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TDDoc aims to simplify the documentation of testdriven projects by utilizing comments, values and more in the testcases to generate documentation. This release of TDDoc was used to create the documentation for the RMock project. The PDF documentation is made from a generated DocBook XML file. The integrated Maven HTML documentation was made from a generated XDoc file. The documentation for TDDoc is ironically not very extensive, but the source from the Documentation project can serve as a big code example.

Unicode Emoji List for Java is a comprehensive library that provides easy access to the vast world of Unicode emojis. This project aims to offer a user-friendly API for retrieving and utilizing emoji characters and their metadata within Java applications. The library covers a wide range of emojis as defined in the latest Unicode standards, ensuring compatibility and up-to-date representation of emojis across different platforms and devices. Whether for enhancing text processing capabilities, developing chat applications, or for any project requiring emoji support, Unicode Emoji List for Java delivers a robust and reliable solution. Its straightforward implementation allows for seamless integration into existing Java projects, fostering creativity and expanding the expressive potential of digital communication.

RELISON is a framework for experimentation on the link recommendation task in social networks, which aims to identify those people in the network with whom a user might be interested to connect, interact or befriend. RELISON provides tools for executing and evaluating contact recommendation approaches, considering not only their accuracy, but also aspects like their novelty, diversity and the effects that such recommendations have on global properties of the networks (as changes in the structural properties or in the characteristics of the information arriving to the users). In order to measure these effects, RELISON also provides functionality for a) analyzing the structural properties of social networks, b) detecting clusters of users (communities) and c) simulating the diffusion of information in a social network. These functionalities can be used regardless of whether recommendations have been provided to the users.