Abstract: The present disclosure relates to identifying an origin/destination pair. Aspects include identifying an origin/destination pair in a service, which includes determining a current time when the current operation is executed in response to failure of a current operation for recording an origin/destination pair. Aspects also include determining a previous time when a last operation was executed for recording an origin/destination pair and identifying a missing point causing failure of the current operation based on a time interval between the current time and the previous time.

Abstract: A method for predicting anomalies in a computer application includes during runtime of the computer application, detecting traffic metrics and incident tickets associated with the computer application, the incident ticket indicating an incident might occur in the computer application; calculating a threshold based on absolute values of second order differences associated with the traffic metrics, wherein the threshold is such that when the absolute value of the second order difference associated with the traffic metrics exceeds the threshold, a recall rate Rrecall that the computer application is recalled is maximized; obtaining predicted metrics of the computer application in a next time period based on the traffic metrics; and in response to an absolute value of a second order difference associated with the predicted metrics exceeding the threshold, predicting potential anomalies of the computer application in the next time period.

Abstract: The methods, systems, and computer program products described herein provide optimized provisioning of replacement parts for service calls through the use of machine learning. In some aspects, historical hardware maintenance tickets may be processed to generate symptoms vectors identifying sets of symptoms associated with the hardware maintenance tickets. The symptoms vectors and corresponding parts usage records of the historical hardware maintenance tickets may be used train a decision model to predict a probability that a particular part will be used to fulfill the new hardware maintenance ticket. The predicted probability may be used by the system when generating a parts provisioning plan for the new hardware maintenance ticket.

Abstract: A method for generating a tree map for tree map visualization includes obtaining node information of a plurality of nodes to be processed, the plurality of nodes to be processed being sub-nodes sharing a same parent node and the node information comprising at least sizes of the nodes; determining from the plurality of nodes a plurality of candidate nodes whose sizes are less than a threshold size; determining at least one super node including the plurality of candidate nodes based on the node information of the determined plurality of candidate nodes, a screen size, and the threshold size, such that when displaying in a zooming-in mode the super node on the screen, all candidate nodes in the super node are displayed at display sizes not less than the threshold size; and determining data required for displaying the tree map based on the determined super node.

Abstract: A method for generating a tree map for tree map visualization includes obtaining node information of a plurality of nodes to be processed, the plurality of nodes to be processed being sub-nodes sharing a same parent node and the node information comprising at least sizes of the nodes; determining from the plurality of nodes a plurality of candidate nodes whose sizes are less than a threshold size; determining at least one super node including the plurality of candidate nodes based on the node information of the determined plurality of candidate nodes, a screen size, and the threshold size, such that when displaying in a zooming-in mode the super node on the screen, all candidate nodes in the super node are displayed at display sizes not less than the threshold size; and determining data required for displaying the tree map based on the determined super node.

Abstract: Aspects of the present invention generally relate to a system, method, and computer program product for transforming APIs from legacy system-of-record to new system-of-engagement using complete API process logic. API candidates are generated from execution traces for transforming the API from the legacy system to a new system of record. An embodiment of the invention is first, add implementers into a legacy systems and collect the instrumenter output as execution traces. Second, rank the execution traces and find the most frequent execution traces. Third, consolidate the execution traces by merging common trace segments. The codes covered by the consolidated execution traces will be considered as candidate API components. Fourth, expand the merged execution traces and find related execution traces and check the connectivity between different nodes.

Abstract: A method for predicting anomalies in a computer application includes during runtime of the computer application, detecting traffic metrics and incident tickets associated with the computer application, the incident ticket indicating an incident might occur in the computer application; calculating a threshold based on absolute values of second order differences associated with the traffic metrics, wherein the threshold is such that when the absolute value of the second order difference associated with the traffic metrics exceeds the threshold, a recall rate Rrecall that the computer application is recalled is maximized; obtaining predicted metrics of the computer application in a next time period based on the traffic metrics; and in response to an absolute value of a second order difference associated with the predicted metrics exceeding the threshold, predicting potential anomalies of the computer application in the next time period.

Abstract: Technical solutions to automate alert remediation are described. One aspect includes a method that includes receiving a plurality of alerts from an application monitoring system, the plurality of alerts associated with a plurality of remediation procedures respectively. The method also includes selecting a subset of alerts from the plurality of alerts. The method also includes identifying a subset of remediation procedures corresponding to the subset of alerts and analyzing compliance, with a service level agreement, of an execution of the entire subset of remediation procedures. In response to the execution of the entire subset of remediation procedures being non-compliant, the latest alert that was added, is removed from the subset of alerts, and a remediation procedure corresponding to the latest alert is removed from the subset of remediation procedures. The method includes executing the entire subset of remediation procedures.

Abstract: Technical solutions to automate alert remediation are described. One aspect includes a method that includes receiving a plurality of alerts from an application monitoring system, the plurality of alerts associated with a plurality of remediation procedures respectively. The method also includes selecting a subset of alerts from the plurality of alerts. The method also includes identifying a subset of remediation procedures corresponding to the subset of alerts and analyzing compliance, with a service level agreement, of an execution of the entire subset of remediation procedures. In response to the execution of the entire subset of remediation procedures being non-compliant, the latest alert that was added, is removed from the subset of alerts, and a remediation procedure corresponding to the latest alert is removed from the subset of remediation procedures. The method includes executing the entire subset of remediation procedures.

