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Janet Sudoku is a powerful Sudoku Generator and Sudoku Solver library for Java (since jdk 1.5) Android .NET (since 2.0) MONO CLS compliant. Additionally library delivers Janet Sudoku Demo App implementation in a simple form of command line tool, yet highly functional. 1. Sudoku Generator - generate Sudoku puzzles using variety of different methods. 2. Sudoku Solver - Solve any Sudoku puzzle, get the path leading to the correct solution. Check whether unique solution exists. Find all solutions if more than one present. Analyse many built-in examples of Sudoku puzzles or load any other. 3. Manipulate the board by applying transformations not affecting solution existence (i.e. rotation, reflection, permutation, swapping segments, and others). Interact with the library via consisted and well documented API. 4. Janet Sudoku Demo App - use simple, yet highly functional, command line tool to generate, solve evaluate different puzzles.

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.

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!

GlassFish build depends on properly functioning several custom lifecycle mappings and artifact handlers. Because these are necessary to resolve dependencies and to run "gf:run" goal and etc., it is critical that these extensions be made available to Maven early on during Maven execution. This definition was originally in maven-glassfish-plugin, which was integrated into Maven POM through <plugin>/<extensions>true marking, but after a series of debugging to resolve artifact resolution failure problems, it turns out that that doesn't cause Maven to load components early enough. I tried to circumbent the prolem by also registering the maven-glassfish-plugin as an extension module (via <build>/<extensions/<extension>), but that apparently confuses Maven to no end --- I get build errors like this: [INFO] Internal error in the plugin manager executing goal 'org.apache.maven.plugins:maven-jar-plugin:2.1:jar': Unable to find the mojo 'org.apache.maven.plugins:maven-jar-plugin:2.1:jar' in the plugin 'org.apache.maven.plugins:maven-jar-plugin' This is obviously one of the problematic areas of Maven, so to avoid doing hack over hack, I'm simply moving the component definitions to its own module.

Spring LDAP is a Java library for simplifying LDAP operations, based on the pattern of Spring's JdbcTemplate. The framework relieves the user of common chores, such as looking up and closing contexts, looping through results, encoding/decoding values and filters, and more. The LdapTemplate class encapsulates all the plumbing work involved in traditional LDAP programming, such as creating a DirContext, looping through NamingEnumerations, handling exceptions and cleaning up resources. This leaves the programmer to handle the important stuff - where to find data (DNs and Filters) and what do do with it (map to and from domain objects, bind, modify, unbind, etc.), in the same way that JdbcTemplate relieves the programmer of all but the actual SQL and how the data maps to the domain model. In addition to this, Spring LDAP provides transaction support, a pooling library, exception translation from NamingExceptions to a mirrored unchecked Exception hierarchy, as well as several utilities for working with filters, LDAP paths and Attributes.

GlassFish build depends on properly functioning several custom lifecycle mappings and artifact handlers. Because these are necessary to resolve dependencies and to run "gf:run" goal and etc., it is critical that these extensions be made available to Maven early on during Maven execution. This definition was originally in maven-glassfish-plugin, which was integrated into Maven POM through <plugin>/<extensions>true marking, but after a series of debugging to resolve artifact resolution failure problems, it turns out that that doesn't cause Maven to load components early enough. I tried to circumbent the prolem by also registering the maven-glassfish-plugin as an extension module (via <build>/<extensions/<extension>), but that apparently confuses Maven to no end --- I get build errors like this: [INFO] Internal error in the plugin manager executing goal 'org.apache.maven.plugins:maven-jar-plugin:2.1:jar': Unable to find the mojo 'org.apache.maven.plugins:maven-jar-plugin:2.1:jar' in the plugin 'org.apache.maven.plugins:maven-jar-plugin' This is obviously one of the problematic areas of Maven, so to avoid doing hack over hack, I'm simply moving the component definitions to its own module.

This package currently contains classes for training multilayer perceptrons with one hidden layer, where the number of hidden units is user specified. MLPClassifier can be used for classification problems and MLPRegressor is the corresponding class for numeric prediction tasks. The former has as many output units as there are classes, the latter only one output unit. Both minimise a penalised squared error with a quadratic penalty on the (non-bias) weights, i.e., they implement "weight decay", where this penalised error is averaged over all training instances. The size of the penalty can be determined by the user by modifying the "ridge" parameter to control overfitting. The sum of squared weights is multiplied by this parameter before added to the squared error. Both classes use BFGS optimisation by default to find parameters that correspond to a local minimum of the error function. but optionally conjugated gradient descent is available, which can be faster for problems with many parameters. Logistic functions are used as the activation functions for all units apart from the output unit in MLPRegressor, which employs the identity function. Input attributes are standardised to zero mean and unit variance. MLPRegressor also rescales the target attribute (i.e., "class") using standardisation. All network parameters are initialised with small normally distributed random values.

