Download JAR files tagged by makes with all dependencies

MyDtt-Plus is a starter of spring-boot, It is an object-oriented Java framework that helps developers increase productivity, "Domain Driven Table" is the concept of DTT, It makes you focus more on domain objects rather than tables. Aims to make it easy to automatically create DB tables based on your Java model with annotation driven. It's also support the ability of create table automatically for MyBatis what Hibernate can do and optionally export SQL to local file，Each table can be added database name concat with table name and fully comments, It can work with ORM frameworks such as MyBatis-Plus and MyBatis with little learning and usage costs. It's worth mentioning that DTT can be MyBatis-Plus is integrated in a 0-code way, just like JPA. However, MyDtt-Plus and MyBatis-Plus may be easier to expand and use than JPA. In addition to supporting the functions of JPA, DDT provides multi-table associated SQL DDL based on MyBatis operation, DTT support databases server for MYSQL, ORACLE, DB2, SQLSERVER, MARIADB, POSTGRESQL and embedded database for H2, HSQL, DERBY.

Balea creates a proxy of javax.sql.DataSource, providing dynamic routing to multiple container based databases following a On Demand Data Source Access architecture. Docker is used as manager to create, start or stop database containers on demand and link correspondent data volumes. Thanks to this approach is possible to distribute data across multiple databases keeping active only the necessary ones in each moment maximizing the use of system resources. The distribution and management of data is hidden under the hood, any process that uses this data source interface (i.e. Hibernate) will perceive it as a single source of data. It makes possible for standard SQL database like Postgresql or MySQL to be maintained, backed up or versioned with simple file system operations as the data volumes are attached dynamically to the managed Docker containers. Docker integration allows also to manage database containers in remote hosts.

A bottom-up rewrite machine is a compiler construction tool that is often used in the compiler's back end to convert a tree-structured representation of a program into machine code -- or, in Java's case, bytecode. JBurg can also be used as a general-purpose dynamic programming engine. JBurg is descended from iburg-class BURGs, described in Fraser, Hanson, and Proebsting's paper, "Engineering a Simple, Efficient Code Generator Generator." JBurg brings similar O(N) minimum-cost tree rewriting capabilities to Java, and also allows the programmer to specify transitions between non-terminal states, that are significantly more powerful than iburg's transitive closures: JBurg transformation rules allow the transformation to inject additional program logic, which makes a JBurg specification more like a grammar than like a list of pattern-matching rules.

Xypron Statistics is a Java library which was developped with supply chain simulation in mind. The normal, the exponential and the gamma distribution have been included. Methods to calculate fill rate and order rate service levels as well as safety factors are provided. The Mersenne Twister algorithm is used to provide high quality random number generation. Some functions for the gamma distribution where adopted from http://www.ssfnet.org/download/ssfnet_raceway-2.0.tar.gz. For these the following applies: Copyright 1999 CERN - European Organization for Nuclear Research. Permission to use, copy, modify, distribute and sell this software and its documentation for any purpose is hereby granted without fee, provided that the above copyright notice appear in all copies and that both that copyright notice and this permission notice appear in supporting documentation. CERN makes no representations about the suitability of this software for any purpose. It is provided "as is" without expressed or implied warranty.

JUNG the Java Universal Network/Graph Framework--is a software library that provides a common and extensible language for the modeling, analysis, and visualization of data that can be represented as a graph or network. It is written in Java, which allows JUNG-based applications to make use of the extensive built-in capabilities of the Java API, as well as those of other existing third-party Java libraries. The JUNG architecture is designed to support a variety of representations of entities and their relations, such as directed and undirected graphs, multi-modal graphs, graphs with parallel edges, and hypergraphs. It provides a mechanism for annotating graphs, entities, and relations with metadata. This facilitates the creation of analytic tools for complex data sets that can examine the relations between entities as well as the metadata attached to each entity and relation. The current distribution of JUNG includes implementations of a number of algorithms from graph theory, data mining, and social network analysis, such as routines for clustering, decomposition, optimization, random graph generation, statistical analysis, and calculation of network distances, flows, and importance measures (centrality, PageRank, HITS, etc.). JUNG also provides a visualization framework that makes it easy to construct tools for the interactive exploration of network data. Users can use one of the layout algorithms provided, or use the framework to create their own custom layouts. In addition, filtering mechanisms are provided which allow users to focus their attention, or their algorithms, on specific portions of the graph.

JUNG the Java Universal Network/Graph Framework--is a software library that provides a common and extendible language for the modeling, analysis, and visualization of data that can be represented as a graph or network. It is written in Java, which allows JUNG-based applications to make use of the extensive built-in capabilities of the Java API, as well as those of other existing third-party Java libraries. The JUNG architecture is designed to support a variety of representations of entities and their relations, such as directed and undirected graphs, multi-modal graphs, graphs with parallel edges, and hypergraphs. It provides a mechanism for annotating graphs, entities, and relations with metadata. This facilitates the creation of analytic tools for complex data sets that can examine the relations between entities as well as the metadata attached to each entity and relation. The current distribution of JUNG includes implementations of a number of algorithms from graph theory, data mining, and social network analysis, such as routines for clustering, decomposition, optimization, random graph generation, statistical analysis, and calculation of network distances, flows, and importance measures (centrality, PageRank, HITS, etc.). JUNG also provides a visualization framework that makes it easy to construct tools for the interactive exploration of network data. Users can use one of the layout algorithms provided, or use the framework to create their own custom layouts. In addition, filtering mechanisms are provided which allow users to focus their attention, or their algorithms, on specific portions of the graph.

