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How To Analyze And Report Web Performance Testing Results Using Automated Software Testing Tools?

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Automated Software Testing

Progressive web applications have become an integral part of the modern app industry. This is because while using these apps, the end users can access multiple features and perform actions without downloading the application on their devices. This process not only helps to save a lot of device storage but also the hassle of going through the downloading and installing process. App developers can integrate automation testing to improve the efficiency of web app test cases.

However, developing and testing web apps is a very complex process as they need to perform seamlessly on different devices with multiple software and hardware combinations. This article will explain how developers can use modern automation testing tools to analyze and report web performance testing results. We will also understand some of the top automated testing tools and how these can improve the modern software testing environment.

Exploring Web Performance Testing

When exposed to various conditions, web performance testing analyzes web applications’ responsiveness, speed, and overall performance. Ensuring that a website or web application meets the user’s expectations is crucial. The most important parameters include reliability, scalability, and overall speed. Let us now understand some of the key aspects of modern web performance testing:

  • Load Testing

Using load testing, the developers can determine the system’s behavior when exposed to unexpected load conditions. This process involves testing the application with both normal and peak traffic levels. The primary objective is to evaluate the time response and overall stability.

  • Stress Testing

Using stress testing, the developers can analyze the behavior of a system beyond its normal operational capacity. For this process, they must push it beyond its limits and identify the breaking points or weaknesses under extreme conditions.

  • Endurance Testing

Endurance testing helps to understand the ability of the system to handle a sustained workload for an extended time. This process also identifies severe performance degradation or memory leaks over time.

  • Scalability Testing

This process measures the ability of the system to scale up or down in terms of user resources or transactions. Using this process, the testers can also assist the system’s ability to maintain performance as the load gradually increases.

  • Performance Profiling

Performance profiling involves a comprehensive process of analyzing the system components to identify bottlenecks that can arise in terms of inefficient code, network issues, or slow database queries. These processes can have a severe impact on the overall performance of the web application.

Performance Profiling
Performance Profiling
  • Benchmark Testing

This process compares the current performance metrics against the modern industry standards or the benchmarks set by the competitors. The primary objective of this process is to assess the relative performance of the application to ensure that it can meet the expectations of the modern competitive app industry.

In short, web performance testing is essential because an unreliable or slow application can lead to user frustration, loss of business opportunities, and decreased user engagement. This process also helps to identify and address performance benchmarks, ensure a positive user experience, and optimize resource utilization for the company.

Some of the most commonly used tools for implementing web performance testing include Gatling, JMeter, and LoadRunner. These tools use various performance metrics like resource utilization, response time, and error rates to guarantee the smooth and efficient functioning of the web application.

Analyzing Web Performance Testing Results with Automated Testing Tools

To quickly analyze and report Web performance testing results using modern automated testing tools, testers just have to follow the following steps:

  1. Data Collection

After running performance tests using automation tools like Jenkins, the app developers must collect the data generated after the test execution process. These data will include multiple metrics like error rates, response time, and resource utilization. The resource utilization data will integrate both CPU and memory usage.

  1. Data Organisation

The developers must arrange the collected data meaningfully and based on their priority. For instance, they can group similar metrics for better understanding and analysis.

  1. Identification of Key Metrics

After the organization process, the app developers must determine the crucial metrics based on the application’s specific requirements. For instance, response time, error rates, and throughput are often considered crucial for most modern web applications.

  1. Performance Analysis

After the developers have collected, organized, and identified the key metrics, it is time to analyze the data to identify trends, patterns, and anomalies. The developers should also look for deviations from expected performance benchmarks and assess the impact of various factors on the application. Some of the considerable factors include network conditions, concurrent users, and server load.

  1. Report Generation

After analyzing all the important parameters, the automation testers must create comprehensive reports summarising the performance test results. This report should act as a summary of the testing scenario. 

Report Generation
Report Generation

The app developers can also consider integrating graphical representations like charts, performance data graphs, and key metrics in this report. It is also important to mention any bottlenecks or issues encountered along with the recommendations for improvement.

