US 12,248,393 B2
Automated software testing
Aaron Edward Dietrich, Kirkland, WA (US); Swamy V. P. L. N. Nallamalli, Bothell, WA (US); Timothy James Chapman, Bellevue, WA (US); Steve K. Lim, Redmond, WA (US); Levent Ozgur, Seattle, WA (US); Alex Pung Leung, Bellevue, WA (US); Taylor Paul Spangler, Kirkland, WA (US); and Jareth Leigh Day, Kirkland, WA (US)
Assigned to Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed by MICROSOFT TECHNOLOGY LICENSING, LLC, Redmond, WA (US)
Filed on Sep. 20, 2022, as Appl. No. 17/948,513.
Claims priority of provisional application 63/341,791, filed on May 13, 2022.
Prior Publication US 2023/0367699 A1, Nov. 16, 2023
Int. Cl. G06F 11/36 (2006.01); G06F 11/3668 (2025.01); G06N 3/08 (2023.01); G06N 3/10 (2006.01)
CPC G06F 11/3664 (2013.01) [G06F 11/368 (2013.01); G06F 11/3688 (2013.01); G06N 3/08 (2013.01); G06N 3/10 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method of automated software testing comprising:
receiving action telemetry data describing actions taken on a first version of a software;
receiving state telemetry data describing states of the first version of the software at points in time during testing;
assigning a reward to a specific state within the state telemetry data that satisfies a reward criterion;
identifying events by associating a respective action of the actions and a respective resulting state of the states, the respective resulting state being produced by the respective action;
generating a time-sequence of the events;
identifying, within the time-sequence of the events using natural language processing, an event pattern that produced the specific state; and
storing the event pattern.