ANALYZING SOFTWARE TEST FAILURES USING NATURAL LANGUAGE PROCESSING AND MACHINE LEARNING

Patent №

US 11,226,892

Granted

2022-01-18

Filed 2020

Owner

INTERNATIONAL BUSINESS MACHINES CORPORATION

AI components

4

ml · nlp · planning · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

17073501

According to an aspect, software test failures are analyzed using natural language processing (NLP) and machine learning. A failure is detected during a code build associated with a software product. Each change set since a last successful code build associated with the software product is identified and analyzed using NLP to extract change set features. A software defect origin model is applied to the extracted features in each analyzed change set to detect an origin of the failure.

Machine learningNatural languagePlanningAI hardwareG06F 11/3688G06F 11/3692G06F 40/194G06F 40/279

AI classification

Natural language1.00
Machine learning1.00
Planning1.00
AI hardware0.99
Knowledge representation0.31
Speech0.26
Evolutionary computation0.07
Vision0.00

Ownership

INTERNATIONAL BUSINESS MACHINES CORPORATION

assignment · 540920293

Assignors

KOCHURA, NADIYA, RAGHAVAN, VINODKUMAR, RANDALL, DONALD H., JR., REEDY, DEREK M., SNOW, TIMOTHY B.

On an employer assignment, the assignors are typically the inventors.

From the same owner

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