Download JAR files tagged by execution with all dependencies

SEWOL provides support for the handling of workflow traces. Specifically it allows to specify the shape and content of process traces in terms of entries representing the execution of a specific workflow activity. SEWOL also allows to write these traces on disk as a log file with the help of a special file writer for process logs. Currently it supports plain text, Petrify, MXML and XES log file types. In order to specify security-related context information, SEWOL provides access control models such as access control lists (ACL) and role-based access control models (RBAC). All types of models can be conveniently edited with the help of appropriate dialogs.

SEPIA provides implementations for various types of Petri nets. Along Place/Transition-nets, it supports Petri nets with distinguishable token colors and defines coloured workflow nets, where coloured tokens are interpreted as data elements used during process execution. To support information flow analysis of processes, SEPIA defines so-called IF-Nets, tailored for security-oriented workflow modeling which enable users to assign security-levels (HIGH, LOW) to transitions, data elements and persons/agents participating in the process execution.

The Jenkins Maven Plugin allows to use the Jenkins CLI (command line interface) from within a Maven build. It allows the execution of any command supported by the CLI, see https://wiki.jenkins-ci.org/display/JENKINS/Jenkins+CLI for further information. Therefore, it downloads the current jenkins-cli.jar from ${project.ciManagement.url}/jnlpJars/jenkins-cli.jar and uses that artifact for interacting with the Jenkins server. The architecture of the Jenkins Maven Plugin follows the UNIX philosophy "do one thing and do it well": it does not provide any logic for specific tasks, for instance creating job configuration files. This can be done with another, more appropriate plugin and its result can then be specified as stdin to the Jenkins Maven Plugin.

The Jeuron Application Platform is a lightweight framework to assemble software components intended to support multiple project and deployment scenarios while also providing an environment for testing and debugging. The platform is comprised of a set of packages which provide transport, messaging, configuration, and execution services designed to create a configurable, scalable, and distributed application environment. The low resource model permits the platform to be instantiated during each build cycle and to be deployed at all levels of the application hierarchy such as application servers, web servers, and mobile or wired workstations.

Class for boosting a classifier using the MultiBoosting method. MultiBoosting is an extension to the highly successful AdaBoost technique for forming decision committees. MultiBoosting can be viewed as combining AdaBoost with wagging. It is able to harness both AdaBoost's high bias and variance reduction with wagging's superior variance reduction. Using C4.5 as the base learning algorithm, Multi-boosting is demonstrated to produce decision committees with lower error than either AdaBoost or wagging significantly more often than the reverse over a large representative cross-section of UCI data sets. It offers the further advantage over AdaBoost of suiting parallel execution. For more information, see Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).

Stopwatch is a free, simple, highly extensible, Java API that allows developers to easily monitor whole application or any part of it. By default Stopwatch generate reports about hits, execution times (total, average, minimum, maximum) as well as load but it can be easily extended to measure anything else by providing custom engine. Out of the box Stopwatch uses an in-memory HSQL database. It is able to persist collected data using a "storage". There is "storage" provided to persist into HSQL database and custom "storage" can be easily integrated.