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InteGraal has been designed in a modular way, in order to facilitate software reuse and extension. It should make it easy to test new scenarios and techniques, in particular by combining algorithms. The main features of Graal are currently the following: (1) internal storage to store data by using a SQL or RDF representation (Postgres, MySQL, HSQL, SQLite, Remote SPARQL endpoints, Local in-memory triplestores) as well as a native in-memory representation (2) data-integration capabilities for exploiting federated heterogeneous data-sources through mappings able to target systems such as SQL, RDF, and black-box (eg. Web-APIs) (3) algorithms for query-answering over heterogeneous and federated data based on query rewriting and/or forward chaining (or chase)

InteGraal has been designed in a modular way, in order to facilitate software reuse and extension. It should make it easy to test new scenarios and techniques, in particular by combining algorithms. The main features of Graal are currently the following: (1) internal storage to store data by using a SQL or RDF representation (Postgres, MySQL, HSQL, SQLite, Remote SPARQL endpoints, Local in-memory triplestores) as well as a native in-memory representation (2) data-integration capabilities for exploiting federated heterogeneous data-sources through mappings able to target systems such as SQL, RDF, and black-box (eg. Web-APIs) (3) algorithms for query-answering over heterogeneous and federated data based on query rewriting and/or forward chaining (or chase)

The Attribution Maven Plugin is a tool for producing information about a project's dependencies, in a way that can be consumed by external reporting tools. It currently leverages the Maven Project Info Reports Plugin (https://maven.apache.org/components/plugins/maven-project-info-reports-plugin/) to obtain all of a project's data, and then output the information to an XML file, such as: target/attribution.xml. This plugin came from the need to get some of the same information produced by the Maven Project Info Reports Plugin, and have it ready to be consumed by tools which may require input in a certain format, such as a CSV. By producing an attribution XML file, scripts can be created to translate the data into these other consumable formats.

This library is the the backend for the Fitzhì solution. Fitzhì aims to gather all technical data regarding your application portfolio into ONE single portal. Fitzhì provides also analysis and assessments at the project scope, but its main target is the portfolio. The main ambition is to provide a global, and dynamic vision of the technical risk for your IT. The dream functionality for Fitzhì should be the ONE single dashboard, one Single Point Point Of Quality, available for the CTO, or CIO, and ready to resume in one second, one view, the current situation and the historic trend.

This module contains library classes for accessing the ThreadFix REST API. The ThreadFix IDE plugins use this library to retrieve application and vulnerability marker information, and in the ThreadFix scanner plugins to get endpoint information and upload scans to ThreadFix applications. The easiest way to start using the library is with the PluginClient or ThreadFixRestClient classes. Both have constructors that take a PropertiesManager instance, which holds the ThreadFix API key and url information. The default PropertiesManager implementation stores these properties in threadfix.properties, but the ThreadFix plugins extend the default PropertiesManager class to override this behavior for the target platform.

This library is the the backend for the Fitzhì solution. Fitzhì aims to gather all technical data regarding your application portfolio into ONE single portal. Fitzhì provides also analysis and assessments at the project scope, but its main target is the portfolio. The main ambition is to provide a global, and dynamic vision of the technical risk for your IT. The dream functionality for Fitzhì should be the ONE single dashboard, one Single Point Point Of Quality, available for the CTO, or CIO, and ready to resume in one second, one view, the current situation and the historic trend.

HotSpot learns a set of rules (displayed in a tree-like structure) that maximize/minimize a target variable/value of interest. With a nominal target, one might want to look for segments of the data where there is a high probability of a minority value occuring (given the constraint of a minimum support). For a numeric target, one might be interested in finding segments where this is higher on average than in the whole data set. For example, in a health insurance scenario, find which health insurance groups are at the highest risk (have the highest claim ratio), or, which groups have the highest average insurance payout.

This module contains library classes for accessing the ThreadFix REST API. The ThreadFix IDE plugins use this library to retrieve application and vulnerability marker information, and in the ThreadFix scanner plugins to get endpoint information and upload scans to ThreadFix applications. The easiest way to start using the library is with the PluginClient or ThreadFixRestClient classes. Both have constructors that take a PropertiesManager instance, which holds the ThreadFix API key and url information. The default PropertiesManager implementation stores these properties in threadfix.properties, but the ThreadFix plugins extend the default PropertiesManager class to override this behavior for the target platform.

This Tool provides the means to monitor the performance of Spring Batch applications without the need to manipulate the respective code basis. Through Listeners and AOP it evaluates the throughput of a monitored Job and writes the result to a simble database-schema (a file-based H2 by default). It measures the performance of Job, Step, Chunk, Reader/Processor/Writer/Tasklet down to indivdual Items. Installation/Usage: 1. Add the springBatchPerformanceMonitoring-dependency to your POM 2. Add the de.viadee.spring.batch.infrastructure.Configurator.class to your Spring-Application-Context (via @Import on your Configuration) 3. Run the Job 4. By default the monitoring result is written to project-folder/target/database/monitoringDB.mv.db

The ServiceMix Drools component provides JBI integration to the Drools Rules Engine. It can be used to deploy a rules set that will implement a router or an actual service. A router will mostly act as a transparent proxy between the consumer and the target service provider mad will mostly be implemented by the jbi.route(uri) method below. This method creates a new exchange identical to the one received by the component and will send it to the specified destination. You can also send back a Fault if needed. A router can also be implemented by using directly the JBI Apis (available with the jbi helper) by using the provided client.