AI and Machine Learning in Automation Testing

• Posted by Riley Claire October 24, 2023 Filed in Technology #machine learning  #AI & Machine Learning solutions  153 views
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  The tactical platform of Artificial Intelligence (AI) and Machine Learning (ML) is being leveraged by many organizations to carry out their specific business-related activities optimally and rewardingly. In the same manner, the domain of AI and ML is also proving to be beneficial for carrying out software automation testing tasks easily and efficiently. However, the testing team should have the required expertise and know-how to implement AI and ML in automation testing feasibly, In this article, you will get to know about a few ways to strategically implement the platforms of AI and ML in the test automation field.

  

  What is Artificial Intelligence (AI)?

  Artificial intelligence provides a streamlined and strategic platform through which facts, information and data can be learned by machines so that ultimately firm decisions can be made. A data-based conclusion can be made by the system from the algorithms.

  Machine Learning (ML) is a subset of AI and AI uses the ML platform, so that models can be trained with large amounts of data and then these trained models are used so that predictions can be made and the desired output can be generated. The platform of AI also plays a strategic role in software automation testing.   

  What is Machine Learning (ML)?

  Computational methods are used by the ML platform, so that information can be learned directly from data. There is no specific requirement for an existing equation as a model. The following are the three essential components of ML:

  • A decision process: A prediction or categorization can be created by using the ML algorithms platform. An approximation is provided by algorithms about a trend in the data dependent on particular data input that can be unmarked or tagged
    
    

  • Error function: The model's predictions are analyzed by the error function
    
    

  • Optimizing models: The gap is closed by adjusting weights between the standout example and the model prediction, if there is an adequate performance of the model on the training data sets.
    
    

  Following are a few key factors that need to be considered when the platform of AI and ML is implemented in test automation:

  1. The tactical use of API testing: It is a testing method wherein data exchange and communication are enabled between two software systems. The application defects can be thoroughly identified through the API testing platform. When the test fails, the code can be dealt with easily and also application changes can be resisted through which automation can be done easily.

  Manual UI tests can be converted into automated API tests through the AI platform.

  1. Leveraging test scripts: When there is an alteration done to the code, it becomes difficult to ascertain the number of tests required by software testers. The AI based software automation testing tools can be able to predict whether multiple tests are required by the application or not.

  When tests are being run using AI then unnecessarily running tests can be stopped and more time can be saved. The overall system performance can be analyzed without the need to repeat the test scripts.

  1. The tactical use of machine learning: When the software that is being tested is updated, then persistent and ongoing monitoring is required by the software automation testing platform. Through the tactical use of the ML platform, this specific issue can be tactically addressed.

  The platform of ML helps in automatically updating and generating test cases, identifying flaws and enhancing the current code scope. High qualitative and quantitative work can be derived from the machine learning platform in considerably less amount of time. The outcome is as per the required expectations.    

  Conclusion: The team should frequently update themselves by learning about the current and latest trends in AI and ML. The team should also be able to scale up the value of artificial intelligence and machine learning from a test automation perspective. If you want expert advice, then there are specialized and certified software testing services providers that can provide you with noteworthy solutions that are aligned with your project specific requirements.