DataRobot. has been granted a patent for a system that utilizes machine learning to assess application performance. The system identifies changes in application versions, scores potential tests without execution, and selects a subset of tests for evaluation prior to deployment, enhancing efficiency in performance testing. GlobalData’s report on DataRobot gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on DataRobot, Predictive modeling techniques was a key innovation area identified from patents. DataRobot's grant share as of July 2024 was 37%. Grant share is based on the ratio of number of grants to total number of patents.
Machine learning-based performance testing for application versions
The granted patent US12072792B2 outlines a sophisticated system designed to enhance the performance testing of application versions prior to their deployment. The system comprises a data processing unit equipped with memory and processors that execute a series of operations upon receiving a performance testing request. Key functionalities include identifying relevant data from repositories that highlight changes between the current and previous application versions, and utilizing a machine learning model trained on historical data to assign performance scores to various tests without the need for executing all tests. Based on these scores, the system selects a subset of tests for execution, thereby streamlining the performance evaluation process.
Additionally, the patent details operations that involve the use of a graphical user interface (GUI) for user interaction, allowing requests to be submitted remotely and results to be communicated back effectively. The system can analyze various data types, such as pull request data and issue tracker information, to generate features that inform the scoring process. It also includes mechanisms for grouping tests based on their scores relative to predefined thresholds, enabling differentiated actions for test execution or skipping. This approach not only optimizes resource utilization but also enhances the efficiency of the application performance testing process, ensuring that only the most relevant tests are conducted prior to deployment.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
