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The goal of quality-check is to provide a small Java library for basic runtime code quality checks. It provides similar features to org.springframework.util.Assert or com.google.common.base.Preconditions without the need to include big libraries or frameworks such as Spring or Guava. The package quality-check tries to replace these libraries and provide all the basic code quality checks you need. The checks provided here are typically used to validate method parameters and detect errors during runtime. To detect errors before runtime we use JSR-305 Annotations. With these annotations you are able to detect possible bugs earlier. For more informations look at FindBugs™ JSR-305 support.

The goal of quality-check is to provide a small Java library for basic runtime code quality checks. It provides similar features to org.springframework.util.Assert or com.google.common.base.Preconditions without the need to include big libraries or frameworks such as Spring or Guava. The package quality-check tries to replace these libraries and provide all the basic code quality checks you need. The checks provided here are typically used to validate method parameters and detect errors during runtime. To detect errors before runtime we use JSR-305 Annotations. With these annotations you are able to detect possible bugs earlier. For more informations look at FindBugs™ JSR-305 support.

This package contains a classifier that can be used to train a two-class kernel logistic regression model with the kernel functions that are available in WEKA. It optimises the negative log-likelihood with a quadratic penalty. Both, BFGS and conjugate gradient descent, are available as optimisation methods, but the former is normally faster. It is possible to use multiple threads, but the speed-up is generally very marginal when used with BFGS optimisation. With conjugate gradient descent optimisation, greater speed-ups can be achieved when using multiple threads. With the default kernel, the dot product kernel, this method produces results that are close to identical to those obtained using standard logistic regression in WEKA, provided a sufficiently large value for the parameter determining the size of the quadratic penalty is used in both cases.

JSci is a set of open source Java packages. The aim is to encapsulate scientific methods/principles in the most natural way possible. As such they should greatly aid the development of scientific based software. It offers: abstract math interfaces, linear algebra (support for various matrix and vector types), statistics (including probability distributions), wavelets, newtonian mechanics, chart/graph components (AWT and Swing), MathML DOM implementation, ... Note: some packages, like javax.comm, for the astro and instruments package aren't listed as dependencies (not available).

"Tests with Parameters" allows you to simply add parameters to your JUnit test methods. TwiP calls such methods with all possible combinations of their parameters... or at least some reasonable subset of commonly failing values in the case of Integers, etc. You can further reduce these values with an assume expression in an annotation, e.g. ">= 0". Alternatively you can specify a static method or field to provide the values for your test method(s), if you want to test with other than the default values. By using TwiP you change the semantics of your tests from existence to for-all quantifiers, i.e. you specify "all ravens are black" instead of "Abraxas is black", "Toni is black", etc. This moves your tests closer to an executable specification, so TwiP is a very nice addition to BDD.

Jetty is an open-source, standards-based, full-featured web server implemented entirely in Java. It is released under the Apache 2.0 licence and is therefore free for commercial use and distribution. First created in 1995, Jetty has benefitted from input from a vast user community and consistent and focused development by a stable core of lead developers. There are many more examples of Jetty in action on the Jetty Powered Page that has selections from among the tens of thousands of production Jetty instances. However, as Jetty aims to be as unobtrusive as possible, countless websites and products are based around Jetty, but Jetty is invisible!

Release Audit Tool (RAT) is a tool to improve accuracy and efficiency when checking releases. It is heuristic in nature: making guesses about possible problems. It will produce false positives and cannot find every possible issue with a release. It's reports require interpretation. In response to demands from project quality tool developers, RAT is available as a library suitable for inclusion in tools. This POM describes that library. Note that binary compatibility is not gauranteed between 0.x releases.

Stepping is a framework designed to ease the implementation of data processing solutions. In use cases where we need to implement data or data-streaming algorithms or any other processing on data, we need to first handle many different infrastructure issues. For example, we need to decide how to split the data processing logic into different steps, think about our threading policy, how to handle communication between the different steps, error handling etc. One of the most important subjects is the Threading Policy of our solution. For example, we need to think how many threads to open, have the option to distribute the processing of data to multiple 'executors' in parallel, have a thread-safe communication layer between the threads etc. On top of that we also care a lot about the performance of our solution, we want to make sure that the latency added by these infrastructures is minimal as possible. Stepping aims to handle many of these aspects so developers can spend their time on the business logic instead of solving these infrastructure and data flow issues issues over and over again.

A NSGA-II implementation using Java. This implementation of NSGA-II algorithm is in pure reference to the original published paper. This is not an effort to convert the originally implemented C code in Java. The original C code by the authors has not be referred to while writing this implementation. This is a fully customizable implementation of the NSGA-II algorithm, made as generic as possible. This documentation assumes you have basic understanding of the NSGA-II algorithm. Apart from the core concepts of the algorithm, everything else in this package can be implemented as per the user's choice and plugged into the algorithm dynamically. Since NSGA-II is more like a set of protocols to follow as an algorithm rather than a concrete implementation of every aspect, this package has been re-written from scratch keeping complete customizability in mind. Apart from the core concepts of the algorithm, everything is considered to be a plugin external to the algorithm that can be implemented by the user and dynamically plugged into the algorithm during runtime as needed. This opens up the possibility of the package to be used simply as a PoC or be converted into something much more complex according to the users needs.

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.