Every organization wants to beat the competition in the fast-paced world of today, thus they are continuously under pressure to offer the highest quality applications. To satisfy these needs and ensure that applications are up to standard and market-ready they rely on test automation, which has gained popularity as a popular solution.
Automation testing enables accurate and efficient test execution because it improves test reliability and coverage while cutting testing time and expenses. Additionally, it makes it possible to test complicated setups and scenarios that are difficult to test manually.
But to achieve the desired level of quality, reporting, and analytics play a crucial role in the test automation framework since they show the outcomes of test execution and enable real-time monitoring of test automation. Thoroughly analyzing test findings, reporting, and analytics assist developers in increasing the effectiveness of their testing.
They also help them keep track of various difficulties that may be caused by a particular change in the behavior of the application or due to flakiness and provide instructions on how to analyze them properly. Specific information like test length, test count, error rate, pass or fail ratio, and various other characteristics are included in reporting and analytics.
It is crucial to remember that the test automation framework’s long-term sustainability and effectiveness depend largely on how well the reporting mechanism has been built. The test analysis report and feedback acquired in this way can be very beneficial to the development lifecycle if the test reporting is done thoroughly and at the appropriate time.
We will go into great detail regarding advanced reporting and analytics in test automation in this article. First, we will go over what reporting and analytics are, crucial metrics to take into account in an automation report, why they’re significant in test automation, difficulties encountered when using test analytics, and key aspects that must be taken into account when building the ideal test analysis report.
Making data-based decisions is critical for all stakeholders in today’s quickly changing application development market. By examining test automation reports, developers can have a better understanding of the quality of their application, decide where to make improvements if defects are found, and make sure that the application satisfies testing requirements.
Reporting and analytics in automation testing is the process of automatically creating in-depth reports on the outcomes of test execution. Developers can assess the success of their testing efforts by analyzing test automation reports, and by comparing the actual results with what was expected, they can spot trends and patterns that can help them improve their testing procedures.
The approach introduces quicker and better ways to uncover errors and pinpoint places where additional test cases are required or where existing test cases need to be optimized to maximize their efficacy.
The test results and test steps are thoroughly analyzed in the test automation report, including the number of tests that were run, the details of each of them, the steps that were run within those tests, the total test execution time, the individual test execution time, the steps that passed, failed, skipped, or became broken, defects found, and the reasons behind failed or skipped test cases. The developers can analyze the test findings and handle them with the help of all the information in the report, assuring the maximum application quality.
The total number of test cases, the passed or failed status, the duration of each test case of each test, the date and time the test was run, the environment name, the build name, and other metrics must all be included in a test automation report. All of this aids in offering insightful information on the quality of the application.
The other metrics that a QA must consider in a test automation report are listed below.
Overall Test Duration
The time required to perform end-to-end automated testing is measured by the overall test duration metric. This guarantees effective testing without noticeable delays.
The Total Number of Defects Discovered
This measure is crucial for identifying and analyzing all flaws in various application versions.
Overall Percentage of Passed/Dailed Tests
Overall percentage of passed/failed tests. By interpreting these indicators, developers can find areas for improvement and gain useful insights into the tested application’s quality. This indicator enables evaluating the thoroughness of the testing report over various periods and important releases.
Reporting and analytics can be particularly beneficial for test automation since they play a significant role in evaluating application quality and give precise information about the test execution and its results, making it easier to identify faults and accelerate the test process.
They provide important insights into the efficiency of the testing process by assisting in the analysis of test results through parameters and metrics that are a component of test automation and overall performance. They also offer an error log that aids in pinpointing areas that need improvement.
By giving a thorough perspective of the testing process, reporting and analytics in test automation relieve testers of the manual labor-intensive and time-consuming task of maintaining, updating, and adding crucial information. They are thereafter able to decide on the application’s release and additional testing with complete knowledge of how the application functions. The team is empowered to focus their efforts on more innovative or strategic tasks with the help of an automated report.
Additionally, they spot defects earlier in the development cycle and also facilitate analysis because they offer comprehensive data on the causes of failure or errors. These reports can be shared with the team members to aid them in keeping tabs on the application during several release cycles.
The fact that reporting and analytics reduce the chances of human error is another important advantage. It helps teams improve application resilience, identifies critical risk areas and potential weaknesses, and makes the development process run more smoothly.
Test analytics provide a more thorough view of testing quality and overall code health. Real-time analytics and reporting improve the effectiveness and productivity of the QA automation team by locating and tracking areas of problems, which enables quick error detection.
To obtain quick and reliable test reporting and analytics, it may be necessary to overcome the challenges listed below.
More Releases in Less Time
Traditionally, one of the last steps in a waterfall development process was to prepare and summarize a test report. Since there were not many releases, there was time for data collection, report creation, and decision-making.
The standards for a “good” test report have been significantly altered by the present quick-release rhythm. Testing must be completed quickly, and choices regarding application quality must be made in a shorter period (weeks, days, or even hours). If the feedback is delayed or of poor quality, the release will take longer to complete.
