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Rule Learner is an open source Java library for learning business rules from historical data. It supports supervised Machine Learning by incorporating well-known algorithms such as RIPPER and C4.5 provided by open source tools such as Weka. Rule Learner is implemented as a Machine Learning component of OpenRules Decision Manager. It allows business analysts to place their historical data in simple Excel tables and to automatically discover business rules that find certain pattern in this data. The generated rules are human readable and presented in Excel format executable by OpenRules Decision Manager.

Samply.Common.MDRFaces is a Java Server Faces library which eases the user interface design of web applications where the respective data model relies on well defined data elements. Especially in case of systems for electronic data capturing, where the necessary data model is not known beforehand and can even vary over time, the user interface has to be easily adjustable. This often means the user instead of the developer designs the various forms for data entry and therefore an easy to use mechanism has to be provided. By using Samply.MDRFaces the developer can focus on the implementation of that mechanism, e.g. some editor component, but does not have to cope with the visualization of every single data element as for that is taken care of automatically.

This small library provides an optimized solution to a problem where tasks for a particular key need to be processed sequentially as they arrive. This kind of problem can be solved by a SingleThreadExecutor, however it is not efficient. The issue is that the tasks for unrelated keys are not being processed in parallel, instead they are put into a queue common to all keys and wait for the single thread to execute them. This library allows them to be executed concurrently. Moreover this library works well in a situation where all the possible keys and their number is not known upfront.

The Java JDK includes various means of creating/consuming compressed files. What is missing is easy way of creating lazy streamed zip archive, in spirit of java.util.zip.DeflaterInputStream. This implementation relies on the fact that the PKZIP specification allows archiving data streams of sizes not known upfront. This implies that the archives produced will be readable only by tools aware of this trick. Notably, java.util.zip.ZipInputStream is OK with that, so we use it to test compatibility.