Download JAR files tagged by sets with all dependencies

Clirr is a tool that checks Java libraries for binary compatibility with older releases. Basically you give it two sets of jar files and Clirr dumps out a list of changes in the public api. Clirr provides an Ant task that can be configured to break the build if it detects incompatible api changes. In a continuous integration process Clirr can automatically prevent accidental introduction of binary compatibility problems in Java libraries.

fastutil extends the Java Collections Framework by providing type-specific maps, sets, lists, and queues with a small memory footprint and fast operations; it provides also big (64-bit) arrays, sets, and lists, sorting algorithms, fast, practical I/O classes for binary and text files, and facilities for memory mapping large files. This jar (fastutil-core.jar) contains data structures based on integers, longs, doubles, and objects, only; fastutil.jar contains all classes. If you have both jars in your dependencies, this jar should be excluded.

This artifact provides the implementation of the L* learning algorithm described in the paper "Learning Regular Sets from Queries and Counterexamples" (https://doi.org/10.1016/0890-5401(87)90052-6) by Dana Angluin including variations and optimizations thereof such as the versions based on "On the Learnability of Infinitary Regular Sets" (https://dx.doi.org/10.1006/inco.1995.1070) by Oded Maler and Amir Pnueli or "Inference of finite automata using homing sequences" (http://dx.doi.org/10.1006/inco.1993.1021) by Ronald L. Rivest and Robert E. Schapire.

fastutil extends the Java Collections Framework by providing type-specific maps, sets, lists, and queues with a small memory footprint and fast operations; it provides also big (64-bit) arrays, sets, and lists, sorting algorithms, fast, practical I/O classes for binary and text files, and facilities for memory mapping large files. This jar (fastutil-core.jar) contains data structures based on integers, longs, doubles, and objects, only; fastutil.jar contains all classes. If you have both jars in your dependencies, this jar should be excluded.

The Data Highway is a service that allows data to be easily landed and consumed via REST interfaces which accept and produce JSON messages. The data is first defined using a schema and a "road" is created which will accept data messages that conform to this schema. Producers of data sets thus only need to define the structure of their data and are then able to send their data to a REST endpoint and not be too concerned with what happens next. The Data Highway will ensure that this data is made available for downstream streaming consumption and also stored reliably in a "data lake" in the cloud for access by various end users.

This is the parent module for all components of the Djenni framework - a test data generation framework that sets out to introduce better practices in test data management and generation. The core goals are: - to reduce the amount of time developers and testers spend manually crafting data - to make tests clearer by only focusing on the key data elements - to make tests even more complete by fuzzing data elements that are not deemed key to the test - to better support later test phases by helping developers to provide data generators suitable for large scale data generation in a thread safe / multi-threadable manner.

This module provides algorithms to compare sets, that is, order-invariant lists. These algorithms are implementations of the AlignmentAlgorithm interface defined in the algorithms module. In particular, this module contains the StrictSetAlignmentScoreAlgorithm for computing the cost of the optimal unordered alignment of two sets, the StrictSetAlignmentFullAlgorithm which provides the Alignment itself as well, and the GreedySetAlignmentScoreAlgorithm as well as the GreedySetAlignmentFullAlgorithm for computing a potentially sub-optimal but faster alignment of two sets. The optimal alignments rely on the HungarianAlgorithm for solving the assignment problem in bipartite graphs. Here, we rely on the implementation provided by Kevin L. Stern which is provided within this distribution.

This module contains the sequence datastructure of the TCS Alignment Toolbox. It defines the possible value sets in the ValueType enum as well as the different KeywordSpecification classes, namely: 1.) StringKeywordSpecification for string type values. 2.) SymbolicKeywordSpecification for values from a discrete alphabet (also refer to the Alphabet class) 3.) VectorialKeywordSpecification for vectors of some length (or for scalars) A NodeSpecification is a vector of such KeywordSpecifications and defines the order of value sets. A node, then, is defined as a vector of values from these value sets (also refer to the Value interface as well as the StringValue, SymbolicValue and VectorialValue classes). Finally a sequence is defined as a list of such nodes.