Large Amounts of Data
Test automation (means more testing) and device expansion (means more devices, browsers, and versions) are two factors that contribute to the massive number of data that modern testing teams produce.
Too much testing data causes problems for many organizations, making it difficult for them to distinguish between what is useful and what is not. Large amounts of irrelevant data lead to unstable environments, shaky test cases, and other problems that result in false negatives for which it is challenging to identify the underlying cause. As a result, it is quite difficult to go through each failure and indicate it in the report.
Separate Test Data
Due to the vast size and variety of teams, tools, and frameworks, there is yet another problem, especially for larger organizations. For instance, a lot of testing data originates from numerous teams and individuals (such as developers, testers, API testers, etc.), and it also comes in a variety of frameworks and formats, including Selenium, Appium, and others. Without a standardized method for gathering and organizing this information across the organization, good test reporting becomes extremely challenging.
In test automation, reporting and analytics are essential because they give developers a simple and clear picture of the test’s progress and outcomes.
To effectively communicate information, the first best practice is to utilize a clear and concise reporting format that is easy to read and understand and includes clear headings, tables, dashboards, and graphs. Developers may immediately understand the overall status of the testing efforts, spot trends, and make data-driven decisions because of these visualizations.
Collaboration and offering useful insights into the testing process are two more best practices for reporting and analytics. This includes sharing access to test metrics reports that include the number of test cases that were run, the number of defects found, the number of defects that were corrected, and the percentage of tests that were completed in addition to providing information about the testing process. Developers and stakeholders can then lead discussions about test results and offer suggestions for ways to make the testing process better.
This strategy promotes a collaborative atmosphere where problems can be solved quickly, information can be exchanged, and decisions can be taken as a group. Thus fostering transparency, ensuring that all team members are aware of the testing process and findings, and embracing multiple viewpoints and insights from various stakeholders to improve decision-making.
Another crucial factor to take into account is that in continuous testing when test suites are regularly run, real-time reporting is essential. Giving teams access to real-time test reports enables them to see problems early, act quickly, and make decisions based on the most recent facts. As a result, teams are better able to maintain excellent application quality over the whole development lifecycle.
Another important factor in offering better reporting and analytics is emphasizing flaws in depth. The report should include details about the type of error, how serious it is, and the efforts taken to repair it. This will make it easier for developers to comprehend how errors affect the application and what efforts need to be taken to fix them.
Another important factor is the use of automatic reporting tools. It can improve accuracy, speed up the reporting process, and give testing process insights in real-time. CI/CD pipelines and test automation frameworks are examples of tools and technology that make real-time reporting possible. These tools can generate reports automatically based on predefined criteria, saving time and effort compared to manually creating reports.
For assessing the quality of an application, reporting and analytics are crucial. They offer valuable insights into the outcomes of test execution, highlighting potential areas for development and other useful metrics. Although they might not provide in-depth information about the testing process itself, they give developers a way to assess the success of their testing efforts, identify defects or other issues with the application, determine its performance, choose the best course of action, and decide whether the application is ready for release.
LambdaTest, a platform for automated testing of Selenium, Cypress, Playwright, and Puppeteer in the cloud, provides comprehensive reporting and analysis of test results. It provides a complete view of the tests, test runs, test results, test logs, screenshots, metrics resources, environments, and orchestration tools enabling teams to simply manage their testing process, as well as quality insights. Additionally, it offers customizable dashboards and reports that enable teams to monitor important metrics like test coverage, defect rates, and the status of test execution.
LambdaTest is an AI-powered test orchestration and test execution that gives users online access to more than 3000 real devices, browsers, and operating systems, with their respective versions, for manual and automated websites and mobile app testing.
This platform supports several programming languages and integrates with well-known test management solutions. It also has several built-in logging and debugging tools that enable teams to provide detailed reports on the outcomes of their test automation to identify and address issues that may have arisen during test execution.
However, analyzing all the data from test automation reports and frameworks takes time. Test analytics from LambdaTest is an online resource for obtaining, analyzing, and simplifying QA procedures and test data. With the aid of the highly customizable dashboards offered by Analytics, QAs, and testers can easily keep track of the development and enhance the quality of their tests running on the platform at a glance, display real-time execution of test data with a single click, and reach well-informed decisions.
The LambdaTest dashboard enables unified test reporting by automatically and smartly classifying all failures and providing practical guidance on how to start resolving problems, respond promptly, and enhance tests.
Other features of this platform include the ability to automate various types of testing, such as end-to-end, functional, compatibility, integration, and system testing; the implementation of parallel testing by running tests simultaneously across various browsers on various machines; early problem detection; faster feedback; improved teamwork; and increased test coverage through seamless integration with CI/CD tools. This makes it possible to enhance the user experience and overall quality of the application.
The discussion above makes it apparent that advanced reporting and analytics are crucial in test automation. By adhering to recommended practices and making use of the right tools, effective test automation reports can be created. Organizations may receive deeper insights into application quality and support improved decision-making with accurate and thorough reports and analytics.