IDENTIFYING POTENTIAL ERRORS IN CODE USING MACHINE LEARNING

A method, system and computer program product for identifying potential errors in a software product after it is built but prior to release. Negative log reports of previously-build software products containing errors in the code in connection with building these software products are identified. The language of the negative log reports is then vectorized and the vectorized negative log reports are then stored. After vectorizing the language of a build log report upon completion of a build of a software product, the vectorized log report is compared with the stored vectorized negative log reports. The release of the software product will then be halted and the programmer will receive a copy of the negative log report associated with the vectorized negative log report closest in distance to the vectorized log report if the vectorized log report is within a threshold amount of distance to a stored vectorized negative log report.