International Business Machines Corporation

Josephine E Justin

Srinivasan Nanduri

Kuntal Dey

Seema Nagar

Jayakarthik Jayabalan

Saritha Vinod

Pidad G D'Souza

Anto A R John

Norton Samuel Augustus Stanley

Cheranellore Vasudevan

Shinoj Zacharias

Girish Dhanakshirur

Naga A Ayachitula

Rajeev Puri

Badekila Ganesh Prashanth Bhat

Srikanth K Murali

Kenneth David Christiance

Ajay Chebbi

Peter M Jensen

Ann M Moyer

Lisa Nayak

Chetna Dnyandeo Warade

Robert A Larsen

Vijaya Jas

Geet Manghnani

A method includes receiving, by one or more processors of a computer system, source code, annotating, by the one or more processors of the computer system, features of the received source code using an automated annotation system to provide annotations for the features, relating, by the one or more processors of a computer system, a code execution path of the source code to the features during the annotating, identifying, by the one or more processors of the computer system, a runtime issue associated with the source code, identifying, by the one or more processors of the computer system using a code analytic engine, one or more of the features based on the annotations that are associated with the runtime issue, and automatically disabling, by the one or more processors of the computer system, the identified one or more features associated with the runtime issue.

Intelligent automated feature toggle system using annotations

In an approach, a processor receives a report of a push notification identified as spam. A processor determines that a threshold number of push notifications identified as spam has been exceeded. A processor, responsive to determining that the threshold number of push notifications identified as spam has been exceeded, performs an action with respect to a sender of the push notification.

Channel to report push notifications as spam

One or more processors compile user preference and activity information associated with a mobile device operated by the user. The installation of a first application (app) on the mobile device operated by the user is confirmed. Responsive to detecting availability of an update to the first application, and confirmation accepting installation of the update, dynamically embedding a message within a new feature included in the update of the first application. A message is selected from one or more available messages to dynamically embed within the new feature included in the update of the first application, based on profile and activity information collected about the first user, and responsive to receiving a confirmation to receive the update of the first application, the message selected from the one or more available messages, is presented to the user, embedded within the new feature of the update to the first application.

Dynamic message embedded within application new feature rollout

Systems and methods for calculating and displaying implicit popularity of products are disclosed. In embodiments, a computer-implemented method, comprises: determining, by a computing device, a set of consumer actions related to a product based on recorded consumer interaction data, wherein the set of consumer actions comprise a plurality of different physical actions of multiple consumers over a span of time; aggregating, by the computing device, the set of consumer actions by type of physical action over time to produce aggregated action event data; calculating, by the computing device, an implicit popularity number for the product based on the aggregated action event data; and sending, by the computing device, a display category to a product display device associated with the product based on the implicit popularity number, wherein the display category represents a measure of consumer popularity of the product.

Calculating and displaying implicit popularity of products

A method and system are provided for data synchronization. The method includes registering, in a database accessible by nodes in a cloud cluster system, node information for each node during an initialization of an application context for an application having at least one instance running on each node. The method further includes storing an update for data in (i) a local storage of a given one of the nodes and (ii) the database, responsive to a request to update the data received by the given one of the nodes. The method also includes generating a modified request that includes details for the updated data. The method additionally includes calling an application programming interface to update a state of respective local storages for the other nodes with the update responsive to the modified request, such that the update is synchronized across the at least one instance running on each node.

Synchronizing data across multiple instances of an application in a cloud

A method displaying a theme-based push notification on a mobile device. The method includes registering a mobile device, wherein registering includes receiving, by an application backend server, a registration token from the mobile device, and storing the received registration token. The method further includes participating in dissemination of at least one theme-based push notification template, wherein participating in dissemination includes transmitting, by the application backend server, at least one theme-based push notification template to the registered mobile device. The method further includes processing a push notification together with the at least one theme-based push notification template, wherein the processing includes generating payload information, by the application backend server, and transmitting the payload information with the push notification to the registered mobile device.

Theme-based push notifications

Aspects of the present invention disclose a method, computer program product, and system for providing push notifications to an active device of a user. The method includes one or more processors identifying a push notification for distribution to at least a first user, wherein the first user is associated with at least two computing devices. The method further includes retrieving historical push notification interaction information that includes data of the first user dismissing push notifications on the at least two computing devices and the first user opening push notifications on the at least two computing devices. The method further includes determining a prediction of an active computing device, of the at least two computing devices, for the first user based on the retrieved historical push notification interaction information. The method further includes the push notification to the predicted active computing device of the first user.

Intelligent distribution of push notifications

Generating reports. The method may include receiving, by a computer, data associated with a meeting. The method may include converting the received data to audio text data, digital text data, and graphical object data. The method may include identifying tokens associated with the converted audio text data, the converted digital text data, and the converted graphical object data. The method may include integrating each token corresponding to timeline data, positional data, and structural data. The method may include creating semantic correlations by connecting tokens associated with the converted audio text data and tokens associated with the converted digital text data. The method may include associating each of the integrated tokens with a semantic correlation based on the timeline data. The method may include creating a report outline based on the received data. The method may include creating an integrated report using the created report outline and the associated tokens.

Generating structured meeting reports through semantic correlation of unstructured voice and text data

An approach is provided for tuning middleware. Performance-related settings are loaded. Performance data of the middleware of a MobileFirst Platform (MFP) running in a docker container infrastructure is received. The performance data is collected by agents installed in container groups. Based on the performance data, a performance issue in one of the container groups is identified and a server included in the one container group is identified as a source of the performance issue. Recommendations are generated for tuning the middleware by modifying one or more of the performance-related settings. While the middleware is running in the docker container infrastructure, one of the recommendations is applied to modify one of the performance-related settings which dynamically tunes the middleware, thereby resolving the performance issue.

Automatically tuning middleware in a mobilefirst platform running in a docker container infrastructure

A method, system, and article for autonomizing autonomic management of a data center, with the data center having at least one computer system and an associated component. Data is collected from the data center and used as input to identify a data center policy. A set of capabilities of elements of the data center are detected and cataloged based upon the collected data. At least one policy is dynamically selected from at least one set of master policies in a policy directory with the selected policy to support the cataloged capabilities of the data center, and to dynamically control selective application and to adapt parameters for quality of service. The selected policy is applied to manage the data center.

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Bengaluru, India

Josephine E Justin