OpenIMAJ (Open Intelligent Multimedia in Java) is a collection of libraries and tools for multimedia analysis written in the Java programming language. OpenIMAJ intends to be the first truly complete multimedia analysis library and contains modules for analysing images, videos, text, audio and even webpages. The OpenIMAJ image and video analysis and feature extraction modules contain methods for processing visual content and extracting state-of-the-art features, including SIFT. The OpenIMAJ clustering and nearest-neighbour libraries contain efficient, multi-threaded implementations of clustering algorithms including Hierarchical K-Means and Approximate K-Means. The clustering library makes it possible to easily create visual-bag-of-words representations for images and video with very large vocabularies. The text-analysis modules contain implementations of a statistical language classifier and low-level processing pipeline. A number of modules deal with content creation, including interactive slideshows and animations. The hardware integration modules allow cross-platform integration with devices including webcams, the Microsoft Kinect, and even devices such as GPS's. OpenIMAJ also incorporates a number of tools to enable extremely-large-scale multimedia analysis using a distributed computing approach based on Apache Hadoop.

JUNG the Java Universal Network/Graph Framework--is a software library that provides a common and extendible language for the modeling, analysis, and visualization of data that can be represented as a graph or network. It is written in Java, which allows JUNG-based applications to make use of the extensive built-in capabilities of the Java API, as well as those of other existing third-party Java libraries. The JUNG architecture is designed to support a variety of representations of entities and their relations, such as directed and undirected graphs, multi-modal graphs, graphs with parallel edges, and hypergraphs. It provides a mechanism for annotating graphs, entities, and relations with metadata. This facilitates the creation of analytic tools for complex data sets that can examine the relations between entities as well as the metadata attached to each entity and relation. The current distribution of JUNG includes implementations of a number of algorithms from graph theory, data mining, and social network analysis, such as routines for clustering, decomposition, optimization, random graph generation, statistical analysis, and calculation of network distances, flows, and importance measures (centrality, PageRank, HITS, etc.). JUNG also provides a visualization framework that makes it easy to construct tools for the interactive exploration of network data. Users can use one of the layout algorithms provided, or use the framework to create their own custom layouts. In addition, filtering mechanisms are provided which allow users to focus their attention, or their algorithms, on specific portions of the graph.

git-commit-id-plugin is a plugin quite similar to https://fisheye.codehaus.org/browse/mojo/tags/buildnumber-maven-plugin-1.0-beta-4 for example but as buildnumber only supports svn (which is very sad) and cvs (which is even more sad). This plugin makes basic repository information available through maven resources. This can be used to display "what version is this?" or "who has deployed this and when, from which branch?" information at runtime - making it easy to find things like "oh, that isn't deployed yet, I'll test it tomorrow" and making both testers and developers life easier. The data currently exported is like this (that's the end effect from the GitRepositoryState Bean): { "branch" : "testing-maven-git-plugin", "commitTime" : "06.01.1970 @ 16:16:26 CET", "commitId" : "787e39f61f99110e74deed68ab9093088d64b969", "commitUserName" : "Konrad Malawski", "commitUserEmail" : "[email protected]", "commitMessageFull" : "releasing my fun plugin :-) + fixed some typos + cleaned up directory structure + added license etc", "commitMessageShort" : "releasing my fun plugin :-)", "buildTime" : "06.01.1970 @ 16:17:53 CET", "buildUserName" : "Konrad Malawski", "buildUserEmail" : "[email protected]" } Note that the data is exported via maven resource filtering and is really easy to use with spring - which I've explained in detail in this readme https://github.com/ktoso/maven-git-commit-id-plugin

DICTIONARY-BASED COMPOUND SPLITTER FOR GERMAN BananaSplit is a compound splitter for German that uses a dictionary resource. The dictionary can be either a simple word list, or a word list equipped with POS values, or an XML based dictionary. The original version was able to use GermaNet as a dictionary. This is useful in applications that rely on GermaNet anyway: no additional lexicon needs to be generated and held in memory. This was also the original purpose of BananaSplit. It served as a compound splitter for a tool called BananaRelation. BananaRelation cannot be published here as it makes heavy use of unpublished code by EML Research, Heidelberg. BananaSplit can either be used as a standalone application or it can be integrated into other Java programs (as a library). This program emerged from the seminar Lexical Semantic Processing in NLP (winter term 2005/2006) taught by Iryna Gurevych at the Seminar für Sprachwissenschaft, Tübingen. Both BananaSplit and BananaRelation were introduced to the seminar participants on 17th of December, 2005. The key algorithm for compound splitting is based on Langer (1998). The program came to use in Müller and Gurevych (2006). Please note that the program splits compounds into two parts only. Details are given in the documents linked below.