  1. Visualization

Visual data like histograms, graphs, and tables massively help to present the data effectively and simply. The developers can use tools like Grafana or custom scripts to visualize complex data sets for easier comprehension and analysis. 

Moreover, modern cloud platforms like LambdaTest natively allow developers to generate visually attractive test cases consisting of screenshots and videos automatically captured during the test execution process.

  1. Comparison and Baseline Analysis

The developers must compare test results with previous test reports or baseline data. This will help them to observe any performance issues or regressions that might be present in the application architecture.

  1. Recommendation

Based on the analysis we performed in the previous steps, it is crucial to provide recommendations for optimizing or fixing the application performance. Some of the most important recommendations include changes in application architecture, code optimizations, and caching strategies.

  1. Documentation

After performing the previous steps in the performance testing analysis process, the developers have to document the entire process, including the tools used, test environment details, test configurations, and all the challenges faced during the testing process. This data will act as a reference in case similar issues arise in the future while updating the application architecture.

  1. Presentation

The developers need to present the findings and all the resolution recommendations to company stakeholders. These stakeholders can include project managers, other developers, or higher management. While implementing this presentation, the developers must ensure it is clear and understandable.

Modern automated testing tools have built-in reporting features that automatically generate test reports. Moreover, they also allow the developers to customize the reports to meet specific project requirements. These customization processes can include scripting or using additional reporting tools.

We would also advise the developers to remember that the effectiveness of the analysis and reports massively relies on the accuracy of the data collected and also the depth of the interpretation skills. So, it is not only important to focus on improving the accuracy of the test data but also on improving the experience of the automation testers. 

Top Automated Testing Tools in the Market

To help the modern automation testers, we have created a list of some of the most popularly used automated software testing tools in the current industry:

  • LambdaTest

Although LambdaTest isn’t an automation testing tool, we included it in the list due to its unique and diverse features for the execution of automation testing over the cloud. While using this platform, developers can use cloud testing to execute automated cross-browser test cases on web applications through remote servers. 

These servers grant access to thousands of real devices and can run test cases from various popular automation tools like Selenium, Appium, and many others. It also helps the developers to analyze the performance testing results using comprehensive test reports. This platform also integrates screenshots and videos in the reports to further improve the troubleshooting and debugging process.

  • Selenium

Selenium is a popular open-source tool for automating web browsers across multiple platforms. While using this tool, the developers can use multiple programming languages and integrate them with different frameworks. 

The Selenium test suite consists of different tools like the WebDriver, Grid, and the integrated development environment to assist the developers at different stages of the application testing process. Selenium supports the integration of modern processes like parallel testing to initiate multiple test instances at the same time.

  • Appium

Appium is a popular and open-source tool for automating mobile applications across multiple platforms. Therefore while using this tool, the developers can test the application for iOS, Android, and the Windows platform. The application developers can also use Appium to ensure the compatibility of applications on both modern and outdated mobile devices.

  • JUnit/TestNG

These are Java-based testing frameworks that are primarily used to execute unit testing. While performing unit testing, the developers divide all the elements present in a web application into several smaller segments known as units. Using these tools, the developers can access assertions, annotations, and test runners for executing and organizing the test cases.

  • TestComplete 

This is a commercial automation testing tool that supports the testing of desktop, mobile, and web applications. While using this tool, app developers can access a wide range of features for multiple modern testing instances like user interface testing, functional testing, and regression testing.

  • Jenkins

This is an open-source automation server that allows developers to initiate continuous delivery and continuous integration on their web applications. While using this server, the developers can also integrate automation testing with tests, builds, and deployments of applications.

The Bottom Line

In conclusion, we can say that analyzing web performance testing results is a crucial parameter to understand the underlying issues in the application infrastructure. In this process, the developers must choose the correct automated software testing tools that complement the application’s requirements and preferences. All the strategies discussed in this article are based on a generalized approach to app development. 

To improve the accuracy of this approach, the developers must understand the specific requirements of their application, target audience, and intended usage. The app developing companies can train developers in this segment through workshops and seminars. Analyzing the target audience will also allow the developers to integrate various customized parameters to rapidly expand their audience base with a positive brand image.

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