Abstract: One embodiment for determining a marketing incentive for a user of an electronic device. In one embodiment, a computer processor detects a first electronic device within a retail environment utilizing a second electronic device that also identifies information associated with the first electronic device. In one embodiment, a computer processor determines a behavior associated with the first electronic device based, at least in part, on movement of the first electronic device within the retail environment. In one embodiment, a computer processor identifies data associated with the retail environment that includes information associated with a retailer associated with the retail environment and information associated with the first electronic device. In one embodiment, a computer processor determines a first marketing incentive based, at least in part, on the determined behavior associated with the first electronic device and the identified data associated with the retail environment.

Abstract: The method includes receiving, by one or more computer processors, a request for data usage, the request for data usage being associated with a mobile device. The method further includes identifying, by one or more computer processors, a current data usage quantity, the current data usage quantity being associated with the mobile device. The method further includes determining, by one or more computer processors, whether the current data usage quantity is beyond a threshold data usage. The method further includes responsive to the data usage quantity being beyond the threshold data usage, receiving, by one or more computer processors, mobile device information associated with the mobile device. The method further includes analyzing, by one or more computer processors, the mobile device information. The method further includes determining, by one or more computer processors, access for the request based on the mobile device information and the current data usage quantity.

Abstract: The method include receiving, by one or more computer processors, a request for data usage, the request for data usage being associated with a mobile device. The method further includes identifying, by one or more computer processors, a current data usage quantity, the current data usage quantity being associated with the mobile device. The method further includes determining, by one or more computer processors, whether the current data usage quantity is beyond a threshold data usage. The method further includes responsive to the data usage quantity being beyond the threshold data usage, receiving, by one or more computer processors, mobile device information associated with the mobile device. The method further includes analyzing, by one or more computer processors, the mobile device information. The method further includes determining, by one or more computer processors, access for the request based on the mobile device information and the current data usage quantity.

Abstract: Provided are techniques for building and fixing a dynamic application topology. Log files are received from multiple sources comprising any of services and nodes. Information is extracted from the log files. An application topology is created for a particular point in time for an application that provides hierarchical relationships of components for executing the application using the extracted information. One or more problems in the application topology are identified. A solution is applied to each of the one or more problems.

Abstract: A method and system for controlling unwanted phone calls. In response to a determination that a phone number of a current incoming call to a user is not a phone number in a contact list including phone numbers of the user's contacts and to a determination that the phone number of the current incoming call is a phone number in a phone list of a shared table, the shared table for the previous call duration is analyzed for the previous call duration and the previous sentiment of the user during a previous incoming phone call for the phone number of the current incoming call to the user. It is ascertained, from analyzing the shared table for the previous call duration, that the previous call duration is less than a predetermined call duration and the previous sentiment is a negative sentiment, and in response the current incoming call is rejected.

Abstract: A method, system and computer program product for analytically selecting which tests are to be executed in a continuous delivery process. An analytics processing system constructs a code dependency tree to analyze the tests that are affected by changes in code after a new build is generated. After analyzing the code dependency tree, the system eliminates those tests in the code dependency tree that do not depend on the changed code. The system then analyzes the historical execution records for those tests that have not been eliminated for execution to obtain an execution rate and a failure rate for those tests. A score is generated for each of the tests from the code dependency tree that were not eliminated for execution based on the historical execution rate and failure rate of the test. Tests that have a score that exceeds a threshold are included for execution.

Abstract: Systems, methods and tools for leveraging computer networks, data sharing, data analytics and sentiment analysis to control the receipt of unwanted telephone calls and preventing unwanted telephone calls from disturbing a user through the implementation of contacts list and/or a shared table of unique calls. Contact lists and shared tables of unique calls may identify incoming calls that may be directed to the user or filtered out based on whether the incoming call's number is in the user's contact list and/or based on the past experiences of the individual users engaging with the incoming caller. Embodiments may track the past call durations for unique incoming number and track the sentiment of users during these calls and use the collected call data and sentiment determine whether subsequent incoming calls from a phone number should be forwarded to the user's telephone enabled device or automatically responded to with further instructions.

