Allstate‘s patent involves a computing platform that uses continuous machine learning and integration to automate data-driven testing. It extracts production data, generates scenarios using machine learning, triggers test script execution, and receives results to ensure application performance. The innovation aims to enhance testing efficiency and accuracy. GlobalData’s report on Allstate 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 Allstate, was a key innovation area identified from patents. Allstate's grant share as of April 2024 was 65%. Grant share is based on the ratio of number of grants to total number of patents.
Data driven testing through automation using continuous machine learning
A recently granted patent (Publication Number: US11971813B2) discloses a computing platform designed to enhance the testing process for applications. The platform includes a processor, communication interface, and memory storing instructions that enable the extraction of production data from user interactions with an application. Using machine learning, unique scenarios are generated from this data, which are then executed using a continuous integration tool to test updated versions of the application. The results of these tests determine if the application performs as expected, with scenarios automatically updated with each new version through continuous machine learning.
Furthermore, the platform can perform operations such as masking personally identifiable information from the production data, exploratory data analysis, dimensionality reduction, and data standardization. It also includes features like visual representation of data clusters, simulation of user actions, conversion of data formats suitable for machine learning, and notification of defects found during testing. The method described in the patent involves extracting production data, generating unique scenarios through machine learning, executing these scenarios using a continuous integration tool, and receiving results to assess the performance of updated application versions. The patent also covers applying clustering algorithms, removing personally identifiable information, simulating user actions, and converting data formats, all aimed at improving the testing process for applications.
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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.
