Mobile App Performance Optimization Solution

Ans: Here are four aspects:

1. Testing tools can limit protocol use, which can hinder their scalability. Ensure the tool you select provides adequate protocol support.
2. Ensure the tool you select can run distributed load tests. This ability will help you run comprehensive load tests.
3. The performance optimization tool you select must have automated log generation capabilities.
4. Select a tool that seamlessly integrates into your CI/CD pipeline

Ans: Mobile app performance testing tools help testers to monitor and test background apps, sensor latency, and varying network conditions. However, website performance testing tools focus on refresh rates, screen sizes, screen resolution across various browser OEMs, and page load times.

‍Ans:

• Bandwidth
• Network output queue length
• Processor usage
• Response time
• Memory usage
• Memory pages
• Thread counts
• Committed memory

‍Ans:

• Endurance testing – An app performance testing method that helps developers understand if the software can handle expected loads.
• Volume testing – Volume testing ensures systems perform well while under large volumes of data.
• Spike testing – Developers run spike tests to understand how their system will respond to a sudden influx of large load spikes.
• Load testing – The main goal of load testing is to identify an app's performance bottlenecks before an organization launches it.
• Stress testing – As the name suggests, developers run this test to observe an app's behavior under extreme stress to find out its breaking point.

Ans: Mobile app performance testing tools are essential to evaluate apps’ existing performance conditions and determine if the app meets scalability, stability, speed, and reliability criteria under expected loads. Applications released with poor performance metrics will have a damaging impact on brand reputation and impede the achievement of sales objectives.

Ans: Developers and QA testers most often use the following metrics during performance testing:

• Wait time 
• Error Rate 
• Average load time
• Response Time