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5 days ago · Data-driven testing (sometimes abbreviated to DDT) is a software testing methodology where test data is stored in external data sources like spreadsheets, databases, or CSV files, rather than hard coded into the test case, allowing the same test logic to be executed multiple times with different sets of data.
3 days ago · An automation framework is a set of guidelines, practices, and tools that help QA professionals test applications more efficiently. It includes coding standards, test-data handling methods, object repositories, processes for storing test results, and information on accessing external resources. A well-designed framework ensures better ...
5 days ago · Data-driven Framework In a data-driven framework, all the testing data inputs have been retained in the table or extension files, including .xls, .xml, .csv, etc. The values from the table will be read when the test scripts are executed.
3 days ago · Data-driven decision making is the process of collecting data based on your company’s key performance indicators (KPIs) and transforming that data into actionable insights. You can use business intelligence (BI) reporting tools during this process, which make big data collection fast and fruitful.
5 days ago · In recent years, deep learning algorithms represented by the Transformer model have gained widespread recognition in the application of time series anomaly detection. This paper proposes a novel data-driven Saxformer improvement framework based on the Boosting algorithm for multidimensional time series anomaly detection. This framework enhances the Transformer model’s ability to capture local feature information and improves both the robustness to noise and the flexibility in practical ...
3 days ago · What is Automation Testing? Automation testing is the process of testing the software application using an automation test tool to find the defects. In this process, executing the test scripts and generating the results are performed automatically by test automation tools.
13 hours ago · Automatic assessment of impairment and disease severity is a key challenge in data-driven medicine. We propose a framework to address this challenge, which leverages AI models trained exclusively ...
