US 12,423,080 B1
Dynamic test publication framework for software development
William Michael Webb, San Antonio, TX (US); Bryan J. Osterkamp, New Braunfels, TX (US); Shiloh Huff, San Antonio, TX (US); Clay Williams, Boerne, TX (US); and Michael Lynn Edwards, San Antonio, TX (US)
Assigned to United Services Automobile Association (USAA), San Antonio, TX (US)
Filed by UIPCO, LLC, San Antonio, TX (US)
Filed on Apr. 28, 2022, as Appl. No. 17/731,481.
Int. Cl. G06F 8/65 (2018.01); G06F 11/3668 (2025.01)
CPC G06F 8/65 (2013.01) [G06F 11/3688 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for implementing software development updates using dynamic test publishing, the method comprising:
receiving test results from a plurality of software tests run by one or more test tools, wherein the test results are converted to a tool agnostic format by one or more adaptors;
generating, by one or more producer elements, a stream of test results data objects using the received test results;
queuing the stream of test results data objects in one or more queues;
publishing, by one or more publisher elements, test results contained in the queued test results data objects to a test evidencing platform using an application programming interface of the test evidencing platform, wherein the published test results are part of a software update for a software product;
predicting, by a trained machine learning model, one or more scaling thresholds,
wherein the trained machine learning model is trained via training data comprising observed states that caused overload conditions, and
wherein the predicted one or more scaling thresholds comprise one or more of: a publishing rate threshold with respect to test results published by the publisher elements to the test evidencing platform, a queue size rate of change threshold, a threshold for a number of software product updates open at a given time, or any combination thereof;
monitoring a state of one or more of the producer elements, queues, publisher elements, test evidencing platform, or a combination thereof; and
dynamically scaling, based on comparing the monitored state to the one or more scaling thresholds, one or more of: a number of producer elements, a size of the one or more queues, a number of publisher elements, or a combination thereof.