Device, system and method for implementing a recurrent neural network to determine a given region of a build log that meets a fatal error criterion condition

A computing device comprising:

• a controller;
• and
• a computer-readable storage medium having stored thereon program instructions that, when executed by the controller, cause the computing device to perform a set of operations comprising:
• training a recurrent neural network (RNN), using a balanced dataset, to predict whether logs input to the RNN are indicative of respective successful computer code or respective failed computer code, the balanced dataset comprising positive log examples and negative log examples from a continuous integration (CI) pipeline, the positive log examples labelled as being indicative of successful computer code, and the negative log examples labelled as being indicative of failed computer code;
• inputting a log to the RNN;
• monitoring evolution of belief predictions of the RNN, as the RNN is analyzing the log, according to successive regions of the log;
• determining, based on the evolution of the belief predictions, that a given region of the log meets a log fatal error criterion condition;
• and
• outputting an indication of the given region.