Performance testing focuses on helping developers understand how a system performs under a specific load. Different mobile app performance testing processes measure outcomes following benchmarks and criteria. These tests provide developers with the diagnostic data required to remove bottlenecks.
First, it’s crucial to comprehend how the program performs on user devices. During software testing, we can use several performance tests:
Load testing
In load testing, we measure system performance as the workload grows. This volume of work may involve concurrent users or transactions. As the workload increases, you monitor the system to measure response time and system stability. This workload is consistent with standard working conditions.
Stress testing
Stress or fatigue testing evaluates system performance outside of typical working limits. Stress testing assesses the stability of the software. It helps developers gauge the software’s ability to recover from failure and understand its limitations.
Spike testing
Spike testing is a sort of stress testing that examines software performance when you increase the workload abruptly and repeatedly. The workload exceeds normal expectations for a brief period.
Endurance testing
In endurance testing — sometimes known as soak testing — the software’s performance under a specified workload is evaluated over time. Endurance testing aims to identify system flaws such as memory leaks. Memory leaks may degrade system performance or cause the system to fail.
Scalability testing
The scalability test analyzes whether or not the program can manage increasing workloads successfully. You can assess this result by progressively increasing the user load or data volume while monitoring system performance. In addition, the workload may remain constant while resources such as CPUs and memory are modified.
Volume testing
Volume testing determines the software’s performance with enormous amounts of anticipated data. Because the test overwhelms the system with data, it is known as flood testing.
Performance Testing Metrics
Response time
Response time is the entire time required for a system or one of its functional components to respond to input. It is the time between a service request and the answer to that request. It can spend this time on anything from loading a website to performing a sophisticated database query. The quicker the response, the better.
Load time
Calculating load time entails determining the average time your system takes to respond to a request from its inception to its conclusion. A straightforward example is a web page’s loading time – from clicking a link to when the page has been entirely loaded in the browser.
Latency
Latency represents the time from when a user sends a request and when the server gets the first byte. It is the time required for communication between the client and server. Developers use this measure to identify latency issues. While they measure latency in milliseconds, they can also measure it in seconds, minutes, or hours.
Error Rate
Error rate helps you to calculate the number of requests resulting in errors by comparing it to the total number of requests your system receives. If you want to attain high performance and enhance the user experience, you need to reduce the error rate in your system. However, it is typical for mistakes to arise when the system’s load surpasses its capacity.
Maximum Active Sessions
‘Maximum active sessions’ represents the max number of concurrently active sessions. Like concurrent users, when the number of active sessions exceeds the system’s capacity, the complexity of processing requests may significantly affect system performance.
Performance Testing Tools
JMeter
Apache JMeter is an open-source performance testing tool that developers use to measure web application performance (and various other systems since recent updates). It simulates large loads on the system components, networks, or servers to evaluate their performance under various load types.
LoadRunner
While JMeter focuses on evaluating the performance of web applications and services, LoadRunner offers a broader range of alternatives, such as testing ERP software and legacy systems.
HeadSpin
HeadSpin provides its users with an automated software testing platform that lets them connect to real, SIM-enabled devices from anywhere in the world. The HeadSpin AI provides insights that you can use to build high-performing apps. It uses Appium (the world’s leading mobile testing automation platform) to assist with testing.
Final thoughts
Performance testing is a required procedure that provides developers with the diagnostic data required to resolve all speed, stability, and scalability limitations in your software product. It also helps you prepare your website or application’s capacity for predicted extreme situations, such as the Christmas season for eCommerce platforms, the end of the fiscal year for financial applications, and significant sporting events for live streaming services.
Despite the evident importance of performance testing to the long-term success of digital solutions, many organizations still need to devote more resources to it. Instead of viewing performance testing as an integral part of the SDLC, many run it at the end. This testing method may result in multiple design defects in your system architecture that, if left uncorrected, are extremely difficult and expensive to solve.
