International Business Machines Corporation

Kyndryl, Inc.

Green Market Square Limited

Globalfoundries Inc.

Marco Aurelio Stelmar Netto

Marcos Dias De Assuncao

Renato Luiz De Freitas Cunha

Bruno Silva

Vagner Figueredo De Santana

Sergio Varga

Carlos Henrique Cardonha

Christopher Charles Young

Lucas Correia Villa Real

Fernando Luiz Koch

Lakshminarayanan Renganarayana

Gray Franklin Cannon

Thiago Cesar Rotta

Priscilla Barreira Avegliano

Takashi Imamichi

Silvia Cristina Sardela Bianchi

Igor Cerqueira Oliveira

Jørgen E Borup

Kris Blöndal

Aaron K Baughman

Rudy Raymond Harry Putra

Eduardo Rocha Rodrigues

Victor Fernandes Cavalcante

Kiran Mantripragada

Ricardo Guimaraes Herrmann

Renan Francisco Santos Souza

Thiago Rodrigues De Souza Costa

Paulo Henrique Paulin

Bruno Flach

Marcos D De Assuncao

Cleidson Ronald Botelho De Souza

Silvia Christina Sardela Bianchi

Maira A De C Gatti

Roberto Guarda

Marcio Rogerio Luccas

Carlos Demetrio De Souza

Cesar Penna Santana

James R Kraemer

Eli M Dow

Jaione Tirapu Azpiroz

John Joseph Rofrano

Ricardo Luis Ohta

Brian L Peterson

Andrea Britto Mattos Lima

Thiago Bianchi

Raymond Harry Rudy

Campbell D Watson

Marisa Affonso Vasconcelos

Maira Athanazio De Cerqueira Gatti

Heloisa Caroline De Souza Pereira Candello

Alan Braz

Emilio Ashton Vital Brazil

Marcos De Castro Sylos

Bruno Da Costa Flach

Daniela Trevisan

Marcos Vinicius Landivar Paraiso

Lakshminaraya Renganarayana

Nelson Mimura Gonzalez

Thiago Roberto Fontes Iunes

Diego P R Franco

Sara Perelman

Maciel Zortea

Maysa Malfiza Garcia De Macedo

Alexandre De Queiroz Baltar

Daniel Neves Zanon

Matheus Bitencourt Rangel Dantas

Danne Meira Castro Aguiar

Ana Paula Brambila

Priscila Vieira De Sousa

Wiliam Pereira Righi

Ashraf Ali Thajudeen

Juliana Medeiros Destro

Marcelo Fernandes De Oliveira

Livia Moreno De Marco Cantieri

Jose Soares Junior

Ricardo Ferrareto Jayme

Clayton Ceragioli Junior

Rodrigo Jungi Suzuki

Yankel Schwartz

Claudio Einicker Garrido

Eric Bueno Gauch

Bruno Estima Correia Milanesi Castanhe

Nilo Freitas De Resende

Elias De Carvalho, Jr

Maryana Zanetti

Daniel De Castro Netto

Jyulian Kyohei Kuroba Kumeda

Paulo Cesar Pinto Calabria

Thamy Telles Do Nascimento

Christian Elias Tanajura Goulart

Facundo Miguel Oliveri

Fabio Luis Marras

Antonio Fernando Gaspar Santos

Robertson Pinto Dias Junior

Niemeyer Souza Barbosa

Juliano Rodovalho Macedo

Fernando Padia Junior

William Pereira

Naaliel Vicente Mendes

Aspects of the invention include correlating a context of a written data privacy requirement with a first code segment of a source code of a target computer system. A selection of a first candidate code segment is received to replace the first code segment. The selected first candidate code segment is determined to have replaced the first code segment and is integrated into the source code. A stimulation signal is transmitted to the target computer system, wherein the stimulation signal is directed toward the first candidate code segment integrated into the source code.

Compliance adaption plans and software component matchmaking

A method of data transformation for acceleration of context migration includes monitoring user actions in a source code development environment using fragment-based source code documents are monitored. A content of each fragment of the source code document is determined. A sequence of execution of the fragments is determined. A status of a project captured by the source code development environment is determined. A fidelity of the data to be transformed to a new execution environment is determined. Upon determining that a new execution environment is warranted based on the determined fidelity, the new execution environment is determined. The one or more fragments are then executed in the new execution environment.

Data transformation for acceleration of context migration in interactive computing notebooks

A customized video stream is provided. A second content is searched for that includes the plurality of entities, and a plurality of user data associated with the social media account. A hierarchy of additional content is generated based, at least in part, on the second content that is associated with the plurality of entities, and the user data associated with the social media account, wherein the hierarchy of additional content contains a plurality of second content. A customized video stream is generated based, at least in part, on the video stream and the hierarchy of additional content. The customized video stream is populated on a display screen of the user device, wherein the video stream is displayed on the display screen of the user device, and the hierarchy of additional content is displayed in a portion of the display screen and displayed concurrently with the video stream.

Video annotation based on social media trends

A method, computer system, and a computer program product for a dynamic machine functionality is provided. The present invention may include setting a threshold for a machine. The present invention may include setting one or more features of the machine available to a user based on the set threshold. The present invention may include determining the machine is being operated. The present invention may include collecting a plurality of data based on the machine operation. The present invention may include transmitting the plurality of data to a machine learning (ML) module. The present invention may include analyzing the collected plurality of data using the ML module. The present invention may include determining that at least one machine functionality of the one or more features should be adjusted based on analysis of the collected plurality of data. The present invention may include adjusting the at least one machine functionality.

