Kaum zu glauben, aber von Apache Commons Logging gibt es noch einmal ein Update. Version 1.2 bietet als “maintenance release containing bug fixes” nichts neues, fixed aber laut https://www.apache.org/dist/commons/logging/RELEASE-NOTES.txt:

o LOGGING-37:   Improve performance of LogFactory#getFactory() by calling
                Thread#currentThread()#getContextClassLoader() directly instead
                of using reflection. As a consequence support for JDK 1.1 has
                been dropped. Thanks to Matthias Ernst, Archie Cobbs.
o LOGGING-156:  Fix SecurityAllowedTestCase when executed with OpenJDK 1.7 due
                to an additional required RuntimePermission. Thanks to Mikolaj Izdebski.
o LOGGING-157:  Fix javadoc to comply with javadoc tool from jdk 1.8. Thanks to Ville Skyttä.

Das auf Groovy basierende Build-Tool Gradle erklimmt eine neue Version: Gradle 2.0.  http://www.gradle.org/docs/current/release-notes zählen auf:

Gradle 2.0 is an important milestone in the evolution of Gradle. As explained in the Gradle 2.0 announcement, the change in major version number signals a new backwards compatibility baseline. Many deprecated features and API have been removed in this release, allowing the development team to simplify the codebase and implement new functionality. The “Potential Breaking Changes” section of these release notes list all of the breaking changes that have been made and all Gradle users are strongly encouraged to read the list.

http://asciidoctor.org/ ist laut Webseite “an open source Ruby processor for converting AsciiDoc markup into HTML 5, DocBook 4.5 and other formats”. Die Software ist in Ruby implementiert und so plattformunabhängig programmiert, dass auch eine Ausführung mit JRuby möglich ist. https://github.com/asciidoctor/asciidoctorj kapselt das in einem netten Projekt, sodass eine Konvertierung direkt mit einer Java-API möglich ist:

import static org.asciidoctor.Asciidoctor.Factory.create;
import org.asciidoctor.Asciidoctor;
...
Asciidoctor asciidoctor = create();
...

String rendered = asciidoctor.render("*This* is it.", Collections.EMPTY_MAP);
System.out.println(rendered);

...
String rendered = asciidoctor.renderFile(new File("target/test-classes/rendersample.asciidoc"), Collections.EMPTY_MAP);
System.out.println(rendered);
...

Mit Optionen:

Map<String, Object> attributes = new HashMap<>();
attributes.put("backend", "docbook");

Map<String, Object> options = new HashMap<>();
options.put("in_place", true);
options.put("attributes", attributes);

String render = asciidoctor.renderFile("target/test-classes/rendersample.asciidoc", options);

Unter der Apache Lizenz:

It is the most standards-compliant Open Source Java persistence product in existence. It is fully compliant with the JDO1, JDO2, JDO2.1, JDO2.2, JDO3, JDO3.1, JPA1, JPA2, JPA2.1 Java standards. It also complies with the OGC Simple Feature Specification for persistence of geospatial Java types to RDBMS. It utilises an OSGi-based plugin mechanism meaning that it is extremely extensible.

http://www.datanucleus.org/. Neues: http://www.datanucleus.org/documentation/news/access_platform_4_0_0_release.html:

• Java 1.8 : Upgrade to ASM v5 to allow for Java 1.8 bytecode changes
• Java 1.8 : support for the majority of java.time types
• Changed the bytecode enhancement contract to use an internal definition rather than the JDO contract
• JPA : no longer needs to have jdo-api.jar present
• Cassandra : support for Cassandra 1.2+
• Support for multicolumn TypeConverters (used by RDBMS, Cassandra, Excel, ODF, Neo4j, MongoDB, JSON, HBase)
• SchemaTool : support for create/delete of a schema (where the datastore supports it)
• RDBMS : support for HikariCP and DBCP2 connection pools
• RDBMS : ability to use single connection per PM/EM (rather than 1 for transactional operations, and 1 for non-transactional operations)
• RDBMS : removed the need to create JavaTypeMapping classes when the user type has a TypeConverter
• JSON : support for embedded 1-1 relation fields/properties
• Excel/ODF/JSON/MongoDB/Neo4j/HBase/Cassandra : move to using „core“ definition of table/columns meaning access to generalised features tested on other datastores