Tristan A Tenyenhuis

US Patent:

20090217103, Aug 27, 2009

Filed:

Feb 26, 2008

Appl. No.:

12/037142

Inventors:

MARIO L. BORELLI - Highland NY, US
Justin M. Spotts - Ulster Park NY, US
Tristan A. Tenyenhuis - Poughkeepsie NY, US

Assignee:

INTERNATIONAL BUSINESS MACHINES CORPORATION - ARMONK NY

International Classification:

G06F 11/00

US Classification:

714 43, 714E1102

Abstract:

A method, information system, and computer readable storage medium verify predefined connectivity for I/O devices. Current predefined logical connection data and actual physical connection data is gathered. The predefined logical connection data and the actual physical connection data are formatted into a plurality of sortable tables. At least a portion of the predefined logical connection data is formatted into a predefined channels table and at least a portion of the actual physical connection data is formatted into a node information table. The portion of the predefined logical connection data is compared with the portion of the actual physical connection data. The portion of the predefined logical connection data is determined to substantially match/not match the portion of the actual physical connection data. At least one predefined logical connection associated with the predefined logical connection data that fails to substantially match the actual physical connection data is displayed to a user.

US Patent:

20200327134, Oct 15, 2020

Filed:

Apr 11, 2019

Appl. No.:

16/381725

Inventors:

- Armonk NY, US
Tristan A. TeNyenhuis - West Islip NY, US
Keith D. Cramer - Pine Island MN, US
Sorabh Murgai - Cary NC, US

International Classification:

G06F 16/2457
G06F 17/27
G06F 16/22
G06F 16/28
G06F 16/242

Abstract:

A method, system, and apparatus are provided for recommending machine learning (ML) project resources for completing a user project by generating indexed project metadata for a plurality of ML projects, generating search metadata for a search request for ML project resources to develop an ML project, and then evaluating the search metadata against the indexed project metadata for each ML project to form a relevancy assessment which is used to order trained models from the ML projects and to display one or more recommended ML project resources comprising one or more of the plurality of trained models having a relevancy assessment exceeding a relevancy threshold.

US Patent:

20200210258, Jul 2, 2020

Filed:

Mar 10, 2020

Appl. No.:

16/813831

Inventors:

- Armonk NY, US
Andrew R. Freed - Cary NC, US
Tristan A. TeNyenhuis - West Islip NY, US

International Classification:

G06F 9/54
G06F 16/953

Abstract:

Provided is a validation framework for modelling possible failures that might occur when an orchestrated transaction calls external services to ensure that error handling and reporting is robust and well designed. The disclosed techniques ensure that no changes are necessary to either the code making a call or the services that might be called. The techniques are not limited to web servers and REST APIs as they may be used to test and validate any kind of system that employs well defined APIs. The claimed subject matter, or “validation framework” may be added to an existing API or created as a new module that acts as a proxy server in a non-micro service type of system. Although described with respect to a gateway-API service, the claimed subject matter is equally applicable to other systems that process orchestrated transactions.