git-commit-id-plugin is a plugin quite similar to https://fisheye.codehaus.org/browse/mojo/tags/buildnumber-maven-plugin-1.0-beta-4 for example but as buildnumber only supports svn (which is very sad) and cvs (which is even more sad). This plugin makes basic repository information available through maven resources. This can be used to display "what version is this?" or "who has deployed this and when, from which branch?" information at runtime - making it easy to find things like "oh, that isn't deployed yet, I'll test it tomorrow" and making both testers and developers life easier. The data currently exported is like this (that's the end effect from the GitRepositoryState Bean): { "branch" : "testing-maven-git-plugin", "commitTime" : "06.01.1970 @ 16:16:26 CET", "commitId" : "787e39f61f99110e74deed68ab9093088d64b969", "commitUserName" : "Konrad Malawski", "commitUserEmail" : "[email protected]", "commitMessageFull" : "releasing my fun plugin :-) + fixed some typos + cleaned up directory structure + added license etc", "commitMessageShort" : "releasing my fun plugin :-)", "buildTime" : "06.01.1970 @ 16:17:53 CET", "buildUserName" : "Konrad Malawski", "buildUserEmail" : "[email protected]" } Note that the data is exported via maven resource filtering and is really easy to use with spring - which I've explained in detail in this readme https://github.com/ktoso/maven-git-commit-id-plugin

Mahout's goal is to build scalable machine learning libraries. With scalable we mean: Scalable to reasonably large data sets. Our core algorithms for clustering, classification and batch based collaborative filtering are implemented on top of Apache Hadoop using the map/reduce paradigm. However we do not restrict contributions to Hadoop based implementations: Contributions that run on a single node or on a non-Hadoop cluster are welcome as well. The core libraries are highly optimized to allow for good performance also for non-distributed algorithms. Scalable to support your business case. Mahout is distributed under a commercially friendly Apache Software license. Scalable community. The goal of Mahout is to build a vibrant, responsive, diverse community to facilitate discussions not only on the project itself but also on potential use cases. Come to the mailing lists to find out more. Currently Mahout supports mainly four use cases: Recommendation mining takes users' behavior and from that tries to find items users might like. Clustering takes e.g. text documents and groups them into groups of topically related documents. Classification learns from existing categorized documents what documents of a specific category look like and is able to assign unlabelled documents to the (hopefully) correct category. Frequent itemset mining takes a set of item groups (terms in a query session, shopping cart content) and identifies, which individual items usually appear together.

