International Business Machines Corporation

Jeffrey Willoughby

Dinesh C Verma

John Richard Dangler

Marc Henri Coq

Richard Burton Finch

Edward C McCain

Chanchal Saha

Shrey Shrivastava

Kanayo Okonji

Yuanchen Hu

Jeffrey Nettey

Shuxin Lin

Emily Wise

Milcah Ntende

Barin Bhattacharya

Andrew Cm Hicks

Donald Thomas

Kevin Randolph

In accordance with a technique of parallelized computer system testing, a processor develops, on a representative computer system, a plurality of groups of system tests based on test-ordering constraints, where the system tests in each of the plurality of groups are executable in a temporally overlapping manner. The processor applies a test suite including a sequence of multiple of the plurality of groups of system tests to a production computer system. Applying the test suite includes performing the system tests in each of multiple of the plurality of tests groups in a temporally overlapping manner, such that testing efficiency is improved.

Computer system test parallelization

An apparatus includes circuitry configured to maintain a record of a plurality of owners and at least one test operation owned by an owner; prompt automatically the owner in response to a failure of the one test operation; maintain a log of actions taken on the one test operation, and provide availability to the log of actions; update an estimated time to completion, and notify a management entity of the updated estimated time to completion; mark and prioritize an order related to the one test operation, in response to the estimated time to completion being within a threshold of a delivery date; rank the marked order with other marked orders by a risk of not being able to meet the delivery date; and notify the owner of the ranking with an urgent message, in response to the marked order failing to meet the delivery date.

Method and system for enhancing orchestration and automating communication between teams during IT systems testing

Aspects of the invention include detecting an anomaly in a database of hardware, firmware, and software events. An exemplary method includes determining whether a previously addressed anomaly is a duplicate of the anomaly, addressing the anomaly according to a state of the previously addressed anomaly based on the previously addressed anomaly being a duplicate of the anomaly, and addressing the anomaly according to machine learning based on the previously addressed anomaly not being the duplicate of the anomaly.

Hardware, firmware, and software anomaly handling based on machine learning

Restricting use of a selected input in recovery from system failures. A testing system obtains, based on failure of a system, an indication of one or more tasks to be performed. The testing system automatically determines whether a user is to perform one or more actions to alter execution of the one or more tasks. The automatically determining is based on an indication of whether a knowledge transfer score of the user meets at least one predefined criterion. Based on knowledge transfer score meeting the at least one predefined criterion, the one or more actions are performed.

Restricting use of selected input in recovery from system failures

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Poughkeepsie, NY, United States of America

Jeffrey Willoughby