Abstract: Systems, methods and tools for leveraging computer networks, data sharing, data analytics and sentiment analysis to control the receipt of unwanted telephone calls and preventing unwanted telephone calls from disturbing a user through the implementation of contacts list and/or a shared table of unique calls. Contact lists and shared tables of unique calls may identify incoming calls that may be directed to the user or filtered out based on whether the incoming call's number is in the user's contact list and/or based on the past experiences of the individual users engaging with the incoming caller. Embodiments may track the past call durations for unique incoming number and track the sentiment of users during these calls and use the collected call data and sentiment determine whether subsequent incoming calls from a phone number should be forwarded to the user's telephone enabled device or automatically responded to with further instructions.

Abstract: The method include receiving, by one or more computer processors, a request for data usage, the request for data usage being associated with a mobile device. The method further includes identifying, by one or more computer processors, a current data usage quantity, the current data usage quantity being associated with the mobile device. The method further includes determining, by one or more computer processors, whether the current data usage quantity is beyond a threshold data usage. The method further includes responsive to the data usage quantity being beyond the threshold data usage, receiving, by one or more computer processors, mobile device information associated with the mobile device. The method further includes analyzing, by one or more computer processors, the mobile device information. The method further includes determining, by one or more computer processors, access for the request based on the mobile device information and the current data usage quantity.

Abstract: An expert system extracts events associated with executing an application from log files generated by various topological resources in a distributed computing environment. The events are plotted as plot points on a time series graph. Patterns are identified in the plot points that are associated with application problems, along with the computing environment configurations both before the problem and after the problem was resolved. The difference in the configurations represents a corrective action for the application problem, and the expert system links the corrective action to the pattern. When a pattern repeats in conjunction with another application problem, the corrective action is identified as a possible solution to the new problem. A confidence level associated with the pattern/corrective action may be increased when a user accepts the corrective action and may be decreased when a user rejects the corrective action.

Abstract: A method, system and computer program product for analytically selecting which tests are to be executed in a continuous delivery process. An analytics processing system constructs a code dependency tree to analyze the tests that are affected by changes in code after a new build is generated. After analyzing the code dependency tree, the system eliminates those tests in the code dependency tree that do not depend on the changed code. The system then analyzes the historical execution records for those tests that have not been eliminated for execution to obtain an execution rate and a failure rate for those tests. A score is generated for each of the tests from the code dependency tree that were not eliminated for execution based on the historical execution rate and failure rate of the test. Tests that have a score that exceeds a threshold are included for execution.

Abstract: The method include receiving, by one or more computer processors, a request for data usage, the request for data usage being associated with a mobile device. The method further includes identifying, by one or more computer processors, a current data usage quantity, the current data usage quantity being associated with the mobile device. The method further includes determining, by one or more computer processors, whether the current data usage quantity is beyond a threshold data usage. The method further includes responsive to the data usage quantity being beyond the threshold data usage, receiving, by one or more computer processors, mobile device information associated with the mobile device. The method further includes analyzing, by one or more computer processors, the mobile device information. The method further includes determining, by one or more computer processors, access for the request based on the mobile device information and the current data usage quantity.

Abstract: A method, system and computer program product for analytically selecting which tests are to be executed in a continuous delivery process. An analytics processing system constructs a code dependency tree to analyze the tests that are affected by changes in code after a new build is generated. After analyzing the code dependency tree, the system eliminates those tests in the code dependency tree that do not depend on the changed code. The system then analyzes the historical execution records for those tests that have not been eliminated for execution to obtain an execution rate and a failure rate for those tests. A score is generated for each of the tests from the code dependency tree that were not eliminated for execution based on the historical execution rate and failure rate of the test. Tests that have a score that exceeds a threshold are included for execution.