# pact-jvm-consumer-java8 Provides a Java8 lambda based DSL for use with Junit to build consumer tests. # A Lambda DSL for Pact This is an extension for the pact DSL provided by [pact-jvm-consumer](../pact-jvm-consumer). The difference between the default pact DSL and this lambda DSL is, as the name suggests, the usage of lambdas. The use of lambdas makes the code much cleaner. ## Why a new DSL implementation? The lambda DSL solves the following two main issues. Both are visible in the following code sample: ```java new PactDslJsonArray() .array() # open an array .stringValue(&quot;a1&quot;) # choose the method that is valid for arrays .stringValue(&quot;a2&quot;) # choose the method that is valid for arrays .closeArray() # close the array .array() # open an array .numberValue(1) # choose the method that is valid for arrays .numberValue(2) # choose the method that is valid for arrays .closeArray() # close the array .array() # open an array .object() # now we work with an object .stringValue(&quot;foo&quot;, &quot;Foo&quot;) # choose the method that is valid for objects .closeObject() # close the object and we&apos;re back in the array .closeArray() # close the array ``` ### The existing DSL is quite error-prone Methods may only be called in certain states. For example `object()` may only be called when you&apos;re currently working on an array whereas `object(name)` is only allowed to be called when working on an object. But both of the methods are available. You&apos;ll find out at runtime if you&apos;re using the correct method. Finally, the need for opening and closing objects and arrays makes usage cumbersome. The lambda DSL has no ambiguous methods and there&apos;s no need to close objects and arrays as all the work on such an object is wrapped in a lamda call. ### The existing DSL is hard to read When formatting your source code with an IDE the code becomes hard to read as there&apos;s no indentation possible. Of course, you could do it by hand but we want auto formatting! Auto formatting works great for the new DSL! ```java array.object((o) -&gt; { o.stringValue(&quot;foo&quot;, &quot;Foo&quot;); # an attribute o.stringValue(&quot;bar&quot;, &quot;Bar&quot;); # an attribute o.object(&quot;tar&quot;, (tarObject) -&gt; { # an attribute with a nested object tarObject.stringValue(&quot;a&quot;, &quot;A&quot;); # attribute of the nested object tarObject.stringValue(&quot;b&quot;, &quot;B&quot;); # attribute of the nested object }) }); ``` ## Installation ### Maven ``` &lt;dependency&gt; &lt;groupId&gt;au.com.dius&lt;/groupId&gt; &lt;artifactId&gt;pact-jvm-consumer-java8_2.12&lt;/artifactId&gt; &lt;version&gt;${pact.version}&lt;/version&gt; &lt;/dependency&gt; ``` ## Usage Start with a static import of `LambdaDsl`. This class contains factory methods for the lambda dsl extension. When you come accross the `body()` method of `PactDslWithProvider` builder start using the new extensions. The call to `LambdaDsl` replaces the call to instance `new PactDslJsonArray()` and `new PactDslJsonBody()` of the pact library. ```java io.pactfoundation.consumer.dsl.LambdaDsl.* ``` ### Response body as json array ```java import static io.pactfoundation.consumer.dsl.LambdaDsl.newJsonArray; ... PactDslWithProvider builder = ... builder.given(&quot;some state&quot;) .uponReceiving(&quot;a request&quot;) .path(&quot;/my-app/my-service&quot;) .method(&quot;GET&quot;) .willRespondWith() .status(200) .body(newJsonArray((a) -&gt; { a.stringValue(&quot;a1&quot;); a.stringValue(&quot;a2&quot;); }).build()); ``` ### Response body as json object ```java import static io.pactfoundation.consumer.dsl.LambdaDsl.newJsonBody; ... PactDslWithProvider builder = ... builder.given(&quot;some state&quot;) .uponReceiving(&quot;a request&quot;) .path(&quot;/my-app/my-service&quot;) .method(&quot;GET&quot;) .willRespondWith() .status(200) .body(newJsonBody((o) -&gt; { o.stringValue(&quot;foo&quot;, &quot;Foo&quot;); o.stringValue(&quot;bar&quot;, &quot;Bar&quot;); }).build()); ``` ### Examples #### Simple Json object When creating simple json structures the difference between the two approaches isn&apos;t big. ##### JSON ```json { &quot;bar&quot;: &quot;Bar&quot;, &quot;foo&quot;: &quot;Foo&quot; } ``` ##### Pact DSL ```java new PactDslJsonBody() .stringValue(&quot;foo&quot;, &quot;Foo&quot;) .stringValue(&quot;bar&quot;, &quot;Bar&quot;) ``` ##### Lambda DSL ```java newJsonBody((o) -&gt; { o.stringValue(&quot;foo&quot;, &quot;Foo&quot;); o.stringValue(&quot;bar&quot;, &quot;Bar&quot;); }).build(); ``` #### An array of arrays When we come to more complex constructs with arrays and nested objects the beauty of lambdas become visible! ##### JSON ```json [ [&quot;a1&quot;, &quot;a2&quot;], [1, 2], [{&quot;foo&quot;: &quot;Foo&quot;}] ] ``` ##### Pact DSL ```java new PactDslJsonArray() .array() .stringValue(&quot;a1&quot;) .stringValue(&quot;a2&quot;) .closeArray() .array() .numberValue(1) .numberValue(2) .closeArray() .array() .object() .stringValue(&quot;foo&quot;, &quot;Foo&quot;) .closeObject() .closeArray(); ``` ##### Lambda DSL ```java newJsonArray((rootArray) -&gt; { rootArray.array((a) -&gt; a.stringValue(&quot;a1&quot;).stringValue(&quot;a2&quot;)); rootArray.array((a) -&gt; a.numberValue(1).numberValue(2)); rootArray.array((a) -&gt; a.object((o) -&gt; o.stringValue(&quot;foo&quot;, &quot;Foo&quot;))); }).build(); ``` `object` is a reserved word in Kotlin. To allow using the DSL without escaping, a Kotlin extension `newObject` is available: ```kotlin newJsonArray { rootArray -&gt; rootArray.array { a -&gt; a.stringValue(&quot;a1&quot;).stringValue(&quot;a2&quot;) } rootArray.array { a -&gt; a.numberValue(1).numberValue(2) } rootArray.array { a -&gt; a.newObject { o -&gt; o.stringValue(&quot;foo&quot;, &quot;Foo&quot;) } } }.build(); ```