Patent ID: 11960383
Assignee: AKILI INTERACTIVE LABS, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 13:
14. A non-transitory computer-readable medium encoded with instructions for commanding one or more processors to execute operations for software quality assurance, the operations comprising:
presenting a user interface comprising an instance of a software build to a user via a user computing device, wherein the software build comprises at least one feature comprising one or more computerized stimuli or interactions configured to elicit an expected stimulus-input pattern from the user in response to the one or more computerized stimuli or interactions,
wherein the expected stimulus-input pattern comprises a clinically validated stimulus-response pattern for treating or targeting one or more neurological, psychological and/or somatic condition in the user;
receiving a plurality of user activity data for a session of the software build, wherein the plurality of user activity data comprises a plurality of user inputs in response to the one or more computerized stimuli or interactions within the instance of the software build;
communicating, via a network communications protocol comprising an application programming interface, the plurality of user activity data from a first server communicably engaged with the user computing device to a second server, wherein the first server comprises a software development subsystem server and the second server comprises a design control sub system server;
receiving, at a classification module executing on the second server, the plurality of user activity data, wherein the classification module is communicably engaged with a design control subsystem database via a simple notification service or a simple queue service, wherein the design control subsystem database is configured to store the plurality of user activity data;
processing, via the classification module executing on the second server, the plurality of user activity data to determine one or more actual stimulus-input patterns for each user input in the plurality of user inputs, wherein the classification module comprises a computer-implemented machine learning framework comprising an ensemble learning model or a supervised learning model configured to classify one or more variables between the user activity data and the clinically validated stimulus-response pattern,
wherein the classification module is configured to calculate a degree of conformity between the one or more actual stimulus-input patterns and the clinically validated stimulus-response pattern for treating or targeting the one or more neurological, psychological and/or somatic condition in the user;
comparing the one or more actual stimulus-input patterns for each user input in the plurality of user inputs to the expected stimulus-input pattern for the at least one feature to determine a total number of instances in which the one or more actual stimulus-input patterns was reflective of the expected stimulus-input pattern within the session of the software build;
calculating at least one output value for the plurality of user activity data according to the classification module, wherein the at least one output value comprises a qualitative or quantitative degree of conformity between the one or more actual stimulus-input patterns and the expected stimulus-input pattern for the at least one feature;
calculating a measure of net therapeutic activity within the session of the software build according to the total number of instances in which the one or more actual stimulus-input patterns was reflective of the expected stimulus-input pattern within the session of the software build; and
determining a pass/fail status for the software build according to the at least one output value and the measure of net therapeutic activity within the session of the software build,
wherein determining the pass/fail status comprises determining a minimum performance threshold for the session of the software build,
wherein the minimum performance threshold comprises a minimum degree of conformity between the one or more actual stimulus-input patterns and the clinically validated stimulus-response pattern for treating or targeting the one or more neurological, psychological and/or somatic condition in the user, and
wherein the minimum performance threshold comprises a minimum measure of therapeutic activity delivered to the user within the session of the software build.