Abstract: A computer-implemented method for searching for a ticket relevant to a current ticket describing an incident, a system and a computer program product for the same. The method includes extracting a topology of a first application of a server system, the first application being indicated by the current ticket; selecting a second application relevant to the first application from a plurality of candidate applications of the server system, according to the topology; and searching tickets associated with the second application for the ticket relevant to the current ticket.

Abstract: Method and systems for tagging code include building a code structure based description unit association model (CDAM) that associates code units with respective description units and organizes the code units in a hierarchical structure. The CDAM is filtered to remove un-meaningful description units through cross-validation between code units. Feature tags are generated based on a weighted sum of term frequencies in the description units of the CDAM to associate features with respective code units.

Abstract: Embodiments of the present invention may evaluate a conflict risk between parallel projects. According to one embodiment of the present invention, a dependency risk between a first project and a second project is determined based on an artifact submission history of a historical project. Then an overlap risk between the first and second projects is determined based on time schedules of the first and second projects. Next, a conflict risk between the first and second projects is evaluated based on the dependency risk and the overlap risk. Further, embodiments of the present invention may optimize the time schedules of parallel projects thereby enabling parallelization of projects.

Abstract: Embodiments of the present invention may evaluate a conflict risk between parallel projects. According to one embodiment of the present invention, a dependency risk between a first project and a second project is determined based on an artifact submission history of a historical project. Then an overlap risk between the first and second projects is determined based on time schedules of the first and second projects. Next, a conflict risk between the first and second projects is evaluated based on the dependency risk and the overlap risk. Further, embodiments of the present invention may optimize the time schedules of parallel projects thereby enabling parallelization of projects.

Abstract: Computer-implemented method for searching for information related to an incident generated in a server system, a system and a computer program product. The method includes extracting context information from a current ticket describing the incident, the context information including a first expression describing a symptom of the incident and indicating at least one component of the server system associated with the symptom; determining a data source which generates data in which the information related to the incident is to be searched for at least according to the at least one component; and using the first expression describing the symptom and a second different expression describing the symptom as keywords to search for the information related to the incident in the data.

Abstract: Integration of personalized traffic information is provided. Contextual information for a client device is collected. Based, at least in part, on the contextual information, traffic information is received. The traffic information is received from one or more broadcast stations to which the traffic information has been mapped based, at least in part, on classification of the traffic information. A communications device is caused to communicate the traffic information.

Abstract: A fine-grained behavior model matching based method and system for effective feature location in large legacy systems. A feature behavior analyzer extracts internal behaviors of a feature under requesting based on NLP techniques or writing rules of the feature specification and generates a feature behavior model. A method uses multiple information sources associated with each method under analyzing to generate an expressive behavior signature for each method. The method integrates control flow information of each method and the signature information of its callees, and generates a CFG-based behavior model. A feature location identifier identifies and ranks the feature-related code locations based on a similarity between the feature behavior and the code behavior models.

Abstract: A method for predicting anomalies in a computer application includes during runtime of the computer application, detecting traffic metrics and incident tickets associated with the computer application, the incident ticket indicating an incident might occur in the computer application; calculating a threshold based on absolute values of second order differences associated with the traffic metrics, wherein the threshold is such that when the absolute value of the second order difference associated with the traffic metrics exceeds the threshold, a recall rate Rrecall that the computer application is recalled is maximized; obtaining predicted metrics of the computer application in a next time period based on the traffic metrics; and in response to an absolute value of a second order difference associated with the predicted metrics exceeding the threshold, predicting potential anomalies of the computer application in the next time period.

Abstract: Analyzing task associations may compute artifact associations for a plurality of artifacts based on historical task submission logs. From the computed artifact associations, shared artifacts that have artifact association with targeted artifacts that are associated with planned tasks, may be determined. Task association between the planned tasks may be identified based on the shared artifacts. Task associations may be analyzed to determine one or more of task assignment and task schedule for the planned tasks.

Abstract: A method for generating a tree map for tree map visualization includes obtaining node information of a plurality of nodes to be processed, the plurality of nodes to be processed being sub-nodes sharing a same parent node and the node information comprising at least sizes of the nodes; determining from the plurality of nodes a plurality of candidate nodes whose sizes are less than a threshold size; determining at least one super node including the plurality of candidate nodes based on the node information of the determined plurality of candidate nodes, a screen size, and the threshold size, such that when displaying in a zooming-in mode the super node on the screen, all candidate nodes in the super node are displayed at display sizes not less than the threshold size; and determining data required for displaying the tree map based on the determined super node.

Abstract: A fine-grained behavior model matching based method and system for effective feature location in large legacy systems. A feature behavior analyzer extracts internal behaviors of a feature under requesting based on NLP techniques or writing rules of the feature specification and generates a feature behavior model. A method uses multiple information sources associated with each method under analyzing to generate an expressive behavior signature for each method. The method integrates control flow information of each method and the signature information of its callees, and generates a CFG-based behavior model. A feature location identifier identifies and ranks the feature-related code locations based on a similarity between the feature behavior and the code behavior models.