International Business Machines Corporation

Guang Tai Liang

Shao Chun Li

Ya Bin Dang

Hao Chen

Qi Cheng Li

Xin Zhou

Li Jun Mei

Yi-Min Chee

Feng Li

Zhenyu Zhang

Method and systems for tagging code include organizing code units in a hierarchical structure that associates the code units with respective description units. The hierarchical structure is filtered to remove un-meaningful description units from the hierarchical structure. Feature tags are generated based on a weighted sum of term frequencies in the description units of the hierarchical structure to associate features with respective code units.

Cross-validation based code feature tagging

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.

Alert remediation automation

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.

Integration of personalized traffic information

A system and method to build feature evolution models for existing applications ('apps') in the market based on open app data repositories). A feature evolution model of an app depicts the app name, its historical versions (historical version labels, release timestamps of each version), rating values of each version, and structured features (e.g., umbrella features and low-level features) each version introduces, improves or deletes. There is further extracted from the app description and release logs the app name, historical version labels, release timestamps, use the rating info of the app to extract and assign rating values for each version of the app, and apply NLP techniques and source code analysis techniques to extract 'structured features' of the app through analyzing the app description, the release logs, and corresponding source code revisions of the app. Upon the built feature evolution models, various feature insights may be easily extracted and generated.

Cognitive feature analytics

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.

System and method for automatic API candidate generation

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.

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Beijing, China

Guang Tai Liang