International Business Machines Corporation

Wells Fargo Bank, N.a.

Accenture Global Solutions Limited

Vivek Shyamlal Sharma

Vijay Ekambaram

Ashish Kumar Mathur

Vikrant Nandakumar

Nitendra Rajput

Sachidanand Mangala Basavanna

Brian John Cragun

Shunguo Yan

Vijay Kumar Ananthapur Bache

Puthukode G Ramachandran

Naveen Gururaja Yeri

Jhilam Bera

Vikas Raykar

Abhishek Datta Sharma

Jayanthi Mohanram

Dipanjan Deb

Nupur Aggarwal

Anil Vohra

Surya Shravan Kumar Sajja

Arun Srinivasan

Amol Deshpande

Prateek Shah

Mani Gupta

Palaniappan Ganesh Kumar

Prasanna Kulkarni

Varsha Ajit Shrikhande

Methods, systems, and computer program products for determining locations for offerings using artificial intelligence are provided herein. A computer-implemented method includes determining an initial sub-set of one or more enterprise locations, from a set of multiple enterprise locations, for providing at least one enterprise offering; determining at least one sequential ordering of one or more additional ones of the multiple enterprise locations for providing the at least one enterprise offering by processing data related to the initial sub-set of one or more enterprise locations using an artificial intelligence engine that utilizes one or more artificial intelligence techniques; and automatically training at least a portion of the artificial intelligence engine that utilizes the one or more artificial intelligence techniques based at least on feedback data pertaining to provision of the at least one enterprise offering to the at least one sequential ordering of one or more additional enterprise locations.

Determining locations for offerings using artificial intelligence

Sharing of user data of customers of a first party with a third party is monitored. The data is presented to customers to enable transparency with respect to what data is provided to whom. Furthermore, remediation is promptly triggered in response to a third-party data breach. After breach detection, customers and data affected by the breach is determined. The type of remediation is determined based on the risk as determined based on the customers affected by the data involved.

Data breach monitoring and remediation

A device may receive source data identifying source enterprise software and may process the source data to determine field mapping data. The device may process the source data, with a first model, to determine implementation guide data identifying implementation guides, and the device may convert data configurations from the source data to target data configurations. The device may generate transport request management data for the target enterprise software based on the source data and the implementation guide data and may process the source data and the implementation guide data, with a second model, to determine copy functionality data identifying functionality of the source enterprise software to be copied. The device may process the source data, with a third model, to determine consolidation data identifying the source data to be consolidated and may configure the target enterprise software, based on the determined data, to generate configured target enterprise software.

Utilizing models for replacing existing enterprise software with new enterprise software

An object detection algorithm is selectively applied to frames in a video. A frame in the video is analyzed using a set of neural networks of the object detection algorithm to detect a location of an object in the frame and predict a bounding box for the object in the frame. A magnitude of a delta between the frame and a second frame is determined. The magnitude of the delta is determined based on a difference between the two frames in values of at least one parameter of their respective sets of pixels. Responsive to the magnitude of the delta being less than a threshold, a new bounding box is predicted for the object in the second frame without analyzing the second frame using the set of neural networks.

Non-resource-intensive object detection

In response to a posting of a negative review of an information technology item, external environmental context data is collected that comprehends processing environment attributes of an external process that interacts with the item in a reviewed performance of the item. An attribute of the item criticized in the review is correlated with an attribute of the external environmental context data as a function of contemporaneous time of occurrence. Degrees of likelihood as the principal cause of the negative review are determined for the attributes of the information technology item and for the correlated external environmental context data attribute. The negative review is determined to be a false negative review if the degree of likelihood that the correlated attribute of the external environmental context data is the principal cause is higher than the degree of likelihood that the criticized attribute of the information technology item is the principal cause.

Automated review validator

Identification and dynamic ranking of performance issues. For an instance of a performance anti-pattern, identifying and recording information relating to a resultant performance issue, quantifying the magnitude of the performance issue, and dynamically ranking the performance issue against other performance issues.

Dynamic ranking of performance issues for applications

Methods, systems, and articles of manufacture for automatically fixing inaccessible widgets during mobile application execution are provided herein. A method includes identifying an image element from a set of one or more user interface elements of an application that are inaccessible to a given set of users; generating a text description associated with the image element; extracting a portion of the text description related to an accessibility property of the image element; and adjusting the accessibility property of the image element to render the image element accessible to the given set of users.

Automatically fixing inaccessible widgets during mobile application execution

Mobile application reviewing is provided. An interaction, made by a user of a wearable device is identified. One or more facial expression data is received. A screenshot of a mobile application on a mobile device is captured. A user sentiment, corresponding to the screenshot, is determined, wherein the sentiment is based on the facial expression data. A mobile application rating corresponding to the user is determined wherein the mobile application rating is based on one or more screenshot ratings corresponding to the user.

Rapid cognitive mobile application review

A method for monitoring software application performance and one or more device states affecting a software application on a periodic basis on a mobile device. The method includes one or more computer processors identifying a software application on a mobile device. The method further includes the one or more computer processors identifying a plurality of sampling plans and one or more respective triggers within the plurality of sampling plans that are respectively associated with the software application and are stored on the mobile device. The method further includes the one or more computer processors determining a first value associated with the one or more respective triggers. The method further includes the one or more computer processors selecting a first sampling plan from the plurality of sampling plans for the software application based, at least in part, on the value associated with the one or more respective triggers.

Sampling of device states for mobile software applications

In an approach to test automation of an application under test which interacts with one or more native stock applications, a computer identifies one or more native stock applications on a mobile computing device. The computer then dumps a view hierarchy for each of the one or more native stock applications. The computer generates, based, at least in part, on the view hierarchy, a template table for each of the one or more native stock applications.

Functional test automation of mobile applications interacting with native stock applications

An application for testing is determined. A test script associated with the application for testing is determined. The application is tested using the test script. The testing requires transferring data form the application to an out-of-band channel.

Application test automation transmitting data via phone/voice calls

Methods and arrangements for testing mobile applications. A mobile application for testing is input at a mobile device. The mobile application is automatically tested using a test script, wherein the testing requires data from an out-of-band channel. The testing includes: invoking a listener module based on the mobile application; using the listener module to automatically obtain data from an out-of-band channel; and communicating the automatically obtained data to the mobile application. Other variants and embodiments are broadly contemplated herein.

Growing community of inventors

Bengaluru, India

Vivek Shyamlal Sharma