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The Jelly JMX Tag Library is a Jelly library for instantiating and configuring Java Beans and MBeans and registering them with a JMX Server in a similar way to the Ant tasks in Jakarta Commons Modeler.

Lightweight library for instantiating functions and predicates in a DSL style, without using anonymous classes. This project is aimed to simplify higher-order programming until Java adds lambdas to its language

Lightweight library for instantiating functions and predicates in a DSL style, without using anonymous classes. This project is aimed to simplify higher-order programming until Java adds lambdas to its language

Rouplex-Niossl is a java SPI (service provider interface) for secure (SSL/TLS), selectable, socket channels. Some of the classes in the java.nio.channels package have been extended by secure counterparts that can be used side by side, or replace existing instances of the plain implementations. This package contains just the entry point calls for instantiating such instances, as well as a non-functional, default implementation. For a concrete implementation of these classes you can take a look at Rouplex-Niossl-Spi, which would be included as a separate dependency to your applications. More specifically this library defines SSLSocketChannel class to inherit from SocketChannel, SSLServerSocketChannel to inherit from ServerSocketChannel and SSLSelector to inherit from SSLSelector. One or more instances of SSLSocketChannel can be registered with an (or more) instance of SSLSelector to be selected upon, with the same exact semantics a SocketChannel would expect from registering with a Selector. Further, a mixture of SocketChannels and SSLSocketChannels can be registered simultaneously with an SSLSelector. The secure counterparts abide to the same API and semantics defined for plain channels at https://docs.oracle.com/javase/8/docs/api/java/nio/channels/package-summary.html. This way, the existing products can be easily updated to provide secure communication and new products can achieve security of data in transit by using the already proven and excellent patterns for communication such as nio.

A library extending the Jdk1.8 java.nio.channels package with SSL implementations for SocketChannel, ServerSocketChannel, Selector and SelectorProvider.

This module contains a more general approach to construct AlignmentAlgorithms by relying on the theoretical concept of Algebraic Dynamic Programming (ADP) as developed by Giegerich et al. ADP defines four ingredients for an alignment algorithm: 1.) A signature that defines the permitted alignment operations. Operations are just function templates with an associated arity, meaning the number of arguments it takes from the left sequence and from the right sequence. In the TCSAlignmentToolbox we have a fixed signature with the following operations: REPLACEMENT(1, 1), DELETION(1, 0), INSERTION(0, 1), SKIPDELETION(1, 0) and SKIPINSERTION(0, 1) 2.) A regular tree grammar that produces alignments, that is: sequences of operations, in a restricted fashion. 3.) An algebra that can translate such trees to a cost. In the TCSAlignmentToolbox this is a Comparator. 4.) A choice function, in case of the TCSAlignmentToolbox: the strict minimum or the soft minimum. An alignment algorithm in the TCSAlignmentToolbox sense of the word then is the combination of choice function and grammar. While we provide hardcoded versions of these combinations in the main package, the adp package allows you to create your own grammars. You can combine them with a choice function by instantiating one of the Algorithm classes provided in this package with a grammar of your choice. For example: AlignmentAlgorithm algo = new SoftADPScoreAlgorithm(my_grammar, comparator); creates an alignment algorithm that implicitly produces all possible alignments your grammar can construct with the given input, translates them to a cost using the algebra/comparator you provided and applies the soft minimum to return the score. This all gets efficient by dynamic programming. Note that there is runtime overhead when using this method in comparison with the hardcoded algorithms. But for complicated grammars this is a much easier way to go. For more information on the theory, please refer to my master's thesis: "Adaptive Affine Sequence Alignment using Algebraic Dynamic Programming"