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This library was created for providing templates for various applications such as invoices, manifests etc in PDF formats. It is extensively used in Assure. It makes use of the Apache Velocity and wkhtmltopdf libraries for creating templates and formats

Gosu language compiler for Gradle. Built with Gradle 6.5.1. This has also been tested extensively with Gradle version(s): 6.5.1 ** Gradle versions below 2.12 are no longer supported ** Projects applying this plugin require a compile-time dependency on the gosu-core-api library. This version requires Gosu 1.13.9 or greater, or 1.14.2 or greater. Please include this in the depencencies closure: dependencies { compile group: 'org.gosu-lang.gosu', name: 'gosu-core-api', version: '1.14.18' }

Gosu language compiler for Gradle. Built with Gradle 5.1.1. This has also been tested extensively with Gradle version(s): 5.1.1 ** Gradle versions below 2.12 are no longer supported ** Projects applying this plugin require a compile-time dependency on the gosu-core-api library. This version requires Gosu 1.13.9 or greater, or 1.14.2 or greater. Please include this in the depencencies closure: dependencies { compile group: 'org.gosu-lang.gosu', name: 'gosu-core-api', version: '1.14.12' }

The JSP TLD Maven Plugin is used to automate the management of JSP Tag Library Descriptors as part of a Maven build. It is intended to decrease the burden on JSP developers associated with writing custom JSP Tag Libraries. The goal is to encourage JSP developers to write better JSP files by using custom JSP Tag Libraries more extensively. The Plugin can process Java annotations on Tag implementation classes and also discover Tag Files (.tag and .tagx files). The Java 5 Annotations recognized by this Plugin are all part of the <a href="../squeakysand-jsp/apidocs/com/squeakysand/jsp/tagext/annotations/package-summary.html">com.squeakysand.jsp.tagext.annotations</a> package.

Chips-n-Salsa is a Java library of customizable, hybridizable, iterative, parallel, stochastic, and self-adaptive local search algorithms. The library includes implementations of several stochastic local search algorithms, including simulated annealing, hill climbers, as well as constructive search algorithms such as stochastic sampling. Chips-n-Salsa now also includes genetic algorithms as well as evolutionary algorithms more generally. The library very extensively supports simulated annealing. It includes several classes for representing solutions to a variety of optimization problems. For example, the library includes a BitVector class that implements vectors of bits, as well as classes for representing solutions to problems where we are searching for an optimal vector of integers or reals. For each of the built-in representations, the library provides the most common mutation operators for generating random neighbors of candidate solutions, as well as common crossover operators for use with evolutionary algorithms. Additionally, the library provides extensive support for permutation optimization problems, including implementations of many different mutation operators for permutations, and utilizing the efficiently implemented Permutation class of the JavaPermutationTools (JPT) library. Chips-n-Salsa is customizable, making extensive use of Java's generic types, enabling using the library to optimize other types of representations beyond what is provided in the library. It is hybridizable, providing support for integrating multiple forms of local search (e.g., using a hill climber on a solution generated by simulated annealing), creating hybrid mutation operators (e.g., local search using multiple mutation operators), as well as support for running more than one type of search for the same problem concurrently using multiple threads as a form of algorithm portfolio. Chips-n-Salsa is iterative, with support for multistart metaheuristics, including implementations of several restart schedules for varying the run lengths across the restarts. It also supports parallel execution of multiple instances of the same, or different, stochastic local search algorithms for an instance of a problem to accelerate the search process. The library supports self-adaptive search in a variety of ways, such as including implementations of adaptive annealing schedules for simulated annealing, such as the Modified Lam schedule, implementations of the simpler annealing schedules but which self-tune the initial temperature and other parameters, and restart schedules that adapt to run length.