A Short Guide to Automated Functional Testing on Audio and Video Apps

A Short Guide to Automated Functional Testing on Audio and Video Apps

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5 min read

Applications for video conferencing are frequently used for online learning, workflow discussion, or broadcasting a new game to pals. Applications for video conferencing have never been so widely used. The best audio and video quality without significant lag times and with some enhancement features like echo cancellation or noise suppression are what people need most from their video conferencing software. Therefore, the quality needs to be managed.

The fact that quality requirements are being raised annually is a crucial component of audio and video applications. For instance, five years ago, standards for video quality were substantially lower than they are now. Specifically, folks were content enough as long as they could see each other, and the video worked. However, as video capabilities have evolved through time and technology has advanced, users’ expectations have grown. Video calls were previously only made between two people and lacked advanced features. Nowadays, however, users frequently make video calls with multiple people while utilizing various attributes, including screen-sharing capabilities, and doing so on numerous devices with multiple screen sizes and aspect ratios. Users anticipate that everyone will be able to see and hear in excellent quality.

Audio video testing is more crucial than ever because of the change in customer expectations while utilizing video conferencing systems.

Why is audio/video call automation necessary?

If you want to test an application as close to the real scenario as possible, assembling a team of human testers would be a brilliant idea; however, automation techniques have some tremendous advantages since they can carry out many tests and are much more practical.

There are some things we cannot automate. However, a skilled automation engineer can modify the automation solution to mimic real-world user behavior to provide outcomes that can accurately capture the user experience. The suitable setup, modified assessment techniques, and selection of the appropriate tools offer the possibility to test a variety of application functionalities across several platforms, including network-restricted tests, as well as to collect reliable data for the client.

While manually testing applications’ audio and video quality is doable, the main challenges with manual testing are the few people and time resources. Manual testers cannot run tests nonstop for a whole week or month. Additionally, manual testers must constantly be aware of the accuracy of the testing process. Specifically, if the media capture and feed were completed at the appropriate time or whether the network connection was accurate. Manual testers must pay close attention to this, and we must recognize the possibility that mistakes will be made during test execution so that it might take more time. But again, what about automated testing? The key benefits of using a test automation platform over manual testing are that tests may be run with little to no downtime, and the test setup can frequently be increased, resulting in a high number of tests being run and, as a result, more test data.

How do we test audio?

When testing audio, we must ensure that a user can speak and that the other user can hear them clearly when on a call. Furthermore, we must verify that the users may mute themselves and that others cannot listen. We can use a variety of technologies to accomplish this to determine whether or not the audio gets sent.

Using the FFmpeg tool is one method of verifying this. We can quickly ascertain whether audio is present in an audio file using FFmpeg’s “volume detect” filter. To get the output for the sample, we would first record an audio piece and then run the FFmpeg command with the appropriate filter. The user’s ability to communicate audio will be verified after we verify that the volume level is high enough. Similarly, when the user is muted, we would need to confirm that the volume does not rise to a level that would be regarded as a standard audio volume.

The SoX tool is another tool to test audio. We can determine the recorded audio sample’s volume level using the SoX stat effect. We would next assess this outcome and confirm if the audio sample only contains silence or includes some audio, just like we would do when using the FFmpeg program.

How do we test audio video?

We use image recognition techniques implemented in Py-TestUI and taken from the OpenCV package to test the most crucial video functionalities.

We record or feed our sample video to verify that other users can see the video—on a video call—from the person on the device under test. After that, we compare the actual video to the expected video using an image recognition algorithm. This validation has two results. The first result is that we can verify that other users are viewing the right video. The second result is that we learn that other users do not see the anticipated video. To determine if there is a problem in this instance, we must do a more thorough investigation to check the presence of any bug in the application.

Additionally, we must confirm that the user on the test device can receive videos from other users. Once more, the image recognition system is utilized to compare our custom video—sent by other users—to the films the user sees on the test device.

If sharing the device’s screen is an option, that functionality also needs to be verified. In other words, the user should be able to stream their screen to others and share it with them. The user should be able to tell when other users are sharing their nets, and the reverse is also true. We employ image recognition technology to compare the expected video with the actual video to implement screen-sharing capability validation.

The way that various programs provide movies during calls is another thing to examine during testing. Additionally, we must confirm that these views behave as planned in multiple circumstances. Is a grid view or a dynamic/focus dominant view, for instance, an option?

Conclusion

It is possible to create an automated test suite using various tools and frameworks. However, the ideal option depends on how important some of these tools’ features are.

Your application should be read and considered in its complete form. Almost all automated functional audio-video test apps are done in this manner. Our engineers are industry leaders, and we go above and beyond to enhance the goods for our clients. Please find out more about our skills in testing audio-video quality, then contact us to discuss your project.

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