Abstract: A method and system for automatically integrating component logs is provided. The method includes retrieving from a software application, high level log identification values representing transactions executed by the software application. Compiled machine language identification values representing compiled code associated with the software application and the hardware device are retrieved from an agent and a high level log identification value of the high level log identification values is identified. The high level log identification value is associated with an instruction set processed by a central processing unit (CPU). An instruction set identification value is correlated with the compiled machine language identification values. The compiled machine language identification values are converted into decompiled machine language identification values and the decompiled machine language identification values are correlated with log levels associated with the high level log identification values.

Abstract: A method, system and computer program product for analytically selecting which tests are to be executed in a continuous delivery process. An analytics processing system constructs a code dependency tree to analyze the tests that are affected by changes in code after a new build is generated. After analyzing the code dependency tree, the system eliminates those tests in the code dependency tree that do not depend on the changed code. The system then analyzes the historical execution records for those tests that have not been eliminated for execution to obtain an execution rate and a failure rate for those tests. A score is generated for each of the tests from the code dependency tree that were not eliminated for execution based on the historical execution rate and failure rate of the test. Tests that have a score that exceeds a threshold are included for execution.

Abstract: The method include receiving, by one or more computer processors, a request for data usage, the request for data usage being associated with a mobile device. The method further includes identifying, by one or more computer processors, a current data usage quantity, the current data usage quantity being associated with the mobile device. The method further includes determining, by one or more computer processors, whether the current data usage quantity is beyond a threshold data usage. The method further includes responsive to the data usage quantity being beyond the threshold data usage, receiving, by one or more computer processors, mobile device information associated with the mobile device. The method further includes analyzing, by one or more computer processors, the mobile device information. The method further includes determining, by one or more computer processors, access for the request based on the mobile device information and the current data usage quantity.

Abstract: One embodiment for determining a marketing incentive for a user of an electronic device. In one embodiment, a computer processor detects a first electronic device within a retail environment utilizing a second electronic device that also identifies information associated with the first electronic device. In one embodiment, a computer processor determines a behavior associated with the first electronic device based, at least in part, on movement of the first electronic device within the retail environment. In one embodiment, a computer processor identifies data associated with the retail environment that includes information associated with a retailer associated with the retail environment and information associated with the first electronic device. In one embodiment, a computer processor determines a first marketing incentive based, at least in part, on the determined behavior associated with the first electronic device and the identified data associated with the retail environment.

Abstract: The method include receiving, by one or more computer processors, a request for data usage, the request for data usage being associated with a mobile device. The method further includes identifying, by one or more computer processors, a current data usage quantity, the current data usage quantity being associated with the mobile device. The method further includes determining, by one or more computer processors, whether the current data usage quantity is beyond a threshold data usage. The method further includes responsive to the data usage quantity being beyond the threshold data usage, receiving, by one or more computer processors, mobile device information associated with the mobile device. The method further includes analyzing, by one or more computer processors, the mobile device information. The method further includes determining, by one or more computer processors, access for the request based on the mobile device information and the current data usage quantity.

Abstract: The method include receiving, by one or more computer processors, a request for data usage, the request for data usage being associated with a mobile device. The method further includes identifying, by one or more computer processors, a current data usage quantity, the current data usage quantity being associated with the mobile device. The method further includes determining, by one or more computer processors, whether the current data usage quantity is beyond a threshold data usage. The method further includes responsive to the data usage quantity being beyond the threshold data usage, receiving, by one or more computer processors, mobile device information associated with the mobile device. The method further includes analyzing, by one or more computer processors, the mobile device information. The method further includes determining, by one or more computer processors, access for the request based on the mobile device information and the current data usage quantity.

Abstract: One embodiment for determining a marketing incentive for a user of an electronic device. In one embodiment, a computer processor detects a first electronic device within a retail environment utilizing a second electronic device that also identifies information associated with the first electronic device. In one embodiment, a computer processor determines a behavior associated with the first electronic device based, at least in part, on movement of the first electronic device within the retail environment. In one embodiment, a computer processor identifies data associated with the retail environment that includes information associated with a retailer associated with the retail environment and information associated with the first electronic device. In one embodiment, a computer processor determines a first marketing incentive based, at least in part, on the determined behavior associated with the first electronic device and the identified data associated with the retail environment.