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This project basically aims to create an abstraction layer above common ORM used this days and provide a simplified DAO layer which is not only independent of the ORM tool being used but also integrated with other services, for example App Layer Caching, Free Text Search Engine etc. Initial target is to implement it for Hibernate and when JPA provides Hibernate's Criteria like API implement for JPA as well. Integrate App Layer Cache and Compass Framework.

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 (e.g. 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 (e.g. 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.