Patent ID: 11893363
Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 6:
7. A method performed by one or more computing devices, comprising:
pre-training a neural transformer model with attention with a first unsupervised training dataset comprising a plurality of sequences of natural language text to learn semantic relationships of a natural language;
pre-training the neural transformer model with attention with a second unsupervised training dataset comprising a plurality of sequences of source code to learn syntax of a programming language and semantic relationships of code elements of the programming language;
fine-tuning the neural transformer model with attention with a supervised training dataset to learn to generate a unit test case fora given focal method written in the programming language, wherein the supervised dataset comprises mapped unit test case pairs, wherein a mapped unit test case pair of the mapped unit test case pairs comprises a first focal method and an associated unit test case written in the programming language, wherein fine-tuning the neural transformer model with attention with the supervised training dataset is a translation task with a training objective that learns a mapping of a focal method to a unit test case, fmi→tci, as a conditional probability P(tci, fmi); and
deploying the neural transformer model with attention to automatically predict a unit test case fora given target method of a source code program.