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JCQL is a tool allowing to generate boilerplate java code from existing cassandra schema. It is intended to be used with Cassandra 2.1+ due to support of UDTs (User Defined Types)/Tuples/Collections. Cassandra's UDTs/Tuples/Collections and an ability to introspect schema through java driver make it possible to automatically generate POJOs and corresponding mappers between database and java models. Properly generated java code saves development efforts and is less error-prone compared to hand coding. Accompanied with proper CI and deployment it can also guarantee consistency between database and java models at any point of application lifecycle from development to production rollout. JCQL does not rely on java reflection or annotations which means all discrepancies between actual cassandra schema and what client code expects it to be will be identified during compilation not at runtime in the middle of the night right after production release. No need to worry about Cassandra client code performance implications due to use of reflection.

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.

The SAP Java Connector (SAP JCo) is a toolkit that allows a Java application to communicate with any SAP system. It combines an easy to use API with unprecedented flexibility and performance. The package supports both, Java to SAP System as well as SAP System to Java calls. - All SAP Connectors are licensed without additional license fees as part of the respective solution or component license. However, please note that each connector may be used only for connecting external (non-SAP) applications to SAP Systems / SAP Solutions. Scenarios, in which two external (non-SAP) applications are integrated via an SAP Connector, are not allowed. - The redistribution of any connector is not allowed. - All SAP users accessing application functionality through the relevant connector are required to be licensed under a respective solution or component license. To use the SAP JCo with the Hibersap project, you need to either install the SAP JCo jar downloaded from SAP to your local Maven repository (variant a) or deploy it to e.g. an enterprise Maven repository like Nexus or Artifactory (variant b): (a) mvn install:install-file -DgroupId=org.hibersap -DartifactId=sapjco3 -Dversion=3.0.12 -Dpackaging=jar -Dfile=path/to/sapjco3.jar (b) mvn deploy:deploy-file -DrepositoryId=[your.repo.id] -DgroupId=org.hibersap -DartifactId=sapjco3 -Dversion=3.0.12 -Dpackaging=jar -Dfile=sapjco3.jar

The SAP Java Connector (SAP JCo) is a toolkit that allows a Java application to communicate with any SAP system. It combines an easy to use API with unprecedented flexibility and performance. The package supports both, Java to SAP System as well as SAP System to Java calls. - All SAP Connectors are licensed without additional license fees as part of the respective solution or component license. However, please note that each connector may be used only for connecting external (non-SAP) applications to SAP Systems / SAP Solutions. Scenarios, in which two external (non-SAP) applications are integrated via an SAP Connector, are not allowed. - The redistribution of any connector is not allowed. - All SAP users accessing application functionality through the relevant connector are required to be licensed under a respective solution or component license. To use the SAP JCo with the Hibersap project, you need to either install the SAP JCo jar downloaded from SAP to your local Maven repository (variant a) or deploy it to e.g. an enterprise Maven repository like Nexus or Artifactory (variant b): (a) mvn install:install-file -DgroupId=org.hibersap -DartifactId=sapjco3 -Dversion=3.0 -Dpackaging=jar -Dfile=path/to/sapjco3.jar (b) mvn deploy:deploy-file -DrepositoryId=[your.repo.id] -DgroupId=org.hibersap -DartifactId=sapjco3 -Dversion=3.0 -Dpackaging=jar -Dfile=sapjco3.jar

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.

ASV Toolbox is a modular collection of tools for the exploration of written language data. They work either on word lists or text and solve several linguistic classification and clustering tasks. The topics covered contain language detection, POS-tagging, base form reduction, named entity recognition, and terminology extraction. On a more abstract level, the algorithms deal with various kinds of word similarity, using pattern based and statistical approaches. The collection can be used to work on large real world data sets as well as for studying the underlying algorithms. The ASV Toolbox can work on plain text files and connect to a MySQL database. While it is especially designed to work with corpora of the Leipzig Corpora Collection, it can easily be adapted to other sources.

Performs one-class classification on a dataset. Classifier reduces the class being classified to just a single class, and learns the datawithout using any information from other classes. The testing stage will classify as 'target'or 'outlier' - so in order to calculate the outlier pass rate the dataset must contain informationfrom more than one class. Also, the output varies depending on whether the label 'outlier' exists in the instances usedto build the classifier. If so, then 'outlier' will be predicted, if not, then the label willbe considered missing when the prediction does not favour the target class. The 'outlier' classwill not be used to build the model if there are instances of this class in the dataset. It cansimply be used as a flag, you do not need to relabel any classes. For more information, see: Kathryn Hempstalk, Eibe Frank, Ian H. Witten: One-Class Classification by Combining Density and Class Probability Estimation. In: Proceedings of the 12th European Conference on Principles and Practice of Knowledge Discovery in Databases and 19th European Conference on Machine Learning, ECMLPKDD2008, Berlin, 505--519, 2008.

Randoop is an automatic unit test generator for Java. It automatically creates unit tests for your classes, in JUnit format. Randoop generates unit tests using feedback-directed random test generation. In a nutshell, this technique randomly, but smartly, generates sequences of methods and constructor invocations for the classes under test, and uses the sequences to create tests. Randoop executes the sequences it creates, using the results of the execution to create assertions that capture the behavior or your program and that catch bugs. Randoop has created tests that find previously unkwon errors even in widely-used libraries including Sun and IBM's JDKs. A .NET version of Randoop, used internally at Microsoft, has been used successfully by a team of test engineers to find errors in a core .NET component that has been heavily tested for years. Randoop's combination of randomized test generation and test execution results in a highly effective test generation technique.

Class for building pace regression linear models and using them for prediction. Under regularity conditions, pace regression is provably optimal when the number of coefficients tends to infinity. It consists of a group of estimators that are either overall optimal or optimal under certain conditions. The current work of the pace regression theory, and therefore also this implementation, do not handle: - missing values - non-binary nominal attributes - the case that n - k is small where n is the number of instances and k is the number of coefficients (the threshold used in this implmentation is 20) For more information see: Wang, Y (2000). A new approach to fitting linear models in high dimensional spaces. Hamilton, New Zealand. Wang, Y., Witten, I. H.: Modeling for optimal probability prediction. In: Proceedings of the Nineteenth International Conference in Machine Learning, Sydney, Australia, 650-657, 2002.

Module that defines the HttpChannel API. HttpChannels abstract complex download and upload steps into a simple and easy to use NIO Channel. NIO Channels can be wrapped into an InputStream or OutputStream and used in any way you may find possible to. Aside from that, Channels can be used natively in most next-gen libraries, meaning that you don't even need to wrap anything, just start writing or reading data to or from the channel wth a ByteBuffer. Anyone using the library should try to rely on code from this module only and, only if necessary, on configuration classes that are implementation specific. Relying on any other resource or class is considered an error and should NOT be done. One of the most interesting usages of channels for uploads and download is that you can easily copy data straight from one channel to the other, with less than 10 lines of code! Also, channels allows the implementation of a "tee" mechanism, in which data redden from a single channel can be copied to several other channels on the fly!