Download JAR files tagged by compute with all dependencies

Webapp Watcher (WAW) is a Java EE Filter which alows you to log the requests response times and Java stack traces of a Java EE web application (.war). You can later compute usage statistics of the web application, and also track down potential bugs with the tool "waw-analyzer"

Webapp Watcher (WAW) is a Java EE Filter which alows you to log the requests response times and Java stack traces of a Java EE web application (.war). You can later compute usage statistics of the web application, and also track down potential bugs with the tool "waw-analyzer"

This package contains Microsoft Azure SDK for SqlVirtualMachine Management SDK. For documentation on how to use this package, please see https://aka.ms/azsdk/java/mgmt. The SQL virtual machine management API provides a RESTful set of web APIs that interact with Azure Compute, Network & Storage services to manage your SQL Server virtual machine. The API enables users to create, delete and retrieve a SQL virtual machine, SQL virtual machine group or availability group listener. Package tag package-preview-2022-08.

This package contains Microsoft Azure Compute Management SDK.

Tool used to analyze a set of classes and determine on what other classes they directly or indirectly depend. Typically this tool is used to compute the necessary and sufficient set of classes to include in a JAR file, for use in the class path of a client or service, or for use in the codebase of a client or service. The tool starts with a set of "root" classes and recursively computes a dependency graph, finding all of the classes referenced directly by the root classes, finding all of the classes referenced in turn by those classes, and so on, until no new classes are found or until classes that are not of interest are found. The normal output of the tool is a list of all of the classes in the dependency graph. The output from this command can be used as input to the jar tool, to create a JAR file containing precisely those classes.

A filter that applies the LOF (Local Outlier Factor) algorithm to compute an outlier score for each instance in the data. Can use multiple cores/cpus to speed up the LOF computation for large datasets. Nearest neighbor search methods and distance functions are pluggable. For more information, see: Markus M. Breunig, Hans-Peter Kriegel, Raymond T. Ng, Jorg Sander (2000). LOF: Identifying Density-Based Local Outliers. ACM SIGMOD Record. 29(2):93-104.

YET ANOTHER IMPLEMENTATION OF LEVENSHTEIN DISTANCE GenericLevenshtein is an implementation of Minimum Edit Distance, also called Levenshtein Distance, written by Ramon Ziai and Niels Ott. This algorithm is very popular and it is often used to compute the similarity of strings. The difference in the presented implementation is that it can operate on sequences of any Java object implementing equals(Object). So no matter if you want to compare genome sequences or sequences of numbers, or just strings, here you go! Furthermore, the costs of the replace, insert, and delete operations can be customized by implementing the simple WeightCalculator<T> interface. In that case it is not a requirement to rely on equals(Object) as your implementation can do whatever you like it to do in oder to compare objects.

The Java Algebra System (JAS) is an object oriented, type safe and multi-threaded approach to computer algebra. JAS provides a well designed software library using generic types for algebraic computations implemented in the Java programming language using the JVM runtime infrastructure. The library can be used as any other Java software package or it can be used interactively or interpreted through a jython (Java Python) or jruby (Java Ruby) front end, there is also an Android App based on Ruboto (jruby for Android). The focus of JAS is at the moment on commutative, solvable and non-commutative polynomials, power series, Groebner bases, factorization, real and complex roots and applications. By the use of Java as implementation language JAS is 64-bit and multi-core CPU ready and can make use of mutiple CPUs where available. JAS can run on a wide variety of devices ranging from Android to compute clusters (using MPJ a Java Message Passing Interface (MPI) or OpenMPI).