Auto-adjustable machine functionality using analytics of sensor data

According to one embodiment, a method, computer system, and computer program product for adaptive surrogate modeling is provided. The embodiment may include capturing a plurality of system information for a smart Internet of Things (IoT) device. The embodiment may also include calculating a lifespan value of the smart IoT device based on the plurality of captured system information. The embodiment may further include, in response to the calculated lifespan value being below a threshold and a surrogate model fitting one or more parameters of the smart IoT device not existing, creating the surrogate model for the smart IoT device. The embodiment may also include deploying the created surrogate model to the smart IoT device through an update transmission.

Device lifetime-aware creation of customizable surrogate-based models

One or more processors may detect that an extreme event that occurred in a first region. One or more processors may determine that the extreme event creates a drift in a probability distribution that is an output of a model associated with the first region. One or more processors may retrain the model associated with the first region using data associated with the extreme event. One or more processors may identify a second region similar to the first region according to a defined correlation threshold. One or more processors may generate data representing potential extreme scenarios for the second region based on the detected extreme event in the first region. One or more processors may retrain a model associated with the second region based on the generated data representing potential extreme scenarios.

Recalibration of risk related models impacted by climate

A collection of code fragments loaded in an interactive development platform for running on a first processor can be received. A candidate fragment in the collection of code fragments can be determined for migration to a second processor based on characterizing the collection of code fragments. Based on a location of the candidate fragment in the collection of code fragments, a spot can be identified in the collection of code fragments to inject a code for saving program context. The code for saving program context can be injected in the identified spot. Responsive to the code for saving program context having run on the first processor and based on a criterion, the program context can be migrated to the second processor.

Program context migration

A method of conducting computing experiments includes executing a set of jobs based on user-selected parameters, learning a user strategy by checking the user-selected parameters during the executing of the set of jobs, and refining the user strategy by refining the set of jobs.

System and method for conducting computing experiments

A computer-implemented method includes receiving, by a processing system, a user story for developing software. The processing system characterizes the user story to determine a plurality of attributes. The processing system classifies a complexity of the user story associated with the attributes. The processing system determines a history score of the user story based on a similarity of one or more previously analyzed user stories having a similar complexity. The processing system recommends one or more modifications to the user story to increase alignment of one or more attributes of the user story with the one or more previously analyzed user stories.

Software development automated assessment and modification

A method can include determining by photogrammetry, a first volume of a food-product unit and a second volume of a food-product subunit. The food-product subunit can be a separated portion of the food-product unit. The method can further include generating a code for the food-product subunit. The code can include a first identifier for the food-product unit and a second identifier for the food-product subunit. The first identifier can be based, at least in part, on the first volume. The second identifier can be based, at least in part, on the second volume. The method can further include assigning the code to the food-product subunit.

Food-product tracking by photogrammetry

When human users traverse physical space or traverse computer software, they take 'navigational paths.' Some embodiments of the present invention are directed to machine logic for identifying a favorable navigation paths by monitoring physical or computer software navigation paths used by human users as they use a set of computer program(s). This favorable navigation path, through physical space or the logic of the set of computer program(s), can then be suggested to future users who want to navigate from a similar starting point to a similar end point.

Tracking computer user navigations to generate new navigation paths

A processor may receive data regarding a reference source code commit. The processor may identify, using an artificial intelligence model, a first group of source code commits including source code commits similar to the reference source code commit, where each source code commit in the first group is associated with a repository. The processor may determine, using the artificial intelligence model, a first risk associated with implementing a first source code commit from the first group of source code commits. The processor may determine an error budget associated with a first repository associated with the first source code commit. The processor may determine a first time for implementing the first source code commit.

Coordinated source code commits utilizing risk and error tolerance

Aspects of the invention include receiving a first instructional video describing a first method of using a function of a first software application; determining each step of the first method described in the first instructional video; determining, by the processor, a second method of using a first function of a second software application, wherein the first function of the first software application is substantially the same as the first function of the second software application; and creating a second instructional video describing each step of the second method.

Automatic creation and annotation of software-related instructional videos

Described are techniques for application migration. The techniques include migrating an application to a target cloud infrastructure and generating a cost-aware code dependency graph during execution of the application on the target cloud infrastructure. The techniques further include modifying the application by removing source code corresponding to unused nodes according to the cost-aware code dependency graph and replacing identified source code of a high-cost subgraph of the cost-aware code dependency graph with calls to a generated microservice configured to provide functionality similar to the identified source code. The techniques further include implementing the modified application on one or more virtual machines of the target cloud infrastructure.

Application migration using cost-aware code dependency graph

A computer-implemented method, system and computer program product for generating test cases for testing software. Log files are analyzed for indications of software defects resulting in software errors. For those log files that were found to indicate software errors, such log files are analyzed to determine if they contain personal data that needs to be anonymized based on an entropy score of the personal data. When the entropy score of the personal data is below a threshold value, anonymized variations of the personal data are generated. Trace logs are then created containing the anonymized variations of the personal data, which are returned to a software tester to create a test case for testing software using the created trace logs without having access to personal data. In this manner, the software tester may reproduce the software errors without having access to the personal data.

Creating test cases for testing software using anonymized log data

Growing community of inventors

Sao Paulo, Brazil

Marco Aurelio Stelmar Netto