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"Kiama is a Scala library for language processing. It enables convenient analysis and transformation of structured data. The programming styles supported by the library are based on well-known formal language processing paradigms, including attribute grammars, tree rewriting, abstract state machines, and pretty printing."

SubScript, a way to extend common programming languages aimed to ease event handling and concurrency. Typical application areas are GUI controllers, text processing applications and discrete event simulations. SubScript is based on a mathematical concurrency theory named Algebra of Communicating Processes (ACP). ACP is a 30-year-old branch of mathematics, as solid as numeric algebra and as Boolean algebra. In fact, you can regard ACP as an extension to Boolean algebra with 'things that can happen'. These items are glued together with operations such alternative, sequential and parallel compositions. This way ACP combines the essence of grammar specification languages and notions of parallelism.

"Datomic is a distributed database designed to enable scalable, flexible and intelligent applications, running on next-generation cloud architectures. It does this by: Bringing declarative data manipulation into the application, and the data with it Getting time, process and perception right Process (writes) require coordination Perception (reads) require none The past doesn't change Leveraging immutability, and a sound model of state Datomic has: ACID Transactions Joins A sound data model A logical query language - Datalog Thus, Datomic avoids the compromises and losses of many NoSQL solutions. In addition, it offers flexibility and power over the traditional model in supporting: Hierarchy Multi-valued attributes Minimal schema Reliable operation on unreliable, ephemeral cloud instances Time Datomic avoids manual caching and replication, complex configuration, sharding (automatic or manual), logging, locking, latching and disk management of traditional servers."

"HDF (Hierarchical Data Format) technologies are relevant when the data challenges being faced push the limits of what can be addressed by traditional database systems, XML documents, or in-house data formats. Leveraging the powerful HDF products and the expertise of The HDF Group, organizations realize substantial cost savings while solving challenges that seemed intractable using other data management technologies. Many HDF adopters have very large datasets, very fast access requirements, or very complex datasets. Others turn to HDF because it allows them to easily share data across a wide variety of computational platforms using applications written in different programming languages. Some use HDF to take advantage of the many open-source and commercial tools that understand HDF. Similar to XML documents, HDF files are self-describing and allow users to specify complex data relationships and dependencies. In contrast to XML documents, HDF files can contain binary data (in many representations) and allow direct access to parts of the file without first parsing the entire contents. HDF, not surprisingly, allows hierarchical data objects to be expressed in a very natural manner, in contrast to the tables of relational database. Whereas relational databases support tables, HDF supports n-dimensional datasets and each element in the dataset may itself be a complex object. Relational databases offer excellent support for queries based on field matching, but are not well-suited for sequentially processing all records in the database or for subsetting the data based on coordinate-style lookup."

"Welcome to Scala Puzzlers, the collection of Traps, Pitfalls and Corner Cases in the Scala language. Prepare to be surprised, entertained and...well, puzzled! What is presented here is a selection of seemingly simple examples which demonstrate that there's plenty of head-scratching left in Scala. Let your mind be challenged by unexpected and unintuitive behaviour and results and learn something in the process. "