system’s performance under stress be evaluated, but so will how it resolves mistakes and prevents data loss. As such, flaws that may result in data loss or memory leaks are recognized and reported.
Consider the company’s social media website from the load test scenario. To summarize, the website is only to be utilized by employees. The company’s average population is between 200 and 250 people. Each post should be limited to 200 MB in size.
Test 1: A number of users exceeding 250 concurrently log in to the system.
Test 2: A number of users exceeding 250 concurrently upload multiple photos.
Test 3: A number of users exceeding 250 concurrently upload a video.
Test 4: A number of users exceeding 250 concurrently publish a mixed format post exceeding the 200 MB limit.
Test 5: A number of users exceeding 250 concurrently publish a mixed format post over random intervals for 24 hours.
Test 6: A number of users exceeding 250 concurrently download multiple files.
Test 7: Restart the application after the system crashes.
Test 8: Terminate the application in the middle of uploading a file.
Test 9: Terminate the application in the middle of downloading a file.
This testing method determines how far an application can go beyond its predicted load and when its performance begins to deteriorate. The extra push also aids in the discovery of bug-related issues that may arise during the system’s peak usage.
When the circumstances around the breaking point are determined, better countermeasures can be implemented to improve how the system recovers from failures caused by this breaking point. These processes subsequently minimize or completely remove the potential for data loss and corruption, as well as address any vulnerabilities that may occur if the software ever reaches this point after deployment.
Now that load test vs stress test has been elaborated, here is a quick comparison between the two testing methods.
Evaluates the system’s capacity and behavior under normal and maximum user loads.
Evaluates the system’s behavior under extreme load.
Limited to expected loads, akin to real life situations that the system might encounter.
Push the system to its breaking point.
Determines the system’s operating capacity
Determines the system’s stability.
Measures the peak performance, server quantity, and response time.
Measure the stability, response time, and error management.
Despite the differentiation between load vs stress testing, when it comes to its fundamental ideas, the lines in the sand blur. In the end, both are non-functional testing approaches that strive to evaluate the system’s performance when subjected to expected real-world scenarios.
Another common goal is to uncover bugs and exceptions that may only appear under certain situations and would otherwise go undiscovered if not for the complete sweep-through.
After all this time establishing the difference between load testing and stress testing, comes the time for its application. As explained above, both tests address system behavior and load management only with divergent processes and goals.
The process demands knowledgeable testers and a large labor pool capable of designing and replicating test cases that cover the purposes of both load testing and stress testing, regardless of which type of testing is necessary. This is the case whether load testing or stress testing is required.
When you outsource these services to a reliable QA partner, you save both the time and the money that you would have spent otherwise on recruiting team members. It’s possible that Unbugify and its team of experienced QA testers will be the best business partner for you.
Whichever testing services you need, you can trust Unbugify’s team of qualified manual testers to do the job. Our load testers conduct assessments that measure how well the system handles heavy and demanding conditions. The stress testers, meanwhile, administer evaluations that gauge the system’s capability to keep up with rising demands and usage.
The test cases and results are then neatly wrapped in a bow, with Unbugify taking care of the documentation throughout the whole testing process.
Reach out to our live operators and create a plan for your load and stress testing needs. Contact us!